Advertisement

Linking EORTC QLQ-C-30 and PedsQL/PEDQOL physical functioning scores in patients with osteosarcoma

Open AccessPublished:June 08, 2022DOI:https://doi.org/10.1016/j.ejca.2022.03.018

      Highlights

      • Score linking is a promising method for linking physical functioning scores obtained with paediatric and adult quality-of-life (QoL) questionnaires in a population of survivors of childhood osteosarcoma.
      • The method provides methodological rigour for quality-of-life (QoL) assessments across the lifespan of cancer patients when the use of distinct age-group-specific inventories is unavoidable.
      • The approach may create the conditions for conducting longitudinal mixed-model meta-analyses.

      Abstract

      Purpose

      The available questionnaires for quality-of-life (QoL) assessments are age-group specific, limiting comparability and impeding longitudinal analyses. The comparability of measurements, however, is a necessary condition for gaining scientific evidence. To overcome this problem, we assessed the viability of harmonising data from paediatric and adult patient-reported outcome (PRO) measures.

      Method

      To this end, we linked physical functioning scores from the Paediatric Quality of Life Inventory (PedsQL) and the Paediatric Quality of Life Questionnaire (PEDQOL) to the European Organisation for Research and Treatment of Cancer Core Questionnaire (EORTC QLQ-C30) for adults. Samples from the EURAMOS-1 QoL sub-study of 75 (PedsQL) and 112 (PEDQOL) adolescent osteosarcoma patients were concurrently administered both paediatric and adult questionnaires on 98 (PedsQL) and 156 (PEDQOL) occasions. We identified corresponding scores using the single-group equipercentile linking method.

      Results

      Linked physical functioning scores showed sufficient concordance to the EORTC QLQ-C30: Lin's ρ = 0.74 (PedsQL) and Lin's ρ = 0.64 (PEDQOL).

      Conclusion

      Score linking provides clinicians and researchers with a common metric for assessing QoL with PRO measures across the entire lifespan of patients.

      Keywords

      Abbreviations:

      COG (Children's Oncology Group), COSS (Cooperative Osteosarcoma Group), EOI (European Osteosarcoma Intergroup), EORTC QLQ-C30 (European Organisation for Research and Treatment of Cancer Core Questionnaire), EURAMOS-1 (EUropean AMerican Osteosarcoma Study-1), FACT-G (Functional Assessment of Cancer Therapy - General), IRT (Item Response Theory), LOA (Limit of Agreement), PEDQOL (Paediatric Quality Of Life Questionnaire), PedsQL (Paediatric Quality of Life Inventory), PRO (Patient-Reported Outcome), PROMIS (Patient-Reported Outcomes Measurement Information System), QoL (Quality-of-Life), SSG (Scandinavian Sarcoma Group)

      1. Introduction

      Quality-of-life (QoL) data are generally collected by self-report questionnaires. Health-related QoL questionnaires can be age-group specific. This age group specificity limits comparability and impedes numerical longitudinal analysis, especially if different instruments are needed to span the age range of the study. Specifically, the motivation for linking scores from paediatric and adult instruments was to make them comparable on a common scale, allowing the study of the QoL developmental trajectory continuously and permitting the analysis with mixed models.
      The use of different instruments constitutes a considerable hurdle for the analysis and interpretation of QoL data, since “[t]he comparability of measurements made in differing circumstances by different methods and investigators is a fundamental pre-condition for all of science” [
      • Dorans Neil J.
      • Holland Paul W.
      Population invariance and the equatability of tests: basic theory and the linear case.
      ]. Therefore, valid methods for linking scores are required.
      Dorans provides an overview of applying linking methodology within the realm of patient-reported outcome (PRO) measures [
      • Neil J.
      Dorans. Linking scores from multiple health outcome instruments.
      ] (Table 1).
      Table 1Publications on linking PRO measures.
      Publications
      Adults
       Health status [
      • Marrie Ruth Ann
      • Dufault Brenden
      • Tyry Tuula
      • Cutter Gary R.
      • Fox Robert J.
      • Salter Amber
      Developing a crosswalk between the rand-12 and the health utilities index for multiple sclerosis.
      ,
      • Shaw Bronwen E.
      • Syrjala Karen L.
      • Onstad Lynn E.
      • Chow Eric J.
      • Flowers Mary E.
      • Jim Heather
      • Scott Baker K.
      • Buckley Sarah
      • Fairclough Diane L.
      • Horowitz Mary M.
      • Lee Stephanie J.
      Promis measures can be used to assess symptoms and function in long-term hematopoietic cell transplantation survivors.
      ,
      • Kaat Aaron J.
      • Schalet Benjamin D.
      • Rutsohn Joshua
      • Jensen Roxanne E.
      • Cella David
      Physical function metric over measure: an illustration with the patient-reported outcomes measurement information system (promis) and the functional assessment of cancer therapy (fact).
      ,
      • McHorney C.A.
      • Cohen A.S.
      Equating health status measures with item response theory: illustrations with functional status items.
      ]
       Physical functioning [
      • Schalet Benjamin D.
      • Rothrock Nan E.
      • Hays Ron D.
      • Kazis Lewis E.
      • Cook Karon F.
      • Rutsohn Joshua P.
      • Cella David
      Linking physical and mental health summary scores from the veterans rand 12-item health survey (vr-12) to the promis Ⓡ global health scale.
      • Haley Stephen M.
      • Ni Pengsheng
      • Lai Jin-shei
      • Tian Feng
      • Coster Wendy J.
      • Jette Alan M.
      • Straub Donald
      • Cella David
      Linking the activity measure for post-acute care and the quality of life outcomes in neurological disorders.
      ]
       Physical and mental health summary scores [
      • Schalet Benjamin D.
      • Revicki Dennis A.
      • Cook Karon F.
      • Krishnan Eswar
      • Fries Jim F.
      • Cella David
      Establishing a common metric for physical function: linking the haq-di and sf-36 pf subscale to promis® physical function.
      ]
       Self-regulation [
      • Mâsse Louise C.
      • Allen Diane
      • Wilson Mark
      • Williams Geoffrey
      Introducing equating methodologies to compare test scores from two different self-regulation scales.
      ]
       Depression [
      • Kaat Aaron J.
      • Newcomb Michael E.
      • Ryan Daniel T.
      • Mustanski Brian
      Expanding a common metric for depression reporting: linking two scales to promis® depression.
      ,
      • Choi Seung W.
      • Schalet Benjamin
      • Cook Karon F.
      • Cella David
      Establishing a common metric for depressive symptoms: linking the bdi-ii, ces-d, and phq-9 to promis depression.
      ,
      • Tulsky David S.
      • Kisala Pamela A.
      • Kalpakjian Claire Z.
      • Bombardier Charles H.
      • Pohlig Ryan T.
      • Heinemann Allen W.
      • Adam Carle
      • Choi Seung W.
      Measuring depression after spinal cord injury: development and psychometric characteristics of the sci-qol depression item bank and linkage with phq-9.
      ,
      • Olino Thomas M.
      • Lan Yu
      • McMakin Dana L.
      • Forbes Erika E.
      • Seeley John R.
      • Lewinsohn Peter M.
      • Pilkonis Paul A.
      Comparisons across depression assessment instruments in adolescence and young adulthood: an item response theory study using two linking methods.
      ,
      • Orlando M.
      • Sherbourne C.D.
      • Thissen D.
      Summed-score linking using item response theory: application to depression measurement.
      ]
       Pain [
      • Cook Karon F.
      • Schalet Benjamin D.
      • Kallen Michael A.
      • Rutsohn Joshua P.
      • Cella David
      Establishing a common metric for self-reported pain: linking bpi pain interference and sf-36 bodily pain subscale scores to the promis pain interference metric.
      ]
       Pain interference [
      • Askew Robert L.
      • Kim Jiseon
      • Chung Hyewon
      • Cook Karon F.
      • Johnson Kurt L.
      • Amtmann Dagmar
      Development of a crosswalk for pain interference measured by the bpi and promis pain interference short form.
      ]
       Anxiety [
      • Kisala Pamela A.
      • Tulsky David S.
      • Kalpakjian Claire Z.
      • Heinemann Allen W.
      • Pohlig Ryan T.
      • Adam Carle
      • Choi Seung W.
      Measuring anxiety after spinal cord injury: development and psychometric characteristics of the sci-qol anxiety item bank and linkage with gad-7.
      ,
      • Schalet Benjamin D.
      • Cook Karon F.
      • Choi Seung W.
      • Cella David
      Establishing a common metric for self-reported anxiety: linking the masq, panas, and gad-7 to promis anxiety.
      ,
      • Lai Jin-shei
      • Cella David
      • Yanez Betina
      • Stone Arthur
      Linking fatigue measures on a common reporting metric.
      ,
      • Noonan Vanessa K.
      • Cook Karon F.
      • Bamer Alyssa M.
      • Choi Seung W.
      • Kim Jiseon
      • Amtmann Dagmar
      Measuring fatigue in persons with multiple sclerosis: creating a crosswalk between the modified fatigue impact scale and the promis fatigue short form.
      ]
       Fatigue [
      • Lai Jin-shei
      • Cella David
      • Yanez Betina
      • Stone Arthur
      Linking fatigue measures on a common reporting metric.
      ,
      • Noonan Vanessa K.
      • Cook Karon F.
      • Bamer Alyssa M.
      • Choi Seung W.
      • Kim Jiseon
      • Amtmann Dagmar
      Measuring fatigue in persons with multiple sclerosis: creating a crosswalk between the modified fatigue impact scale and the promis fatigue short form.
      ]
       EORTC QLQ-C30 <> FACT-G [
      • Holzner B.
      • Bode R.K.
      • Hahn E.A.
      • Cella D.
      • Kopp M.
      • Sperner-Unterweger B.
      • Kemmler G.
      Equating eortc qlq-c30 and fact-g scores and its use in oncological research.
      ]
      Children <> Adults
       Emotional distress [
      • Reeve Bryce B.
      • Thissen David
      • DeWalt Darren A.
      • Huang I-Chan
      • Liu Yang
      • Magnus Brooke
      • et al.
      Linkage between the promis(r) pediatric and adult emotional distress measures.
      ]
       Physical functioning in a population of individuals with spinal cord injury [
      • Tian Feng
      • Ni Pengsheng
      • Mulcahey M.J.
      • Hambleton Ronald K.
      • Tulsky David
      • Haley Stephen M.
      • Jette Alan M.
      Tracking functional status across the spinal cord injury lifespan: linking pediatric and adult patient-reported outcome scores.
      ]
      In the present study, we evaluated the viability of linking physical functioning scores of two paediatric PRO questionnaires (the PedsQL and the PEDQOL) to the EORTC QLQ-C30) in a population of survivors of childhood osteosarcoma. We restrict our report to the physical functioning domain because we were mainly interested in the viability of linking paediatric and adult instruments. We provide information on linking emotional functioning, cognitive functioning, social functioning, fatigue and pain domains in the appendix.

      2. Materials and methods

      The overall study design [
      • Marina N.
      • Bielack S.
      • Whelan J.
      • Smeland S.
      • Krailo M.
      • Sydes M.R.
      • Butterfass-Bahloul T.
      • Calaminus G.
      • Bernstein M.
      International collaboration is feasible in trials for rare conditions: the euramos experience.
      ,
      • Whelan J.S.
      • Bielack S.S.
      • Marina N.
      • Smeland S.
      • Jovic G.
      • Hook J.M.
      • et al.
      Euramos-1, an international randomised study for osteosarcoma: results from pre-randomisation treatment.
      ] and the methodological specifics of the QoL questionnaire sub-study have been laid out in detail previously [
      • Calaminus Gabriele
      • Jenney Meriel
      • Hjorth Lars
      • Baust Katja
      • Bernstein Mark
      • Bielack Stefan
      • De Vos Patricia
      • Pancras C.
      • Hogendoorn W.
      • Jovic Gordana
      • Krailo Mark
      • Kreitz Kiana
      • Marina Neyssa
      • Popoola Babasola O.
      • Sauerland Cristina
      • Smeland Sigbjørn
      • Teske Carmen
      • Schweinitz Clara V.
      • Whelan Jeremy
      • Wiener Andreas
      • Sydes Matthew R.
      • Nagarajan Rajaram
      Quality of life of patients with osteosarcoma in the european american osteosarcoma study-1 (euramos-1): development and implementation of a questionnaire substudy.
      ]. We briefly describe the study design.

      2.1 Participants

      The EURAMOS-1 trial cohort consisted of 2260 participants who, between the ages 5 and 40 years old, had been diagnosed with a previously untreated resectable high-grade osteosarcoma (at any site, except for craniofacial structures). Among these, 2213 participants were eligible for QoL-assessment (≥5 years old) and had a questionnaire in their respective language available (see [
      • Calaminus Gabriele
      • Jenney Meriel
      • Hjorth Lars
      • Baust Katja
      • Bernstein Mark
      • Bielack Stefan
      • De Vos Patricia
      • Pancras C.
      • Hogendoorn W.
      • Jovic Gordana
      • Krailo Mark
      • Kreitz Kiana
      • Marina Neyssa
      • Popoola Babasola O.
      • Sauerland Cristina
      • Smeland Sigbjørn
      • Teske Carmen
      • Schweinitz Clara V.
      • Whelan Jeremy
      • Wiener Andreas
      • Sydes Matthew R.
      • Nagarajan Rajaram
      Quality of life of patients with osteosarcoma in the european american osteosarcoma study-1 (euramos-1): development and implementation of a questionnaire substudy.
      ]). Recruitment took place between 2005 and 2011, involving 17 countries and four study groups: the Children's Oncology Group (COG), the Cooperative Osteosarcoma Group (COSS), the European Osteosarcoma Intergroup (EOI), and the Scandinavian Sarcoma Group (SSG). EURAMOS-1 consortium members and their affiliations are listed in Appendix E.1. We obtained demographics from the EURAMOS-1 enrolment survey (sex, date of birth, and study group). Age was stratified as “5 to 15”, “16 to 17” and “18 or older”. As a secondary outcome measure, QoL was assessed prospectively at four time points during and after treatment (Fig. 1).

      2.2 Questionnaires

      Due to the unavailability of a single questionnaire suited for use across the whole age span of participants and in all participating countries, the EURAMOS-1 consortium opted for using different, age- and country-specific instruments (Table 2a).
      Table 2aQoL questionnaire by region and age group.
      QuestionnaireRegionAge group
      ≥5 −1516–17≥18
      PedsQLCOG (North America) &

      EOI (North West Europe)
      ++
      PEDQOLCOSS (Central Europe) & SSG (Scandinavia)++
      EORTC

      QLQ-C30
      All++
      In the age range 16–18 years old, all patients were asked to complete a paediatric questionnaire (either PedsQL [
      • Varni James W.
      • Seid Michael
      • Rode Cheryl A.
      The pedsql™: measurement model for the pediatric quality of life inventory.
      ] or PEDQOL [
      • Calaminus G.
      • Weinspach S.
      • Teske C.
      • Göbel U.
      Quality of life in children and adolescents with cancer. first results of an evaluation of 49 patients with the pedqol questionnaire.
      ]) and the EORTC QLQ-C30 [
      • Aaronson N.K.
      • Ahmedzai S.
      • Bergman B.
      • Bullinger M.
      • Cull A.
      • Duez N.J.
      • Filiberti A.
      • Flechtner H.
      • Fleishman S.B.
      • de Haes J.C.
      The european organization for research and treatment of cancer qlq-c30: a quality-of-life instrument for use in international clinical trials in oncology.
      ]. We used this sub-sample for score linking. We restricted our study to aggregate scores pertaining to physical functioning, given its significance to QoL in osteosarcoma survivors and the substantial conceptual overlap between instruments in this domain. We linked two sub-sets of participants aged 16–17 years. These sub-sets were administered either the PedsQL or the PEDQOL questionnaire before the EORTC QLQ-C30 on the same day.

      2.3 Analyses

      2.3.1 Similarity of item content and physical functioning sub-scale structure between instruments

      The PedsQL, the PEDQOL and the EORTC QLQ-C30 all contain items that assess the physical functioning domain with multiple items (for details on scoring, see Table 2b and for verbatim item content see Appendix F).
      Table 2bQoL questionnaires physical functioning scoring.
      QuestionnaireNumber of itemsScale pointsPeriod
      PedsQL45Past month
      PEDQOL44Past week
      EORTC QLQ-C3054Past week
      Item content showed substantial overlap across the three measures. To measure internal consistency of the instruments, we calculated Cronbach’s α. A summary of the results is given in Table 2c.
      Table 2cInternal consistency reliability of the physical functioning aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toN1Cronbach's α (95% CI)Item–total correlation2
      MinMeanMax
      E1PedsQLEORTC QLQ-C30380.87 (0.80, 0.93)0.430.690.82
      PEDQOL410.68 (0.52, 0.85)0.490.600.68
      EORTC QLQ-C30PedsQL380.80 (0.70, 0.89)0.350.650.79
      PEDQOL410.88 (0.82, 0.94)0.620.770.86
      E2PedsQLEORTC QLQ-C30240.73 (0.57, 0.88)0.280.510.82
      PEDQOL470.47 (0.22, 0.72)0.060.480.68
      EORTC QLQ-C30PedsQL240.73 (0.58, 0.87)0.260.610.75
      PEDQOL470.82 (0.73, 0.90)0.530.680.77
      E3PedsQLEORTC QLQ-C30200.77 (0.63, 0.92)0.420.570.67
      PEDQOL410.60 (0.40, 0.80)0.420.540.59
      EORTC QLQ-C30PedsQL200.76 (0.61, 0.91)0.430.700.85
      PEDQOL410.78 (0.69, 0.87)0.450.670.80
      E4PedsQLEORTC QLQ-C30160.86 (0.76, 0.95)0.340.680.88
      PEDQOL270.65 (0.44, 0.86)0.280.590.74
      EORTC QLQ-C30PedsQL160.85 (0.74, 0.95)0.600.790.90
      PEDQOL270.74 (0.59, 0.89)0.310.640.75
      1 N refers to the number of participants in which Cronbach's α was measured for the instrument in the second column when linked to the instrument in the third column.
      2 Item–total correlation indicates the correlation between the score on a single item and the aggregate physical functioning sub-scale score.

      2.3.2 Summary of physical functioning raw scores, correlation and concordance between instruments

      The overall mean physical functioning score, i.e. across all four time points, was 51.6 (SD = 22.7) for the PedsQL and 74.3 (SD = 22.3) for the corresponding EORTC QLQ-C30 (n = 98). The overall mean for physical functioning of the PEDQOL was 46.8 (SD = 25.1) and the corresponding EORTC QLQ-C30 overall mean was 63.5 (SD = 27.2) (n = 156).
      The correlations between the EORTC QLQ-C30 physical functioning sub-scale and the corresponding aggregate scores of the two paediatric instruments were both good, but the PedsQL physical functioning raw scores correlated more strongly (r = 0.73; 95% confidence interval (CI): 0.63, 0.81) than those of the PEDQOL (r = 0.64; CI: 0.54, 0.73). The physical functioning raw scores of the paediatric questionnaires showed only moderate agreement with those of the EORTC QLQ-C30 before linking, with similar values for the PedsQL (Lin's ρ = 0.49; CI: 0.63, 0.81) and the PEDQOL (Lin's ρ = 0.53; CI: 0.43, 0.63). Given a substantial overlap in item content, we linked the respective aggregate physical functioning scores of the PedsQL and the PEDQOL questionnaires to their EORTC QLQ-C30 equivalent.

      2.3.3 Linking design

      To produce physical functioning crosswalks (score conversion tables), we linked scores of those participants who had completed one of the two paediatric instruments and the EORTC QLQ-C30 at the same time point. This group consisted of participants who were 16–18 years old. This linking technique, referred to as the single-group design, is akin to a repeated measures design with a single group and two treatments [
      • von Davier A.
      Statistical Models for test equating, scaling, and linking.
      ]. It is considered the most valid linking design because the scores of identical individuals are linked, thus requiring the smallest sample size to achieve the same level of accuracy as designs with a lesser degree of group equivalency [
      • Lord Frederic M.
      Notes on comparable scales for test scores.
      ].
      To ensure that the instruments to be linked showed sufficient conceptual congruity [
      • Neil J.
      Dorans. Linking scores from multiple health outcome instruments.
      ], we employed two methods, modelling our approach on Choi et al. (2014) and Marrie et al. (2020). First, we reviewed the content of the physical functioning items of the three instruments to ensure that they indeed measure approximately the same concept. Second, to assess internal consistency, we calculated Cronbach's α for the three questionnaires.

      2.3.4 Linking function

      We performed identity, mean, linear, equipercentile and circle-arc linking procedures (Fig. 2). Previously, we had applied log-linear pre-smoothing to three moments to adjust for potential sampling error introduced by uneven score distributions [
      • Kolen Michael J.
      • Brennan Robert L.
      Test equating, scaling, and linking: Methods and practices. Statistics for Social and Behavioral Sciences.
      ]. Log-linear pre-smoothing is a recommended procedure for small samples such as ours because a smoothed distribution yields more reliable results [
      • Kolen Michael J.
      • Brennan Robert L.
      Test equating, scaling, and linking: Methods and practices. Statistics for Social and Behavioral Sciences.
      ]. We used root mean square error (RMSE) by means of parametric bootstrapping to determine the best linking method (for details see [
      • equate Anthony D. Albano
      An r package for observed-score linking and equating.
      ], 5.7).
      Fig. 2
      Fig. 2Five functions linking physical functioning scores.
      We chose the equipercentile linking method to produce crosswalk tables, as it emerged as the method with the most favourable linking quality parameters, overall.

      2.3.5 Evaluation of linking quality

      As a first step towards ascertaining the agreement between paediatric and adult QoL instruments, we created Bland–Altman plots [
      • Bland J.M.
      • Altman D.G.
      Statistical methods for assessing agreement between two methods of clinical measurement.
      ] (Fig. 3 and Table 2d). We plotted the differences (y-axis) for scores linked from each paediatric questionnaire and those measured by the EORTC QLQ-C30 against subject means (x-axis) to check for patterns and distributions. Following Zhou et al. [
      • Zhou Xiaoyan
      • Dibley Michael J.
      • Cheng Yue
      • Ouyang Xue
      • Yan Hong
      Validity of self-reported weight, height and resultant body mass index in Chinese adolescents and factors associated with errors in self-reports.
      ], we established that the limits of agreement for linked and measured scores were to be considered ”good” if they fell within one standard deviation (SD) of the mean of measured EORTC QLQ-C30 scores, ”fair” if they did not extend beyond two SDs, and ”poor”, otherwise.
      Fig. 3
      Fig. 3Bland–Altman plots for linked vs. observed physical functioning scores.
      Table 2dBland–Altman plots: descriptive characteristics.
      Bland–Altman analysis
      ParameterCountValueSD95% CI
      PedsQLBias980.5315.92(−2.66, 3.72)
      Upper

      LOA
      9831.73(26.26, 37.21)
      Lower

      LOA
      98−30.67(−36.15, −25.20)
      PedQOLBias156−0.3222.84(−3.94, 3.29)
      Upper

      LOA
      15644.44(38.25, 50.62)
      Lower

      LOA
      156−45.09(−51.27, −38.90)
      Additionally, we calculated Pearson's correlation coefficient r and Lin's concordance correlation coefficient between each of the two paediatric measures and the EORTC QLQ-C30.
      We prepared histograms of the differences between measured and linked EORTC QLQ-C30 scores to visually inspect whether the distributions approximate normality (Fig. 4).
      Fig. 4
      Fig. 4Histograms with distributions of differences between physical functioning scores.
      Details on software are given in Appendix A.

      3. Results

      3.1 Participant characteristics

      The QoL sub-sample consisted of 2213 osteosarcoma patients. The mean age at registration was 15.1 (SD = 5.3) years. Out of the complete sub-sample, 760 participants had completed the PedsQL in the physical functioning domain at one or more of the four time points, and 337 had completed the PEDQOL in this domain at one time point or more. Out of these participants, 75 participants between the ages of 16 and 18 had completed both the PedsQL and the EORTC QLQ-C30 in the physical functioning domain at the same time point on 98 occasions, and 112 had completed both the PEDQOL and the EORTC QLQ-C30 concurrently on 156 occasions.
      Table 3a gives an overview of patient characteristics by linked questionnaire (PedsQL or PEDQOL) for the physical functioning domain, including sex, age, and study group, overall and by linked sub-sample.
      Table 3aCharacteristics of participants in the physical functioning domain by paediatric questionnaire, overall and linked.
      CharacteristicsPhysical functioning
      The columns pertain to those participants whose PedsQL or PEDQOL scores were linked to their respective EORTC QLQ-C30 scores. Therefore, the table does not contain a separate column for EORTC QLQ-C30 scores.
      PedsQLPEDQOL
      OverallLinked to EORTC

      QLQ-C30
      OverallLinked to EORTC

      QLQ-C30
      Sex, n(%)
       Male429

      (56)
      48

      (64)
      171

      (51)
      68

      (61)
       Female331

      (44)
      27

      (36)
      164

      (49)
      44

      (39)
      Age (years)
      Age refers to the age at the time of registration for participation in the study.
      Age group, n(%)
       5 to 15671

      (88)
      44

      (59)
      275

      (82)
      70

      (62)
       16 to 1774

      (10)
      22

      (29)
      59

      (18)
      42

      (38)
       18 or older15

      (2)
      9

      (12)
      1

      (0)
      0

      (0)
       Mean (SD)12.8

      (3.0)
      15.1

      (2.7)
      13.4

      (2.9)
      15.6

      (1.3)
      Study group, n(%)
       COG616

      (81)
      96

      (98)
      0

      (0)
      0

      (0)
       COSS0

      (0)
      0

      (0)
      211

      (63)
      83

      (74)
       EOI144

      (19)
      2

      (2)
      59

      (18)
      22

      (20)
       SSG0

      (0)
      0

      (0)
      65

      (19)
      7

      (6)
      COG: Childrens's Oncology Group; COSS: Cooperative Osteosarcoma Group; EOI: European Osteosarcoma Intergroup; SSG: Scandinavian Sarcoma Group.
      1 The columns pertain to those participants whose PedsQL or PEDQOL scores were linked to their respective EORTC QLQ-C30 scores. Therefore, the table does not contain a separate column for EORTC QLQ-C30 scores.
      2 Age refers to the age at the time of registration for participation in the study.

      3.1.1 Bland–Altman plots

      We used Bland–Altman plots to compare PedsQL and PEDQOL scores to EORTC QLQ C-30 scores. The interpretation of Bland–Altman plots is premised on normality and homoscedasticity of the distribution. We prepared histograms for the distributions of differences (Fig. 4 and Table 2d) to make a first visual assessment. We then prepared Bland–Altman plots (Fig. 3) displaying the differences in scores between each paediatric instrument and the EORTC QLQ-C30 against the respective means.
      To inspect for heteroscedasticity, we prepared quantile–quantile (Q–Q) plots (Fig. 5) for differences between scores linked from the two paediatric questionnaires and EORTC QLQ-C30 scores. We judged that scores linked from the PEDQOL displayed adequate homoscedasticity. However, scores linked from the PedsQL indicated an uneven, left-skewed distribution. Therefore, we log-transformed the score differences, achieving better overall homoscedasticity, albeit with a remaining left skew (Fig. 6). To account for the presence of substantial heteroscedasticity in scores linked from the PedsQL, we prepared a Bland–Altman plot on log-transformed data (Fig. 7a) which indicated a better fit of limits of agreement. Given that log-transformed scores do not lend themselves to easy interpretation for clinical practice, we additionally plotted the score differences in a conventional Bland–Altman plot on the original scale with back-transformed limits of agreement (Fig. 7b) [
      • Euser Anne M.
      • Dekker Friedo W.
      • Le Cessie Saskia
      A practical approach to Bland-Altman plots and variation coefficients for log transformed variables.
      ,
      • Brehm Merel-Anne
      • Scholtes Vanessa A.
      • Dallmeijer Annet J.
      • Twisk Jos W.
      • Harlaar Jaap
      The importance of addressing heteroscedasticity in the reliability analysis of ratio-scaled variables: an example based on walking energy-cost measurements.
      ].
      Fig. 5
      Fig. 5Quantile–quantile plots of differences between physical functioning scores.
      Fig. 6
      Fig. 6Quantile–quantile plot of logarithm of differences between PedsQL and EORTC QLQ-C30 physical functioning scores (n = 98).
      Fig. 7
      Fig. 7Bland–Altman plots for linked vs. observed log-transformed and back-transformed physical functioning scores (n = 98).
      Summarily, we judged agreement for physical functioning scores acceptable, as the limits of agreement did not extend beyond two standard deviations of EORTC QLQ-C30 scores for either of the paediatric instruments, and the majority of scores being within one standard deviation of EORTC QLQ-C30 scores.

      3.1.2 Correlations between physical functioning aggregate scores of paediatric and adult instruments

      Additionally, we calculated Pearson's r and Lin's ρ− [
      • Lin L.I.
      A concordance correlation coefficient to evaluate reproducibility.
      ] concordance correlation coefficients between the EORTC QLQ-C30 and the PedsQL and PEDQOL physical functioning converted scores.
      The correlation coefficients for physical functioning scores were good for both the PedsQL and the PEDQOL to EORTC QLQ-C30 conversions, with a Lin's ρ of 0.74 and 0.64, respectively (Table 3b and 3c).
      Table 3bPaediatric questionnaires and EORTC QLQ-C30: Correlation and concordance coefficients post-linking.
      CoefficientPhysical functioning
      PedsQLPEDQOL
      Pearson's r (95% CI)0.74 (0.64–0.82)0.64 (0.54–0.72)
      Lin's ρ (95% CI)0.74 (0.64–0.82)0.64 (0.54–0.72)
      Table 3cInterpretation of concordance correlation coefficients [
      • Bland J.M.
      • Altman D.G.
      Statistical methods for assessing agreement between two methods of clinical measurement.
      ].
      Concordance

      Correlation coefficient
      Strength of agreement
      <0.20Poor
      0.21–0.40Fair
      0.41–0.60Moderate
      0.61–0.80Good
      0.81–1.00Very good

      3.1.3 Correlations between other aggregate scores of paediatric and adult instruments

      The converted scores of the PedsQL and PEDQOL fatigue both correlated well with EORTC QLQ-C30 scores (Lin's ρ = 0.69 and Lin's ρ = 0.71). Correlation coefficients for pain were moderate for the PedsQL (Lin's ρ = 0.58) and good for the PEDQOL (Lin's ρ = 0.73). Correlation coefficients for emotional functioning were moderate (Lin's ρ = 0.55) for the PedsQL and fair for PEDQOL (Lin's ρ = 0.36) conversions to EORTC QLQ-C30 scores. The correlation of converted cognitive functioning scores with EORTC QLQ-C30 scores was fair for the PedsQL (Lin's ρ = 0.37) and moderate for the PEDQOL (Lin's ρ = 0.47). Converted social functioning scores correlated poorly with EORTC QLQ-C30 scores for both, the PedsQL (Lin's ρ = 0.17) and the PEDQOL PedsQL (Lin's ρ = 0.08).

      4. Discussion

      Data harmonisation provides a number of benefits by permitting the pooling of data, such as answering novel research questions or increasing statistical power. Despite a growing interest in harmonising data, retrospective data harmonisation (after data collection) is the rule and prospective harmonisation (before data collection) the exception [
      • Marrie Ruth Ann
      • Dufault Brenden
      • Tyry Tuula
      • Cutter Gary R.
      • Fox Robert J.
      • Salter Amber
      Developing a crosswalk between the rand-12 and the health utilities index for multiple sclerosis.
      ]. While it may be due to a lack of foresight or practicability that retrospective data harmonisation remains the only option, harmonising data prospectively may also be inherently impossible. This was the case in the international research collaboration the present study grew out of which included longitudinal QoL assessments in adult survivors of childhood osteosarcoma. The use of different PRO measures during childhood and adulthood was unavoidable, as no suitable instrument for both age groups existed.
      To obtain harmonised data retrospectively, we linked the scores from two paediatric PRO measures to an adult PRO measure to assess the quality of life across the lifespan of osteosarcoma survivors. Visual and numerical concordance assessments indicated good agreement between physical functioning aggregate scores. The equipercentile linking method yielded the best overall results for this sample. Sub-sets consisting of 75 (PedsQL) and 112 participants (PEDQOL) yielded 98 (PedsQL) and 156 (PEDQOL) score pairings between paediatric and adult questionnaires and were sufficient to permit score linking for the whole cohort and enabled the analysis of QoL data for a forthcoming publication.
      In domains other than physical functioning, the concordance estimates obtained with Pearson's r diverged from those obtained with dedicated concordance coefficients (Appendix, Table D.1), thus confirming that Pearson's r is not a useful measure for assessing intra-individual agreement. The Pearson correlation coefficient (Pearson's r) is generally not considered a suitable measure of concordance because it is only informative if the relationship between two variables is linear, thus potentially leading to incorrect conclusions in case of non-linearity. Crucially, Pearson's r only evaluates the extent of a linear relationship on a population level, ignoring intra-individual concordance. Despite its apparent shortcomings, Pearson's r continues to be widely employed in the score linking literature as a measure of agreement between two instruments. This is all the more surprising, given that non-linear score linking methods were presumably developed to specifically account for non-linear agreement between two instruments. Due to its continued popularity and to underscore differences between concordance measures, we nevertheless included Pearson's r alongside Lin's concordance correlation coefficient ρ [
      • Lin L.I.
      A concordance correlation coefficient to evaluate reproducibility.
      ] which we consider more apt. We provide an evaluation according to value ranges to allow a verbal interpretation, similar to the kappa concordance coefficient for binary variables [
      • Bland J.M.
      • Altman D.G.
      Statistical methods for assessing agreement between two methods of clinical measurement.
      ], with five categories, ranging from ”Poor” to ”Very Good” (Table 3c).
      Building on McNemar's coefficient of alienation, Dorans [
      • Neil J.
      Dorans. Equating, concordance, and expectation.
      ] defined ”Reduction in Uncertainty”. Since a 50% reduction in uncertainty, as measured in score units, requires a Pearson's r of at least 0.866, Dorans recommended a correlation of this magnitude as an appropriate lower bound. This recommendation was made in the context of high-stakes educational testing, as Choi and colleagues [
      • Choi Seung W.
      • Schalet Benjamin
      • Cook Karon F.
      • Cella David
      Establishing a common metric for depressive symptoms: linking the bdi-ii, ces-d, and phq-9 to promis depression.
      ] have pointed out. For linking health outcome measures, they suggesteda correlation of 0.75–0.80 as an appropriate minimum, given that aggregate outcomes are the focus of interest, and in particular when using a single-group design which permits the direct evaluation of accuracy.
      A limitation of our study is that our results may not be population invariant, i.e. the linking quality parameters we obtained may not generalise to other populations. Previous studies linking PedsQL or PEDQOL physical functioning aggregate scores to the EORTC QLQ-C30 are lacking. Therefore, we were unable to draw comparisons to similar or dissimilar populations and we cannot generalise our findings beyond the highly selective clinical population our sample was drawn from. The aim of our study was to evaluate the feasibility of linking paediatric and adult PRO measures within a population of osteosarcoma survivors. Clearly, our findings are restricted to this narrowly circumscribed area of clinical practice and research. The methodology also does not allow for harmonisation in completely disparate age groups (e.g. 5-10 year-old with 35–40 year-old).
      The use of age-adequate (i.e. age-specific) questionnaires for children seems unavoidable, rendering a direct comparison of paediatric and adult scores in survivors of childhood cancer inherently impossible. Therefore, we see the potential general utility of score linking in this field in offering interoperability of paediatric and adult PRO measures, and the specific value of this study in showing the viability of this approach for the first time. Having established its feasibility, the approach described may be integrated in future study designs involving dissimilar populations. Doing so may yield evidence regarding the population invariance of our results.
      Another limitation of our study is that we cannot rule out an order effect, i.e. the relationship of the instruments may have depended on the order of their administration. This point should be addressed in future investigations by randomising the order of administration. In a similar vein, the administration of two questionnaires at the same point may have biased the responses to the second questionnaire. Randomising the order of administration should also reduce fatigue bias, by equalising the directionality of such an effect between the instruments.
      We consider the single-group design a major strength of our study, as it provides the firmest methodological grounds for score linking. Its inherent potential disadvantages should be balanced against its strengths and against the weaknesses of alternative linking designs. Using a single-group design, we obtained actual and linking-derived scores from the same population. This allowed us to evaluate the accuracy of our linking functions directly. As a tangible product, we created crosswalk tables between PedsQL and PEDQOL physical functioning aggregate scores (see Appendix, Table L.1) which will bring forward data harmonisation and will enable us to perform longitudinal analyses within the EURAMOS-1 cohort.
      With score linking, it is possible to directly compare scores of osteosarcoma patients obtained with distinct age-group-specific inventories and observe their QoL across the entire lifespan. The approach may create the conditions for conducting longitudinal mixed-model meta-analyses. We consider score linking a promising tool for assuring comparability of intra-individual QoL assessments in studies over time and extending across different stages of life. We anticipate that oncological QoL research may strongly benefit from score linking.

      Funding

      The study sponsor was the UK Medical Research Council in Europe and the US National Cancer Institute in North America and Australia. Each trial group organised local coordination elements; central coordination and analysis was led from Medical Research Council Clinical Trials Unit at University College of London. Neither the sponsors nor the funders of the trial had a role in trial design, data analysis, or data interpretation. The EURAMOS-1 is an academic clinical trial funded through multiple national and international government agencies and cancer charities: - Children's Oncology Group funding for the EURAMOS-1 trial (AOST0331) was supported by the National Clinical Trial Network (NCTN) Operations Centre Grant U10CA180886, NCTN Statistics and Data Center Grant U10CA180899 and St. Baldrick's Foundation. - European Science Foundation under the European Science Foundation Collaborative Research Programme for Pan-European Clinical Trials, through contract number ERASCT-2003-980409 of the European Commission, DG Research, FP6 (Ref No MM/NG/EMRC/0202) National funding in Europe was provided by the following:
      • Belgium: Fonds National de la Recherche Scientifique Belgium FWO (Fonds voor Wetenschappelijk Onderzoek-Vlaanderen)
      • Denmark: Danish Medical Research Council
      • Finland: Academy of Finland
      • Germany: Deutsche Forschungsgemeinschaft ref No: BI 1045/1-1 & 1–2, Deutsche Krebshilfe (DKH) ref No: 50-2723-Bi2
      • Hungary: Semmelweis Foundation
      • Netherlands: ZonMw (Council for Medical Research)
      • Norway: Research Council of Norway
      • Sweden: SSG and Swedish Childhood Cancer Fund
      • Switzerland: Swiss Paediatric Oncology Group
      • United Kingdom: includes funding for the trial coordinating data centre (MRC Clinical Trials Unit at UCL): Cancer Research UK, CRUK/05/013, Medical Research Council: MC_UU_12023/28.
      Additional funding to the University of Münster Centre for Clinical Trials, site of the EURAMOS Intergroup Safety Desk: Federal Ministry of Education and Research, Germany, BMBF 01KN1105.

      CRediT authorship contribution statement

      Axel Budde: Conceptualisation, Data curation, Formal analysis, Methodology, Software, Writing - original draft preparation, Visualisation. Katja Baust: Conceptualisation, Data curation, Writing - review and editing, Project administration. Leonie Weinhold: Methodology, Validation, Writing - review & editing. Mark Bernstein: Investigation, Writing - review and editing. Stefan Bielack: Investigation, Writing - review and editing. Catharina Dhooge: Investigation, Writing - review and editing. Lars Hjorth: Investigation, Writing - review and editing. Katherine A. Janeway: Investigation, Writing - review and editing. Meriel Jenney: Investigation, Writing - review and editing. Mark D. Krailo: Investigation, Writing - review and editing. Neyssa Marina: Investigation, Writing - review and editing. Rajaram Nagarajan: Investigation, Writing - review and editing. Sigbjørn Smeland: Investigation, Writing - review and editing. Matthew R. Sydes: Investigation, Methodology, Writing - review and editing. Patricia DeVos: Investigation, Writing - review and editing. Jeremy Whelan: Investigation, Writing - review and editing. Andreas Wiener: Investigation, Writing - review and editing. Gabriele Calaminus: Conceptualisation, Investigation, Writing - review and editing, Supervision. Matthias Schmid: Conceptualisation, Methodology, Writing - review and editing, Supervision.

      Conflict of interest statement

      The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: SB reports grants from Deutsche Krebshilfe, Deutsche Forschungsgemeinschaft, and European Science Foundation during the conduct of the study and personal fees from Lilly, Bayer, Pfizer, Novartis, Isofol, Clinigen, Sensorion, Ipsen, and Roche outside the submitted work. MRS reports grants and nonfinancial support from Astellas, grants from Clovis, grants and nonfinancial support from Janssen, grants and nonfinancial support from Novartis, grants and nonfinancial support from Pfizer, and grants and nonfinancial support from Sanofi, during the conduct of the study and personal fees from Lilly Oncology and personal fees from Janssen for educational courses and workshops outside the submitted work. NM reports employment by Five Prime Therapeutics, Inc and Sanofi US, outside the submitted work. The remaining authors declare no conflicts of interest.

      Acknowledgements

      The authors thank all the patients and parents for their contribution and all data managers, especially Ms Eva-Mari Olofsson from the SSG office in Lund, for their support to collect the data from all the patients in timely order.

      Appendix A. Supplementary data

      The following is the supplementary data to this article:

      A. Software

      We conducted all statistical analyses using version 4.1.0 of the R platform, version 2.0.7 of R package equate for score linking, R package blandr for the calculation of concordance correlation coefficients and the tidyverse suite of R packages for data preparation and data visualisation.

      B. Characteristics of participants by domain, overall and linked.

      Table B.1Characteristics of PedsQL participants by domain, overall and linked.
      CharacteristicsPedsQL participants by domain
      FunctionalSymptom
      Physical FunctioningEmotional FunctioningCognitive FunctioningSocial FunctioningFatiguePain
      OverallLinkedOverallLinkedOverallLinkedOverallLinkedOverallLinkedOverallLinked
      Sex, n(%)
       Male429

      (56)
      48

      (64)
      445

      (57)
      51

      (64)
      395

      (57)
      45

      (64)
      439

      (56)
      45

      (64)
      445

      (57)
      45

      (64)
      443

      (57)
      48

      (62)
       Female331

      (44)
      27

      (36)
      339

      (43)
      29

      (36)
      296

      (43)
      25

      (36)
      339

      (44)
      25

      (36)
      341

      (43)
      25

      (36)
      341

      (44)
      29

      (38)
      Age (years)
      Age refers to the age at the time of registration for participation in the study.
      Age group, n(%)
       5 to 15671

      (88)
      44

      (59)
      690

      (88)
      48

      (60)
      609

      (88)
      43

      (61)
      685

      (88)
      43

      (61)
      694

      (88)
      43

      (61)
      692

      (88)
      47

      (61)
       16 to 1774

      (10)
      22

      (29)
      78

      (10)
      30

      (29)
      69

      (10)
      20

      (29)
      77

      (10)
      20

      (29)
      76

      (10)
      20

      (29)
      76

      (10)
      21

      (27)
       18 or older15

      (2)
      9

      (12)
      16

      (2)
      7

      (11)
      13

      (2)
      9

      (10)
      16

      (2)
      7

      (10)
      16

      (2)
      7

      (10)
      16

      (2)
      9

      (12)
       Mean(SD)12.8

      (3.0)
      15.1

      (2.7)
      12.8

      (3.0)
      15.1

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.1

      (2.7)
      Study group, n(%)
       COG616

      (81)
      73

      (97)
      640

      (82)
      78

      (98)
      562

      (81)
      68

      (97)
      632

      (81)
      68

      (97)
      639

      (81)
      68

      (97)
      638

      (81)
      75

      (97)
       COSS0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
       EOI144

      (19)
      2

      (3)
      144

      (18)
      2

      (2)
      129

      (19)
      2

      (3)
      146

      (19)
      2

      (3)
      147

      (19)
      2

      (3)
      146

      (19)
      2

      (3)
       SSG0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      COG: Childrens's Oncology Group; COSS: Cooperative Osteosarcoma Group; EOI: European Osteosarcoma Intergroup; SSG: Scandinavian Sarcoma Group.
      1 Age refers to the age at the time of registration for participation in the study.
      Table B.2Characteristics of PEDQOL participants by domain, overall and linked.
      CharacteristicsPedsQL participants by domain
      FunctionalSymptom
      Physical FunctioningEmotional FunctioningCognitive FunctioningSocial FunctioningFatiguePain
      OverallLinkedOverallLinkedOverallLinkedOverallLinkedOverallLinkedOverallLinked
      Sex, n(%)
       Male429

      (56)
      48

      (64)
      445

      (57)
      51

      (64)
      395

      (57)
      45

      (64)
      439

      (56)
      45

      (64)
      445

      (57)
      45

      (64)
      443

      (57)
      48

      (62)
       Female331

      (44)
      27

      (36)
      339

      (43)
      29

      (36)
      296

      (43)
      25

      (36)
      339

      (44)
      25

      (36)
      341

      (43)
      25

      (36)
      341

      (44)
      29

      (38)
      Age (years)
      Age refers to the age at the time of registration for participation in the study.
      Age group, n(%)
       5 to 15671

      (88)
      44

      (59)
      690

      (88)
      48

      (60)
      609

      (88)
      43

      (61)
      685

      (88)
      43

      (61)
      694

      (88)
      43

      (61)
      692

      (88)
      47

      (61)
       16 to 1774

      (10)
      22

      (29)
      78

      (10)
      30

      (29)
      69

      (10)
      20

      (29)
      77

      (10)
      20

      (29)
      76

      (10)
      20

      (29)
      76

      (10)
      21

      (27)
       18 or older15

      (2)
      9

      (12)
      16

      (2)
      7

      (11)
      13

      (2)
      9

      (10)
      16

      (2)
      7

      (10)
      16

      (2)
      7

      (10)
      16

      (2)
      9

      (12)
       Mean(SD)12.8

      (3.0)
      15.1

      (2.7)
      12.8

      (3.0)
      15.1

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.0

      (2.6)
      12.8

      (3.0)
      15.1

      (2.7)
      Study group, n(%)
       COG616

      (81)
      73

      (97)
      640

      (82)
      78

      (98)
      562

      (81)
      68

      (97)
      632

      (81)
      68

      (97)
      639

      (81)
      68

      (97)
      638

      (81)
      75

      (97)
       COSS0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
       EOI144

      (19)
      2

      (3)
      144

      (18)
      2

      (2)
      129

      (19)
      2

      (3)
      146

      (19)
      2

      (3)
      147

      (19)
      2

      (3)
      146

      (19)
      2

      (3)
       SSG0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      0

      (0)
      COG: Childrens's Oncology Group; COSS: Cooperative Osteosarcoma Group; EOI: European Osteosarcoma Intergroup; SSG: Scandinavian Sarcoma Group.
      1 Age refers to the age at the time of registration for participation in the study.

      C. Internal consistency reliability of the three instruments by domain.

      Table C.1Internal consistency reliability of the emotional functioning aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toNCronbach's α (95% CI)Item–total correlation
      MinMeanMax
      E1PedsQLEORTC QLQ-C30390.74 (0.61, 0.87)0.360.620.82
      PEDQOL470.56 (0.70, 0.84)0.310.600.79
      EORTC QLQ-C30PedsQL390.72 (0.82, 0.91)0.520.720.91
      PEDQOL470.73 (0.82, 0.90)0.650.710.80
      E2PedsQLEORTC QLQ-C30290.72 (0.82, 0.93)0.440.710.80
      PEDQOL510.61 (0.73, 0.85)0.370.630.77
      EORTC QLQ-C30PedsQL290.73 (0.82, 0.92)0.560.730.85
      PEDQOL510.72 (0.81, 0.90)0.550.710.81
      E3PedsQLEORTC QLQ-C30190.60 (0.77, 0.93)0.550.650.79
      PEDQOL430.35 (0.56, 0.77)0.380.480.75
      EORTC QLQ-C30PedsQL190.60 (0.77, 0.95)0.590.730.87
      PEDQOL430.67 (0.78, 0.88)0.550.680.82
      E4PedsQLEORTC QLQ-C30180.66 (0.81, 0.95)0.290.700.87
      PEDQOL320.45 (0.65, 0.85)0.390.560.76
      EORTC QLQ-C30PedsQL180.55 (0.73, 0.91)0.370.630.77
      PEDQOL320.65 (0.77, 0.90)0.480.670.73
      Table C.2Internal consistency reliability of the cognitive functioning aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toNCronbach's α (95% CI)Item–total correlation
      MinMeanMax
      E1PedsQLEORTC QLQ-C30330.47(0.14, 0.80)0.470.470.47
      PEDQOL360.76(0.63, 0.88)0.410.630.76
      EORTC QLQ-C30PedsQL330.06(-0.56, 0.68)0.130.130.13
      PEDQOL380.66(0.45, 0.88)0.610.610.61
      E2PedsQLEORTC QLQ-C30180.56(0.18, 0.94)0.540.540.54
      PEDQOL330.68(0.50, 0.85)0.360.540.68
      EORTC QLQ-C30PedsQL180.21(-0.47, 0.88)0.270.270.27
      PEDQOL330.41(0.01, 0.81)0.410.410.41
      E3PedsQLEORTC QLQ-C30190.80(0.62, 0.97)0.750.750.75
      PEDQOL410.84(0.77, 0.92)0.530.720.81
      EORTC QLQ-C30PedsQL190.62(0.36, 0.87)0.660.660.66
      PEDQOL410.33(-0.07.0.74)0.350.350.35
      E4PedsQLEORTC QLQ-C30160.94(0.89, 1.00)0.920.920.92
      PEDQOL320.74(0.60, 0.88)0.540.620.76
      EORTC QLQ-C30PedsQL160.04(-0.88, 0.97)0.110.110.11
      PEDQOL410.33(-0.07, 0.74)0.690.690.69
      Table C.3Internal consistency reliability of the social functioning aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toNCronbach's α (95% CI)Item–total correlation
      MinMeanMax
      E1PedsQLEORTC QLQ-C30380.34(−0.01, 0.69)0.170.420.65
      PEDQOL470.24(−0.09, 0.58)0.050.300.53
      EORTC QLQ-C30PedsQL380.66(0.45, 0.87)0.610.610.61
      PEDQOL470.67(0.49, 0.86)0.620.620.62
      E2PedsQLEORTC QLQ-C30270.62(0.41, 0.83)0.390.570.67
      PEDQOL40−0.22(−0.81, 0.38)−0.330.200.81
      EORTC QLQ-C30PedsQL270.61(0.32, 0.90)0.570.570.57
      PEDQOL400.70(0.52, 0.89)0.650.650.65
      E3PedsQLEORTC QLQ-C30190.48(0.14, 0.83)−0.100.460.71
      PEDQOL28−0.27(−1.05, 0.50)−0.500.150.49
      EORTC QLQ-C30PedsQL190.79(0.62, 0.96)0.760.760.76
      PEDQOL280.58(0.30, 0.86)0.570.570.57
      E4PedsQLEORTC QLQ-C30170.60(0.36, 0.85)0.320.500.68
      PEDQOL24−0.02(−0.68, 0.64)−0.030.210.71
      EORTC QLQ-C30PedsQL170.78(0.58, 0.98)0.740.740.74
      PEDQOL240.89(0.81, 0.98)0.850.850.85
      Table C.4Internal consistency reliability of the fatigue aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toNCronbach's α (95% CI)Item–total correlation
      MinMeanMax
      E1PedsQLEORTC QLQ-C3040
      PEDQOL50
      EORTC QLQ-C30PedsQL400.82(0.71, 0.93)0.770.770.77
      PEDQOL500.89(0.83, 0.95)0.850.850.85
      E2PedsQLEORTC QLQ-C3030
      PEDQOL54
      EORTC QLQ-C30PedsQL300.64(0.39, 0.90)0.590.590.59
      PEDQOL540.85(0.77, 0.93)0.800.800.80
      E3PedsQLEORTC QLQ-C3019
      PEDQOL45
      EORTC QLQ-C30PedsQL190.87(0.75, 0.99)0.820.820.82
      PEDQOL450.88(0.81, 0.95)0.830.830.83
      E4PedsQLEORTC QLQ-C3017
      PEDQOL32
      EORTC QLQ-C30PedsQL170.73(0.50, 0.97)0.700.700.70
      PEDQOL320.59(0.35, 0.83)0.590.590.59
      Table C.5Internal consistency reliability of the pain aggregate scores of the three instruments.
      Time pointQuestionnaireLinked toNCronbach's α (95% CI)Item–total correlation
      MinMeanMax
      E1PedsQLEORTC QLQ-C3040
      PEDQOL50
      EORTC QLQ-C30PedsQL400.82(0.71, 0.93)0.770.770.77
      PEDQOL500.89(0.83, 0.95)0.850.850.85
      E2PedsQLEORTC QLQ-C3030
      PEDQOL54
      EORTC QLQ-C30PedsQL300.64(0.39, 0.90)0.590.590.59
      PEDQOL540.85(0.77, 0.93)0.800.800.80
      E3PedsQLEORTC QLQ-C3019
      PEDQOL45
      EORTC QLQ-C30PedsQL190.87(0.75, 0.99)0.820.820.82
      PEDQOL450.88(0.81, 0.95)0.830.830.83
      E4PedsQLEORTC QLQ-C3017
      PEDQOL32
      EORTC QLQ-C30PedsQL170.73(0.50, 0.97)0.700.700.70
      PEDQOL320.59(0.35, 0.83)0.590.590.59

      D. Paediatric questionnaires and EORTC QLQ-C30: concordance measures.

      Table D.1Paediatric questionnaires and EORTC QLQ-C30: concordance measures.
      Concordance CoefficientQuestionnaireDomain
      FunctionalSymptom
      Physical FunctioningEmotional FunctioningCognitive FunctioningSocial FunctioningFatiguePain
      Pearson's r (95% CI)PedsQL

      PEDQOL
      0.74 (0.64–0.82)

      0.64 (0.54–0.72)
      0.64 (0.52–0.74)

      0.58 (0.47–0.67)
      0.37 (0.17–0.54)

      0.57 (0.45–0.67)
      0.27 (0.07–0.44)

      0.16 (−0.01–0.32)
      0.70 (0.58–0.78)

      0.72 (0.64–0.78)
      0.59 (0.45–0.70)

      0.73 (0.67–0.78)
      Lin's ρ (95% CI)PedsQL

      PEDQOL
      0.74 (0.64–0.82)

      0.64 (0.54–0.72)
      0.55 (0.42–0.65)

      0.36 (0.27–0.44)
      0.37 (0.17-0-54)

      0.47 (0.35–0.58)
      0.17 (0.05–0.29)

      0.08 (−0.01–0.16)
      0.69 (0.58–0.78)

      0.71 (0.63–0.77)
      0.58 (0.45–0.69)

      0.73 (0.65–0.79)

      E. EURAMOS-1 consortium.

      Table E.1EURAMOS-1 consortium.
      NameSurnameAffiliation

      Dept/Programme/Centre
      Institution NameCityCountry
      SigbjørnSmelandInstitute for Clinical MedicineOslo University HospitalOsloNO
      Stefan SBielackOlgahospital StuttgartKlinikum StuttgartStuttgartDE
      JeremyWhelanUniversity College HospitalLondonUK
      MarkBernsteinIWK Health CenterDalhousie UniversityHalifax, NSCA
      KirstenSundby HallInstitute for Clinical MedicineOslo University HospitalOsloNO
      CatherineRechnitzerRigshospitaletUniversity of CopenhagenCopenhagenDK
      MikaelErikssonLund UniversityLundSE
      ImreAntalSemmelweis UniversityBudapestHU
      GodehardFriedelThoracic surgeryKlinik SchillerhöheGerlingenDE
      StefanieHecker-NoltingOlgahospital StuttgartKlinikum StuttgartStuttgartDE
      EditaKabickovaMotol University HospitalPragueCZ
      LeoKagerSt. Anna Kinderspital/CCRIViennaAT
      ThomasKühneUniversity Hospital BaselBaselCH
      SusannaLangMedical University of ViennaViennaAT
      RegineMayer-SteinackerUniversity Hospital UlmUlmDE
      PeterReichardtHELIOS Klinikum Berlin-BuchBerlinDE
      BeateTimmermannUniversity Hospital EssenEssenDE
      Theklavon KalleOlgahospital StuttgartKlinikum StuttgartStuttgartDE
      CarolaArndtMayo ClinicRochester, MNUS
      Ching CLauBaylor College of MedicineHouston, TXUS
      Cindy LSchwartzM D Anderson Cancer CenterUniversity of TexasHouston, TXUS
      Douglas SHawkinsUniversity of WashingtonSeattle, WAUS
      Holcombe EGrierDana-Farber Cancer InstituteBoston, MAUS
      Katherine AJanewayDana-Farber Cancer InstituteBoston, MAUS
      Ken L BBrownUniversity of British ColumbiaVancouver, BCCA
      LeoMascarenhasKeck School of MedicineUniversity of Southern CaliforniaLos Angeles, CAUS
      LisaTeotBoston Children's HospitalBoston, MAUS
      Mark CGebhardtDana-Farber Cancer InstituteBoston, MAUS
      Mark DKrailoChildren's Oncology GroupArcadia, CAUS
      Michael SIsakoffConnecticut Children's Medical CenterHartford, CTUS
      Patrick JLeaveySouthwestern Children's Medical CenterUniversity of TexasDallas, TXUS
      Paul AMeyersMSKCCNew York, NYUS
      R LorRandallPrimary Childrens HospitalThe University of UtahSLC, UTUS
      RajNagarajanChildren's Hospital Medical CenterCincinnati, OHUS
      RichardGorlickM D Anderson Cancer CenterThe University of TexasHouston, TXUS
      RobertGoldsbyPaediatric OncologyUCSF Medical Center–Mission BaySF, CAUS
      Stephen LLessnickNationwide Children's Hospital/OSUColumbus, OHUS
      CatherinaDhoogeUniversity Hospital GhentGhentBE
      MichaelCapraOur Lady's Children's HospitalDublinIE
      JakobAnningaNL
      Adrienne MFlanaganCancer InstituteRNOH/UCLStanmore/LondonUK
      RobertGrimerRoyal Orthopaedic HospitalBirminghamUK
      SandraStraussUniversity College HospitalLondonUK
      HansGelderblomLeiden University Medical CenterLeidenNL
      MarleenRenardUniversity Hospital LeuvenLeuvenBE
      FionaInglebyMRC Clinical Trials UnitUniversity College LondonLondonUK
      GordanaJovicMRC Clinical Trials UnitUniversity College LondonLondonUK
      TrudeButterfaß-BahloulUniversity Hospital MünsterMünsterDE
      GabrieleCalaminusPaediatric Haematology and OncologyUniversity Hospital BonnBonnDE
      PancrasHogendoornLeiden University Medical CenterLeidenNL
      Matthew RSydesMRC Clinical Trials UnitUniversity College LondonLondonUK
      NeyssaMarinaFive Prime Therapeutics, IncSouth SF, CAUS

      F. Physical functioning items per questionnaire.

      F.1 PedsQL physical functioning items.

      In the past ONE month, how much of a problem has this been for you …
      Table F.1PedsQL physical functioning items.
      About My Health and Activities (problems with …)NeverAlmost

      Never
      SometimesOftenAlways
      1. It is hard for me to walk more than one block.
      2. It is hard for me to run.
      3. It is hard for me to do sports activity or exercise.
      4. It is hard for me to lift something heavy.
      5. It is hard for me to take a bath or shower by myself.
      6. It is hard for me to do chores around the house.
      7. I hurt or ache.
      8. I have low energy

      F.2 PEDQOL physical functioning items.

      Table F.2PEDQOL physical functioning items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1…. konnte ich mit meinen Freunden beim Sport mithalten./… I was able to keep up with my friends in sports.
      2…. habe ich beim Spielen und beim Sport lieber zugesehen als mitgespielt./ … I watched rather than played in games and sports.
      3…. habe ich mich stark gefühlt./… I felt strong.
      4…. fühlte ich mich fit genug, um nach der Schule mit meinen Freunden zu spielen/ … I felt fit enough to play with my friends after school.

      F.3 EORTC QLQ-C30 physical functioning items.

      Table F.3EORTC QLQ-C30 physical functioning items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Were you short of breath?
      2. Have you had pain?
      3. Did you need to rest?
      4. Have you had trouble sleeping?
      5. Have you felt weak?

      G. Emotional functioning items per questionnaire.

      G.1 PedsQL emotional functioning items.

      In the past ONE month, how much of a problem has this been for you …
      Table G.1PedsQL emotional functioning items.
      About My Feelings (problems with …)NeverAlmost NeverSometimesOftenAlways
      1. I feel afraid or scared.
      2. I feel sad or blue.
      3. I feel angry.
      4. I have trouble sleeping.
      5. I worry about what will happen to me.

      G.2 PEDQOL emotional functioning items.

      Table G.2PEDQOL emotional functioning items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1…. fühlte ich mich alleine./ … I felt alone.
      2…. war ich ärgerlich./ … I have been annoyed.
      3…. fühlte ich mich glücklich./ … I felt happy.
      4…. habe ich viel gelacht und Spaßgehabt./ … I have laughed a lot and had fun.

      G.3 EORTC QLQ-C30 emotional functioning items.

      Table G.3EORTC QLQ-C30 emotional functioning items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Did you feel tense?
      2. Did you worry?
      3. Did you feel irritable?
      4. Did you feel depressed?

      H. Cognitive functioning items per questionnaire.

      H.1 PedsQL cognitive functioning items.

      In the past ONE month, how much of a problem has this been for you …
      Table H.1PedsQL cognitive functioning items.
      About School (problems with …)NeverAlmost NeverSometimesOftenAlways
      1. It is hard to pay attention in class.
      2. I forget things.
      3. I have trouble keeping up with my schoolwork.
      4. I miss school because of not feeling well.
      5. I miss school to go to the doctor or hospital.

      H.2 PEDQOL cognitive functioning items.

      Table H.2PEDQOL cognitive functioning items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1…. fiel es mir leicht, neue Dinge zu lernen./ … I found it easy to learn new things.
      2…. fiel es mir schwer, mich zu konzentrieren./ … I had a hard time concentrating.
      3…. war ich genauso schlau wie alle anderen in der Klasse./ … I was just as smart as everyone else in the class.
      4…. konnte ich mir Sachen gut merken./ … I've been able to remember things well.
      5…. brauchte ich sehr lange, um meine Schularbeiten zu machen./ … it took me a long time to do my schoolwork.

      H.3 EORTC QLQ-C30 cognitive functioning items.

      Table H.3EORTC QLQ-C30 cognitive functioning items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Have you had difficulty concentrating on things, like reading a newspaper or watching television?
      2. Have you had difficulty remembering things?

      I. Social functioning items per questionnaire.

      I.1 PedsQL social functioning items.

      In the past ONE month, how much of a problem has this been for you …
      Table I.1PedsQL social functioning items.
      How I Get Along with Others (problems with …)NeverAlmost NeverSometimesOftenAlways
      1. I have trouble getting along with other kids.
      2. Other kids do not want to be my friend.
      3. Other kids tease me.
      4. I cannot do things other kids my age can do.
      5. It is hard to keep up when I play with other kids.

      I.2 PEDQOL social functioning items.

      Table I.2PEDQOL social functioning items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1… fühlte ich mich in Gruppen von Gleichaltrigen ausgeschlossen./ … I felt left out in groups of peers.
      2… habe ich lieber was alleine gemacht./ … I preferred to do something on my own.
      3… konnte ich mit meinen Freunden über das reden, was mir wirklich Sorgen macht./ … I was able to talk to my friends about what was really bothering me.
      Zum Schluss möchten wir Dich bitten, die folgenden allgemeinen Sätze zu beantworten:/Finally, we would like you to answer the following general sentences:
      4. Ich habe es leicht, Freunde zu finden./I have an easy time making friends.
      5. Ich bin beliebt bei meinen Freunden./I am popular with my friends.

      I.3 EORTC QLQ-C30 social functioning items.

      Table I.3EORTC QLQ-C30 social functioning items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Has your physical condition or medical treatment interfered with your family life?
      2. Has your physical condition or medical treatment interfered with your social activities?

      J. Fatigue items per questionnaire.

      J.1 PedsQL fatigue items.

      In the past ONE month, how much of a problem has this been for you …
      Table J.1PedsQL fatigue items.
      About My Health and Activities (problems with …)NeverAlmost NeverSometimesOftenAlways
      1. I have low energy.

      J.2 PEDQOL fatigue items.

      Table J.2PEDQOL fatigue items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1…. fühlte ich mich schlapp und müde./ … I have felt listless and tired.

      J.3 EORTC QLQ-C30 fatigue items.

      Table J.3EORTC QLQ-C30 fatigue items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Did you need to rest?
      2. Have you felt weak?
      3. Have you felt tired?

      K. Pain items per questionnaire.

      K.1 PedsQL pain items.

      In the past ONE month, how much of a problem has this been for you …
      Table K.1PedsQL pain items.
      About My Health and Activities (problems with …)NeverAlmost NeverSometimesOftenAlways
      1. I hurt or ache.

      K.2 PEDQOL pain items.

      Table K.2PEDQOL pain items.
      In der letzten Woche …/In the last week …Nie/NeverSelten/RarelyHäufig/FrequentlyImmer/Always
      1…. hatte ich Schmerzen./ … I've been in pain.

      K.3 EORTC QLQ-C30 pain items.

      Table K.3EORTC QLQ-C30 pain items.
      DURING THE PAST WEEK:Not at AllA LittleQuite a BitVery Much
      1. Have you had pain?
      2. Did pain interfere with your daily activities?

      L. Crosswalks between the PedsQL/the PEDQOL and the EORTC QLQ-C30.

      Table L.1Crosswalk for physical functioning.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      020 (5.45)7 (1.76)5073 (2.79)73 (3.11)
      120 (5.69)13 (2.79)5173 (2.72)80 (3.06)
      220 (5.62)13 (3.30)5273 (2.64)80 (3.01)
      320 (5.48)13 (3.60)5380 (2.57)80 (2.95)
      420 (5.30)13 (3.78)5480 (2.49)80 (2.90)
      520 (5.10)13 (3.89)5580 (2.41)80 (2.84)
      620 (4.89)13 (3.94)5687 (2.34)80 (2.78)
      720 (4.68)13 (3.95)5787 (2.26)80 (2.72)
      820 (4.47)20 (3.93)5887 (2.19)80 (2.66)
      927 (4.27)20 (3.89)5987 (2.12)80 (2.60)
      1030 (4.95)20 (3.66)6087 (2.05)80 (2.54)
      1130 (4.74)20 (3.60)6187 (1.98)80 (2.47)
      1233 (4.55)20 (3.53)6287 (1.91)80 (2.41)
      1333 (4.37)20 (3.47)6387 (1.85)80 (2.35)
      1433 (4.21)20 (3.41)6487 (1.78)80 (2.28)
      1533 (4.06)20 (3.36)6587 (1.72)80 (2.22)
      1633 (3.92)20 (3.31)6687 (1.65)80 (2.16)
      1733 (3.80)27 (3.27)6793 (1.59)87 (2.09)
      1833 (3.69)33 (3.25)6893 (1.53)93 (2.03)
      1933 (3.60)33 (3.22)6993 (1.46)93 (1.96)
      2040 (3.52)33 (3.21)7093 (1.40)93 (1.89)
      2140 (3.45)33 (3.20)7193 (1.34)93 (1.83)
      2244 (3.40)33 (3.20)7293 (1.28)93 (1.77)
      2347 (3.35)33 (3.20)7393 (1.22)93 (1.70)
      2447 (3.31)33 (3.20)7493 (1.16)93 (1.64)
      2547 (3.28)40 (3.21)75100 (1.11)93 (1.58)
      2647 (3.25)44 (3.22)76100 (1.05)96 (1.51)
      2747 (3.24)44 (3.23)77100 (1.00)96 (1.45)
      2853 (3.23)44 (3.25)78100 (0.95)96 (1.39)
      2953 (3.22)44 (3.26)79100 (0.90)96 (1.34)
      3053 (3.22)44 (3.28)80100 (0.85)96 (1.28)
      3153 (3.22)44 (3.29)81100 (0.80)96 (1.22)
      3256 (3.22)44 (3.30)82100 (0.76)96 (1.16)
      3356 (3.22)47 (3.32)83100 (0.71)100 (1.11)
      3460 (3.23)53 (3.33)84100 (0.67)100 (1.05)
      3560 (3.24)53 (3.34)85100 (0.63)100 (1.00)
      3660 (3.24)53 (3.35)86100 (0.59)100 (0.95)
      3760 (3.24)53 (3.36)87100 (0.55)100 (0.89)
      3860 (3.24)53 (3.36)88100 (0.51)100 (0.84)
      3964 (3.24)53 (3.36)89100 (0.47)100 (0.78)
      4064 (3.23)53 (3.36)90100 (0.43)100 (0.73)
      4170 (3.22)53 (3.35)91100 (0.40)100 (0.67)
      4273 (3.20)60 (3.35)92100 (0.36)100 (0.61)
      4373 (3.17)67 (3.33)93100 (0.32)100 (0.55)
      4473 (3.14)67 (3.31)94100 (0.28)100 (0.49)
      4573 (3.09)67 (3.29)95100 (0.24)100 (0.42)
      4673 (3.05)67 (3.26)96100 (0.20)100 (0.35)
      4773 (2.99)67 (3.23)97100 (0.16)100 (0.28)
      4873 (2.93)67 (3.19)98100 (0.12)100 (0.21)
      4973 (2.86)67 (3.15)99100 (0.07)100 (0.13)
      100100 (0.02)100 (0.04)
      Table L.2Crosswalk for emotional functioning.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      00 (4.04)0 (1.33)5058 (4.47)42 (2.82)
      10 (4.74)0 (1.94)5162 (4.62)42 (2.79)
      20 (5.16)0 (2.32)5262 (4.76)42 (2.77)
      30 (5.48)0 (2.61)5362 (4.86)42 (2.75)
      40 (5.75)0 (2.85)5462 (4.92)42 (2.73)
      50 (5.99)0 (3.07)5567 (4.92)42 (2.72)
      60 (6.21)0 (3.28)5667 (4.86)42 (2.71)
      70 (6.41)0 (3.47)5767 (4.74)42 (2.71)
      80 (6.59)0 (3.65)5867 (4.58)50 (2.71)
      90 (6.75)0 (3.82)5967 (4.38)58 (2.72)
      100 (6.90)0 (3.99)6075 (4.15)58 (2.72)
      110 (7.02)0 (4.16)6183 (3.91)58 (2.74)
      120 (7.13)0 (4.33)6283 (3.67)58 (2.76)
      130 (7.21)0 (4.49)6383 (3.43)58 (2.78)
      140 (7.26)0 (4.64)6483 (3.21)58 (2.80)
      1517 (7.29)0 (4.79)6583 (2.99)58 (2.82)
      1617 (7.28)0 (4.93)6683 (2.80)58 (2.84)
      1717 (7.24)0 (5.07)6783 (2.62)58 (2.86)
      1817 (7.17)16 (5.19)6883 (2.45)67 (2.87)
      1917 (7.06)16 (5.30)6983 (2.31)67 (2.87)
      2021 (6.93)16 (5.39)7083 (2.17)67 (2.86)
      2129 (6.76)16 (5.47)7192 (2.05)67 (2.83)
      2229 (6.56)16 (5.53)7292 (1.93)67 (2.79)
      2329 (6.34)16 (5.57)7392 (1.83)67 (2.73)
      2429 (6.10)16 (5.59)7492 (1.74)67 (2.66)
      2529 (5.84)17 (5.59)7592 (1.65)83 (2.58)
      2629 (5.58)17 (5.56)7692 (1.56)83 (2.48)
      2729 (5.31)17 (5.51)7792 (1.49)83 (2.38)
      2829 (5.05)17 (5.44)7892 (1.41)83 (2.28)
      2929 (4.80)17 (5.35)7992 (1.34)83 (2.17)
      3033 (4.56)17 (5.23)80100 (1.28)83 (2.06)
      3133 (4.35)17 (5.10)81100 (1.22)83 (1.96)
      3233 (4.15)17 (4.95)82100 (1.16)83 (1.85)
      3333 (3.98)17 (4.79)83100 (1.10)92 (1.75)
      3433 (3.84)21 (4.62)84100 (1.04)92 (1.65)
      3533 (3.72)21 (4.45)85100 (0.99)92 (1.56)
      3633 (3.63)21 (4.27)86100 (0.94)92 (1.47)
      3733 (3.55)21 (4.10)87100 (0.89)92 (1.37)
      3833 (3.51)21 (3.93)88100 (0.84)92 (1.28)
      3933 (3.48)21 (3.78)89100 (0.79)92 (1.19)
      4042 (3.47)21 (3.63)90100 (0.74)92 (1.10)
      4150 (3.49)21 (3.49)91100 (0.69)92 (1.01)
      4250 (3.52)33 (3.37)92100 (0.64)100 (0.92)
      4350 (3.57)33 (3.26)93100 (0.59)100 (0.82)
      4450 (3.65)33 (3.17)94100 (0.54)100 (0.73)
      4550 (3.74)33 (3.08)95100 (0.48)100 (0.63)
      4658 (3.86)33 (3.01)96100 (0.41)100 (0.52)
      4758 (3.99)33 (2.95)97100 (0.34)100 (0.42)
      4858 (4.14)33 (2.90)98100 (0.25)100 (0.30)
      4958 (4.30)33 (2.86)99100 (0.16)100 (0.18)
      100100 (0.06)100 (0.06)
      Table L.3Crosswalk for cognitive functioning.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      00 (10.88)0 (5.96)5083 (5.84)67 (5.60)
      10 (11.03)16 (6.55)5183 (5.40)67 (5.73)
      20 (11.02)16 (6.77)5283 (4.96)67 (5.83)
      30 (10.96)16 (6.87)5383 (4.54)67 (5.88)
      40 (10.87)16 (6.91)5483 (4.13)67 (5.88)
      50 (10.75)16 (6.90)5583 (3.76)67 (5.82)
      60 (10.60)16 (6.86)5683 (3.42)67 (5.70)
      70 (10.42)17 (6.80)5783 (3.11)67 (5.50)
      80 (10.22)17 (6.71)5883 (2.85)67 (5.25)
      90 (9.99)17 (6.61)5983 (2.61)67 (4.94)
      100 (9.75)17 (6.49)6083 (2.40)67 (4.60)
      110 (9.47)17 (6.37)6183 (2.22)83 (4.25)
      120 (9.18)17 (6.23)6283 (2.07)83 (3.88)
      130 (8.86)17 (6.09)6383 (1.93)83 (3.53)
      140 (8.54)17 (5.95)6483 (1.81)83 (3.19)
      150 (8.22)17 (5.80)6583 (1.71)83 (2.88)
      160 (7.89)17 (5.66)6683 (1.61)83 (2.60
      170 (7.54)17 (5.51)6783 (1.53)83 (2.34)
      180 (7.19)17 (5.37)6883 (1.45)83 (2.12)
      190 (6.85)17 (5.23)6983 (1.39)83 (1.92)
      200 (6.53)17 (5.09)7083 (1.32)83 (1.75)
      210 (6.23)25 (4.96)7183 (1.26)83 (1.59)
      220 (5.97)25 (4.84)7283 (1.21)83 (1.46)
      230 (5.72)25 (4.72)7383 (1.16)100 (1.34)
      240 (5.51)25 (4.62)7483 (1.11)100 (1.23)
      2542 (5.33)25 (4.52)75100 (1.07)100 (1.13)
      2650 (5.16)25 (4.44)76100 (1.03)100 (1.05)
      2750 (5.03)33 (4.36)77100 (0.99)100 (0.97)
      2850 (4.92)33 (4.30)78100 (0.95)100 (0.89)
      2950 (4.84)33 (4.24)79100 (0.91)100 (0.83)
      3050 (4.78)33 (4.20)80100 (0.87)100 (0.77)
      3150 (4.76)33 (4.17)81100 (0.84)100 (0.71)
      3250 (4.77)33 (4.15)82100 (0.80)100 (0.66)
      3350 (4.81)33 (4.14)783100 (0.77)100 (0.61)
      3450 (4.90)42 (4.14)84100 (0.73)100 (0.56)
      3550 (5.03)42 (4.15)85100 (0.70)100 (0.52)
      3650 (5.20)42 (4.17)86100 (0.67)100 (0.48)
      3750 (5.42)42 (4.20)87100 (0.64)100 (0.44)
      3867 (5.68)42 (4.24)88100 (0.60)100 (0.40)
      3967 (5.96)42 (4.30)89100 (0.57)100 (0.37)
      4067 (6.26)50 (4.36)90100 (0.54)100 (0.34)
      4167 (6.56)50 (4.44)91100 (0.50)100 (0.31)
      4267 (6.82)50 (4.53)92100 (0.47)100 (0.28)
      4367 (7.03)50 (4.63)93100 (0.44)100 (0.24)
      4467 (7.15)50 (4.74)94100 (0.40)100 (0.21)
      4567 (7.17)50 (4.87)95100 (0.35)100 (0.18)
      4667 (7.08)50 (5.00)96100 (0.30)100 (0.15)
      4767 (6.88)67 (5.15)97100 (0.25)100 (0.12)
      4867 (6.60)67 (5.30)98100 (0.19)100 (0.09)
      4967 (6.24)67 (5.46)99100 (0.12)100 (0.06)
      100100 (0.05)100 (0.02)
      Table L.4Crosswalk for social functioning.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      00 (0.1)0 (8e-04)500 (4.5)0 (1e+00)
      10 (0.2)0 (2e-03)510 (4.6)0 (1e+00)
      20 (0.2)0 (3e-03)520 (4.7)0 (2e+00)
      30 (0.3)0 (4e-03)530 (4.7)0 (2e+00)
      40 (0.3)0 (4e-03)540 (4.7)0 (2e+00)
      50 (0.3)0 (5e-03)5517 (4.7)0 (2e+00)
      60 (0.3)0 (5e-03)5617 (4.7)0 (2e+00)
      70 (0.3)0 (6e-03)5717 (4.6)0 (3e+00)
      80 (0.3)0 (6e-03)5817 (4.6)0 (3e+00)
      90 (0.4)0 (6e-03)5917 (4.5)0 (3e+00)
      100 (0.4)0 (7e-03)6033 (4.5)0 (3e+00)
      110 (0.4)0 (7e-03)6133 (4.5)0 (3e+00)
      120 (0.4)0 (7e-03)6233 (4.5)0 (3e+00)
      130 (0.4)0 (8e-03)6333 (4.5)0 (4e+00)
      140 (0.4)0 (8e-03)6433 (4.6)0 (4e+00)
      150 (0.4)0 (9e-03)6533 (4.7)0 (4e+00)
      160 (0.4)0 (9e-03)6633 (4.8)0 (4e+00)
      170 (0.4)0 (1e-02)6733 (4.9)17 (4e+00)
      180 (0.4)0 (1e-02)6833 (5.1)17 (5e+00)
      190 (0.5)0 (1e-02)6933 (5.4)17 (5e+00)
      200 (0.5)0 (1e-02)7050 (5.7)17 (5e+00)
      210 (0.5)0 (1e-02)7150 (6.0)17 (5e+00)
      220 (0.5)0 (1e-02)7250 (6.3)17 (5e+00)
      230 (0.5)0 (2e-02)7350 (6.7)33 (6e+00)
      240 (0.6)0 (2e-02)7450 (7.1)50 (6e+00)
      250 (0.6)0 (2e-02)7550 (7.4)50 (6e+00)
      260 (0.7)0 (2e-02)7667 (7.7)50 (6e+00)
      270 (0.7)0 (3e-02)7767 (7.8)50 (7e+00)
      280 (0.8)0 (3e-02)7867 (7.8)50 (7e+00)
      290 (0.8)0 (4e-02)7967 (7.6)50 (7e+00)
      300 (0.9)0 (4e-02)8067 (7.3)50 (7e+00)
      310 (1.0)0 (5e-02)8175 (6.9)67 (7e+00)
      320 (1.1)0 (6e-02)8275 (6.3)67 (8e+00)
      330 (1.2)0 (8e-02)8375 (5.7)67 (8e+00)
      340 (1.3)0 (9e-02)8475 (5.0)67 (8e+00)
      350 (1.5)0 (1e-01)8583 (4.4)67 (8e+00)
      360 (1.6)0 (1e-01)86100 (3.8)67 (8e+00)
      370 (1.8)0 (2e-01)87100 (3.3)67 (8e+00)
      380 (2.0)0 (2e-01)88100 (2.8)83 (7e+00)
      390 (2.2)0 (2e-01)89100 (2.5)83 (7e+00)
      400 (2.4)0 (3e-01)90100 (2.1)83 (7e+00)
      410 (2.6)0 (3e-01)91100 (1.8)83 (6e+00)
      420 (2.9)0 (4e-01)92100 (1.6)83 (6e+00)
      430 (3.1)0 (5e-01)93100 (1.4)83 (5e+00)
      440 (3.4)0 (6e-01)94100 (1.2)83 (4e+00)
      450 (3.6)0 (7e-01)95100 (1.0)83 (4e+00)
      460 (3.8)0 (8e-01)96100 (0.8)83 (3e+00)
      470 (4.1)0 (9e-01)97100 (0.6)83 (3e+00)
      480 (4.2)0 (1e+00)98100 (0.5)83 (2e+00)
      490 (4.4)0 (1e+00)99100 (0.3)83 (1e+00)
      100100 (0.1)100 (4e-01)
      Table L.5Crosswalk for fatigue.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      00 (0.2)11 (0.7)5033 (4.0)56 (2.7)
      110 (0.4)22 (1.4)5156 (4.1)56 (2.7)
      210 (0.7)22 (1.8)5256 (4.1)56 (2.8)
      310 (0.9)22 (2.0)5356 (4.1)56 (2.8)
      410 (1.1)22 (2.1)5456 (4.1)56 (2.8)
      510 (1.2)22 (2.2)5556 (4.1)56 (2.9)
      610 (1.3)22 (2.2)5656 (4.1)56 (2.9)
      710 (1.5)22 (2.2)5756 (4.1)56 (2.9)
      810 (1.6)22 (2.2)5856 (4.1)56 (3.0)
      910 (1.7)22 (2.2)5956 (4.1)56 (3.0)
      1010 (1.8)22 (2.3)6056 (4.1)56 (3.0)
      1110 (1.9)22 (2.3)6156 (4.0)56 (3.1)
      1210 (1.9)22 (2.3)6256 (4.0)56 (3.1)
      1310 (2.0)22 (2.3)6356 (4.0)56 (3.1)
      1410 (2.1)22 (2.3)6456 (4.0)56 (3.1)
      1510 (2.2)22 (2.3)6556 (4.0)56 (3.2)
      1610 (2.2)22 (2.3)6656 (3.9)56 (3.2)
      1710 (2.3)22 (2.3)6756 (3.9)67 (3.2)
      1810 (2.4)22 (2.3)6856 (3.9)94 (3.2)
      1910 (2.4)22 (2.3)6956 (3.9)94 (3.2)
      2010 (2.5)22 (2.3)7056 (3.9)94 (3.2)
      2110 (2.6)22 (2.3)7156 (3.8)94 (3.2)
      2210 (2.6)22 (2.3)7256 (3.8)94 (3.2)
      2310 (2.7)22 (2.4)7356 (3.8)94 (3.2)
      2410 (2.8)22 (2.4)7456 (3.8)94 (3.2)
      2511 (2.8)22 (2.4)7567 (3.8)94 (3.1)
      2622 (2.9)22 (2.4)7678 (3.8)94 (3.1)
      2722 (3.0)22 (2.4)7778 (3.8)94 (3.1)
      2822 (3.1)22 (2.4)7878 (3.9)94 (3.1)
      2922 (3.1)22 (2.4)7978 (3.9)94 (3.0)
      3022 (3.2)22 (2.4)8078 (3.9)94 (3.0)
      3122 (3.3)22 (2.4)8178 (4.0)94 (2.9)
      3222 (3.3)22 (2.4)8278 (4.0)94 (2.8)
      3322 (3.4)33 (2.5)8378 (4.1)94 (2.8)
      3422 (3.4)56 (2.5)8478 (4.2)94 (2.7)
      3522 (3.5)56 (2.5)8578 (4.3)94 (2.6)
      3622 (3.6)56 (2.5)8678 (4.3)94 (2.4)
      3722 (3.6)56 (2.5)8778 (4.4)94 (2.3)
      3822 (3.7)56 (2.5)8878 (4.5)94 (2.2)
      3922 (3.7)56 (2.5)8978 (4.6)94 (2.0)
      4022 (3.8)56 (2.5)9078 (4.6)94 (1.9)
      4122 (3.8)56 (2.5)9178 (4.7)94 (1.7)
      4222 (3.8)56 (2.5)9278 (4.7)94 (1.5)
      4322 (3.9)56 (2.5)9378 (4.6)94 (1.4)
      4422 (3.9)56 (2.5)9478 (4.6)94 (1.2)
      4522 (3.9)56 (2.6)9578 (4.5)94 (1.0)
      4622 (4.0)56 (2.6)9678 (4.3)94 (0.8)
      4722 (4.0)56 (2.6)9778 (4.1)94 (0.7)
      4822 (4.0)56 (2.6)9878 (3.7)94 (0.5)
      4922 (4.0)56 (2.7)9978 (3.1)94 (0.3)
      10089 (2.1)100 (0.1)
      Table L.6Crosswalk for pain.
      Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)Original PedsQL score/PEDQOL scoreEstimated EORTC QLQ-C30-equivalent score by linked questionnaire (Bootstrap SE)
      PedsQLPEDQOLPedsQLPEDQOL
      00 (0.09)0 (0.07)5033 (5.90)50 (5.84)
      10 (0.24)0 (0.20)5167 (6.06)50 (5.94)
      20 (0.39)0 (0.32)5267 (6.21)50 (6.01)
      30 (0.52)0 (0.42)5367 (6.34)50 (6.04)
      40 (0.64)0 (0.52)5467 (6.46)50 (6.04)
      50 (0.74)0 (0.60)5567 (6.57)50 (5.99)
      60 (0.84)0 (0.68)5667 (6.65)50 (5.92)
      70 (0.93)0 (0.76)5767 (6.72)50 (5.81)
      80 (1.02)0 (0.83)5867 (6.76)50 (5.68)
      90 (1.10)0 (0.89)5967 (6.78)50 (5.53)
      100 (1.17)0 (0.96)6067 (6.78)50 (5.37)
      110 (1.25)0 (1.02)6167 (6.76)50 (5.20)
      120 (1.32)0 (1.08)6267 (6.72)50 (5.02)
      130 (1.39)0 (1.14)6367 (6.67)50 (4.86)
      140 (1.46)0 (1.21)6467 (6.60)50 (4.69)
      150 (1.53)0 (1.27)6567 (6.52)50 (4.53)
      160 (1.61)0 (1.34)6667 (6.44)50 (4.39)
      170 (1.68)0 (1.40)6767 (6.35)67 (4.25)
      180 (1.75)0 (1.47)6867 (6.26)100 (4.12)
      190 (1.83)0 (1.54)6967 (6.16)100 (4.00)
      200 (1.91)0 (1.62)7067 (6.07)100 (3.89)
      210 (1.99)0 (1.70)7167 (5.98)100 (3.80)
      220 (2.07)0 (1.77)7267 (5.89)100 (3.72)
      230 (2.16)0 (1.86)7367 (5.81)100 (3.65)
      240 (2.25)0 (1.94)7467 (5.74)100 (3.59)
      2517 (2.34)0 (2.03)7567 (5.66)100 (3.53)
      2617 (2.44)0 (2.13)7692 (5.59)100 (3.49)
      2717 (2.54)0 (2.22)7792 (5.52)100 (3.45)
      2817 (2.64)0 (2.33)7892 (5.46)100 (3.41)
      2917 (2.75)0 (2.43)7992 (5.39)100 (3.37)
      3017 (2.86)0 (2.54)8092 (5.32)100 (3.33)
      3117 (2.98)0 (2.66)8192 (5.24)100 (3.28)
      3217 (3.10)0 (2.78)8292 (5.16)100 (3.23)
      3317 (3.22)17 (2.91)8392 (5.07)100 (3.16)
      3417 (3.35)50 (3.05)8492 (4.97)100 (3.08)
      3517 (3.49)50 (3.19)8592 (4.87)100 (3.00)
      3617 (3.63)50 (3.34)8692 (4.75)100 (2.89)
      3717 (3.77)50 (3.50)8792 (4.61)100 (2.78)
      3817 (3.92)50 (3.67)8892 (4.47)100 (2.65)
      3917 (4.07)50 (3.84)8992 (4.30)100 (2.51)
      4017 (4.22)50 (4.02)9092 (4.12)100 (2.36)
      4117 (4.38)50 (4.21)9192 (3.93)100 (2.19)
      4217 (4.55)50 (4.40)9292 (3.71)100 (2.01)
      4317 (4.71)50 (4.60)9392 (3.47)100 (1.83)
      4417 (4.88)50 (4.80)9492 (3.21)100 (1.63)
      4517 (5.05)50 (5.00)9592 (2.92)100 (1.42)
      4617 (5.22)50 (5.20)9692 (2.61)100 (1.21)
      4717 (5.40)50 (5.38)9792 (2.25)100 (0.98)
      4817 (5.57)50 (5.56)9892 (1.83)100 (0.74)
      4917 (5.74)50 (5.71)9992 (1.34)100 (0.48)
      100100 (0.66)100 (0.18)
      2Score differences are defined as the paediatric instrument as less than the adult instrument.
      3The US-English versions of are displayed here in an exemplary fashion.

      References

        • Dorans Neil J.
        • Holland Paul W.
        Population invariance and the equatability of tests: basic theory and the linear case.
        J Educ Meas. 2000; 37 (ISSN 1745–3984): 281-306https://doi.org/10.1111/j.1745-3984.2000.tb01088.x
        • Neil J.
        Dorans. Linking scores from multiple health outcome instruments.
        Qual Life Res : Int J Qual Life Asp Treat Care Rehabil. 2007; 16 (ISSN 0962–9343): 85-94https://doi.org/10.1007/s11136-006-9155-3
        • Marrie Ruth Ann
        • Dufault Brenden
        • Tyry Tuula
        • Cutter Gary R.
        • Fox Robert J.
        • Salter Amber
        Developing a crosswalk between the rand-12 and the health utilities index for multiple sclerosis.
        Mult Scler. 2020; 26: 1102-1110https://doi.org/10.1177/1352458519852722
        • Shaw Bronwen E.
        • Syrjala Karen L.
        • Onstad Lynn E.
        • Chow Eric J.
        • Flowers Mary E.
        • Jim Heather
        • Scott Baker K.
        • Buckley Sarah
        • Fairclough Diane L.
        • Horowitz Mary M.
        • Lee Stephanie J.
        Promis measures can be used to assess symptoms and function in long-term hematopoietic cell transplantation survivors.
        Cancer. 2018; 124 (ISSN 0008–543X): 841-849https://doi.org/10.1002/cncr.31089
        • Kaat Aaron J.
        • Schalet Benjamin D.
        • Rutsohn Joshua
        • Jensen Roxanne E.
        • Cella David
        Physical function metric over measure: an illustration with the patient-reported outcomes measurement information system (promis) and the functional assessment of cancer therapy (fact).
        Cancer. 2018; 124 (ISSN 0008–543X): 153-160https://doi.org/10.1002/cncr.30981
        • McHorney C.A.
        • Cohen A.S.
        Equating health status measures with item response theory: illustrations with functional status items.
        Med Care. 2000; 38 (ISSN 257079): II43-59https://doi.org/10.1097/00005650-200009002-00008
        • Schalet Benjamin D.
        • Rothrock Nan E.
        • Hays Ron D.
        • Kazis Lewis E.
        • Cook Karon F.
        • Rutsohn Joshua P.
        • Cella David
        Linking physical and mental health summary scores from the veterans rand 12-item health survey (vr-12) to the promis Ⓡ global health scale.
        J Gen Intern Med. 2015; 30 (ISSN 1525–1497): 1524-1530https://doi.org/10.1007/s11606-015-3453-9
        • Haley Stephen M.
        • Ni Pengsheng
        • Lai Jin-shei
        • Tian Feng
        • Coster Wendy J.
        • Jette Alan M.
        • Straub Donald
        • Cella David
        Linking the activity measure for post-acute care and the quality of life outcomes in neurological disorders.
        Arch Phys Med Rehabil. 2011; 92 (ISSN 0003–9993): S37-S43https://doi.org/10.1016/j.apmr.2011.01.026
        • Schalet Benjamin D.
        • Revicki Dennis A.
        • Cook Karon F.
        • Krishnan Eswar
        • Fries Jim F.
        • Cella David
        Establishing a common metric for physical function: linking the haq-di and sf-36 pf subscale to promis® physical function.
        J Gen Intern Med. 2015; 30 (ISSN 1525–1497): 1517-1523https://doi.org/10.1007/s11606-015-3360-0
        • Mâsse Louise C.
        • Allen Diane
        • Wilson Mark
        • Williams Geoffrey
        Introducing equating methodologies to compare test scores from two different self-regulation scales.
        Health Educ Res. 2006; 21 (ISSN 0268–1153): i110-i120https://doi.org/10.1093/her/cyl088
        • Kaat Aaron J.
        • Newcomb Michael E.
        • Ryan Daniel T.
        • Mustanski Brian
        Expanding a common metric for depression reporting: linking two scales to promis® depression.
        Qual Life Res : Int J Qual Life Asp Treat Care Rehabil. 2017; 26 (ISSN 0962–9343): 1119-1128https://doi.org/10.1007/s11136-016-1450-z
        • Choi Seung W.
        • Schalet Benjamin
        • Cook Karon F.
        • Cella David
        Establishing a common metric for depressive symptoms: linking the bdi-ii, ces-d, and phq-9 to promis depression.
        Psychol Assess. 2014; 26 (ISSN 1040–3590): 513-527https://doi.org/10.1037/a0035768
        • Tulsky David S.
        • Kisala Pamela A.
        • Kalpakjian Claire Z.
        • Bombardier Charles H.
        • Pohlig Ryan T.
        • Heinemann Allen W.
        • Adam Carle
        • Choi Seung W.
        Measuring depression after spinal cord injury: development and psychometric characteristics of the sci-qol depression item bank and linkage with phq-9.
        J Spinal Cord Med. 2015; 38 (ISSN 1079–0268): 335-346https://doi.org/10.1179/2045772315Y.0000000020
        • Olino Thomas M.
        • Lan Yu
        • McMakin Dana L.
        • Forbes Erika E.
        • Seeley John R.
        • Lewinsohn Peter M.
        • Pilkonis Paul A.
        Comparisons across depression assessment instruments in adolescence and young adulthood: an item response theory study using two linking methods.
        J Abnorm Child Psychol. 2013; 41 (ISSN 1573–2835): 1267-1277https://doi.org/10.1007/s10802-013-9756-6
        • Orlando M.
        • Sherbourne C.D.
        • Thissen D.
        Summed-score linking using item response theory: application to depression measurement.
        Psychol Assess. 2000; 12 (ISSN 1040–3590): 354-359https://doi.org/10.1037//1040-3590.12.3.354
        • Cook Karon F.
        • Schalet Benjamin D.
        • Kallen Michael A.
        • Rutsohn Joshua P.
        • Cella David
        Establishing a common metric for self-reported pain: linking bpi pain interference and sf-36 bodily pain subscale scores to the promis pain interference metric.
        Qual Life Res. 2015; 24 (ISSN 1573–2649): 2305-2318https://doi.org/10.1007/s11136-015-0987-6
        • Askew Robert L.
        • Kim Jiseon
        • Chung Hyewon
        • Cook Karon F.
        • Johnson Kurt L.
        • Amtmann Dagmar
        Development of a crosswalk for pain interference measured by the bpi and promis pain interference short form.
        Qual Life Res. 2013; 22 (ISSN 1573–2649): 2769-2776https://doi.org/10.1007/s11136-013-0398-5
        • Kisala Pamela A.
        • Tulsky David S.
        • Kalpakjian Claire Z.
        • Heinemann Allen W.
        • Pohlig Ryan T.
        • Adam Carle
        • Choi Seung W.
        Measuring anxiety after spinal cord injury: development and psychometric characteristics of the sci-qol anxiety item bank and linkage with gad-7.
        J Spinal Cord Med. 2015; 38 (ISSN 1079–0268): 315-325https://doi.org/10.1179/2045772315Y.0000000029
        • Schalet Benjamin D.
        • Cook Karon F.
        • Choi Seung W.
        • Cella David
        Establishing a common metric for self-reported anxiety: linking the masq, panas, and gad-7 to promis anxiety.
        J Anxiety Disord. 2014; 28 (ISSN 0887–6185): 88-96https://doi.org/10.1016/j.janxdis.2013.11.006
        • Lai Jin-shei
        • Cella David
        • Yanez Betina
        • Stone Arthur
        Linking fatigue measures on a common reporting metric.
        J Pain Symptom Manag. 2014; 48 (ISSN 0885–3924): 639-648https://doi.org/10.1016/j.jpainsymman.2013.12.236
        • Noonan Vanessa K.
        • Cook Karon F.
        • Bamer Alyssa M.
        • Choi Seung W.
        • Kim Jiseon
        • Amtmann Dagmar
        Measuring fatigue in persons with multiple sclerosis: creating a crosswalk between the modified fatigue impact scale and the promis fatigue short form.
        Qual Life Res. 2012; 21 (ISSN 1573–2649): 1123-1133https://doi.org/10.1007/s11136-011-0040-3
        • Holzner B.
        • Bode R.K.
        • Hahn E.A.
        • Cella D.
        • Kopp M.
        • Sperner-Unterweger B.
        • Kemmler G.
        Equating eortc qlq-c30 and fact-g scores and its use in oncological research.
        Eur J Cancer (Oxford, England : 1990). 2006; 42 (ISSN 0959–8049): 3169-3177https://doi.org/10.1016/j.ejca.2006.08.016
        • Reeve Bryce B.
        • Thissen David
        • DeWalt Darren A.
        • Huang I-Chan
        • Liu Yang
        • Magnus Brooke
        • et al.
        Linkage between the promis(r) pediatric and adult emotional distress measures.
        Qual Life Res : Int J Qual Life Asp Treat Care Rehabil. 2016; 25 (ISSN 0962–9343): 823-833https://doi.org/10.1007/s11136-015-1143-z
        • Tian Feng
        • Ni Pengsheng
        • Mulcahey M.J.
        • Hambleton Ronald K.
        • Tulsky David
        • Haley Stephen M.
        • Jette Alan M.
        Tracking functional status across the spinal cord injury lifespan: linking pediatric and adult patient-reported outcome scores.
        Arch Phys Med Rehabil. 2014; 95 (e15,ISSN 0003–9993): 2078-2085https://doi.org/10.1016/j.apmr.2014.05.023
        • Marina N.
        • Bielack S.
        • Whelan J.
        • Smeland S.
        • Krailo M.
        • Sydes M.R.
        • Butterfass-Bahloul T.
        • Calaminus G.
        • Bernstein M.
        International collaboration is feasible in trials for rare conditions: the euramos experience.
        Cancer Treat Res. 2009; 152 (ISSN 0927–3042): 339-353https://doi.org/10.1007/978-1-4419-0284-9_18
        • Whelan J.S.
        • Bielack S.S.
        • Marina N.
        • Smeland S.
        • Jovic G.
        • Hook J.M.
        • et al.
        Euramos-1, an international randomised study for osteosarcoma: results from pre-randomisation treatment.
        Ann Oncol. 2015; 26 (ISSN 0923–7534): 407-414https://doi.org/10.1093/annonc/mdu526
        • Calaminus Gabriele
        • Jenney Meriel
        • Hjorth Lars
        • Baust Katja
        • Bernstein Mark
        • Bielack Stefan
        • De Vos Patricia
        • Pancras C.
        • Hogendoorn W.
        • Jovic Gordana
        • Krailo Mark
        • Kreitz Kiana
        • Marina Neyssa
        • Popoola Babasola O.
        • Sauerland Cristina
        • Smeland Sigbjørn
        • Teske Carmen
        • Schweinitz Clara V.
        • Whelan Jeremy
        • Wiener Andreas
        • Sydes Matthew R.
        • Nagarajan Rajaram
        Quality of life of patients with osteosarcoma in the european american osteosarcoma study-1 (euramos-1): development and implementation of a questionnaire substudy.
        JMIR research protocols. 2019; 8 (ISSN 1929–0748)e14406https://doi.org/10.2196/14406
        • Varni James W.
        • Seid Michael
        • Rode Cheryl A.
        The pedsql™: measurement model for the pediatric quality of life inventory.
        Med Care. 1999; 37 (ISSN 00257079): 126-139
        • Calaminus G.
        • Weinspach S.
        • Teske C.
        • Göbel U.
        Quality of life in children and adolescents with cancer. first results of an evaluation of 49 patients with the pedqol questionnaire.
        Klin Pädiatr. 2000; 212 (ISSN 0300–8630): 211-215https://doi.org/10.1055/s-2000-9679
        • Aaronson N.K.
        • Ahmedzai S.
        • Bergman B.
        • Bullinger M.
        • Cull A.
        • Duez N.J.
        • Filiberti A.
        • Flechtner H.
        • Fleishman S.B.
        • de Haes J.C.
        The european organization for research and treatment of cancer qlq-c30: a quality-of-life instrument for use in international clinical trials in oncology.
        J Natl Cancer Inst. 1993; 85 (ISSN 0027–8874): 365-376https://doi.org/10.1093/jnci/85.5.365
        • von Davier A.
        Statistical Models for test equating, scaling, and linking.
        Springer, New York2010 (9780387981383)
        • Lord Frederic M.
        Notes on comparable scales for test scores.
        ETS Res Bull Ser. 1950; (i–21, 1950. ISSN 2333–8504)https://doi.org/10.1002/j.2333-8504.1950.tb00673.x
        • Kolen Michael J.
        • Brennan Robert L.
        Test equating, scaling, and linking: Methods and practices. Statistics for Social and Behavioral Sciences.
        3rd ed. Springer, New York2014 (ISBN 1493903160)
        • equate Anthony D. Albano
        An r package for observed-score linking and equating.
        J Stat Software. 2016; 74: 1-36https://doi.org/10.18637/jss.v074.i08
        • Bland J.M.
        • Altman D.G.
        Statistical methods for assessing agreement between two methods of clinical measurement.
        Lancet (London, England). 1986; 1 (ISSN 0140–6736): 307-310
        • Zhou Xiaoyan
        • Dibley Michael J.
        • Cheng Yue
        • Ouyang Xue
        • Yan Hong
        Validity of self-reported weight, height and resultant body mass index in Chinese adolescents and factors associated with errors in self-reports.
        BMC Publ Health. 2010; 10 (ISSN 1471–2458): 190https://doi.org/10.1186/1471-2458-10-190
        • Euser Anne M.
        • Dekker Friedo W.
        • Le Cessie Saskia
        A practical approach to Bland-Altman plots and variation coefficients for log transformed variables.
        J Clin Epidemiol. 2008; 61 (ISSN 0895–4356): 978-982https://doi.org/10.1016/j.jclinepi.2007.11.003
        • Brehm Merel-Anne
        • Scholtes Vanessa A.
        • Dallmeijer Annet J.
        • Twisk Jos W.
        • Harlaar Jaap
        The importance of addressing heteroscedasticity in the reliability analysis of ratio-scaled variables: an example based on walking energy-cost measurements.
        Dev Med Child Neurol. 2012; 54 (ISSN 1469–8749): 267-273https://doi.org/10.1111/j.1469-8749.2011.04164.x
        • Lin L.I.
        A concordance correlation coefficient to evaluate reproducibility.
        Biometrics. 1989; 45 (ISSN 0006–341X): 255-268
        • Neil J.
        Dorans. Equating, concordance, and expectation.
        Appl Psychol Meas. 2004; 28: 227-246https://doi.org/10.1177/0146621604265031

      Linked Article