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Sex-differences in symptoms and functioning in >5000 cancer survivors: Results from the PROFILES registry

  • Sabine Oertelt-Prigione
    Correspondence
    Corresponding author: Gender Unit, Department of Primary and Community Care, Radboud Institute for Health Sciences (RIHS), Radboud University Medical Center, Geert Grooteplein 21, Nijmegen, 6500HB, the Netherlands.
    Affiliations
    Gender Unit, Department of Primary and Community Care, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands

    Institute of Legal and Forensic Medicine, Charité – Universitätsmedizin, Berlin, Germany
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  • Belle H. de Rooij
    Affiliations
    Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, the Netherlands

    CoRPS - Center of Research on Psychological and Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
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  • Floortje Mols
    Affiliations
    CoRPS - Center of Research on Psychological and Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
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  • Simone Oerlemans
    Affiliations
    Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, the Netherlands
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  • Olga Husson
    Affiliations
    Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands

    Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands

    Division of Clinical Studies, Institute of Cancer Research, London, United Kingdom
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  • Dounya Schoormans
    Affiliations
    CoRPS - Center of Research on Psychological and Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
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  • John B. Haanen
    Affiliations
    Division of Molecular Oncology and Immunology, Netherlands Cancer Institute, Amsterdam, the Netherlands
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  • Lonneke V. van de Poll-Franse
    Correspondence
    Corresponding author: Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, the Netherlands.
    Affiliations
    Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, the Netherlands

    CoRPS - Center of Research on Psychological and Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands

    Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
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Open AccessPublished:August 16, 2021DOI:https://doi.org/10.1016/j.ejca.2021.07.019

      Highlights

      • Long-term cancer survivors report sex-specific symptoms and functional impairments.
      • Comparison with age-and sex-matched reference group showed more impairment in males.
      • Loss of role and social functioning in males could represent a loss of gender role.

      Abstract

      Background

      Previous reports highlight the greater number of side effects that women experience during cancer treatment, but little is known about sex differences in symptoms and functioning in long-term survivors.

      Methods

      We investigated sex differences in the prevalence of physical (EORTC QLQ-C30) and emotional symptoms (Hospital Anxiety and Depression Scale) and loss of functioning (EORTC QLQ-C30) in 5339 cancer survivors (55% males). General linear models were computed to assess the differences in symptoms and functioning between female and male cancer survivors and between survivors and an age-matched reference population.

      Results

      The direct comparison between female and male cancer survivors identified more symptoms, such as nausea and vomiting (M = 5.0 versus. 3.2), insomnia (M = 26.1 versus. 15.9), anxiety (M = 5.2 versus. 4.2), and lower physical (M = 77.5 versus. 82.5) and emotional functioning (M = 83.4 versus. 86.3), in female survivors. However, comparison with an age-matched reference population demonstrated that several symptoms, such as fatigue, dyspnea, anxiety and depression, appeared to be more frequent in male patients. The investigation of functioning domains — compared with a reference population — highlighted further sex-specific differences. Female survivors experienced a moderate net loss in physical and cognitive functioning (−6.1 [95% CI = −8.1; −4,1] and −5.2 respectively [95% CI = −7; −3.5]), whereas male survivors displayed a significant net loss in role and social functioning compared to the reference population (−9.9 [95% CI = −11.2; −8.6] and −7.7 [95% CI = −9.6; −7.6] respectively).

      Conclusion

      To adequately capture sex differences in symptoms and functioning in long-term cancer survivors, a comparison with a reference population should always be considered. In our study population, this adjustment highlighted a significant and unexpected long-term impact on male patients. Role and social functioning were especially impacted in male patients, emphasizing the need to further investigate these gendered domains.

      Keywords

      1. Introduction

      Almost all, not sex-specific, cancers affect men more than women, with the well-documented exception of thyroid cancer [
      • Bray F.
      • Ferlay J.
      • Soerjomataram I.
      • et al.
      Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
      ]. Research points to the role of genetic differences in autosomes and sex chromosomes, the influence of circulating hormones and their receptors [
      • Clocchiatti A.
      • Cora E.
      • Zhang Y.
      • et al.
      Sexual dimorphism in cancer.
      ], as well as differences in the immune function and in exposure to risk factors [
      • Klein S.L.
      • Flanagan K.L.
      Sex differences in immune responses.
      ]. Sex differences also affect pharmacotherapy exposing female subjects to 1.5 times the risk of serious side effects compared to males [
      • Parekh A.
      • Fadiran E.O.
      • Uhl K.
      • et al.
      Adverse effects in women: implications for drug development and regulatory policies.
      ]. Gastrointestinal symptoms are more common in females; dermatological symptoms appear to be more common in males [
      • Tran C.
      • Knowles S.R.
      • Liu B.A.
      • et al.
      Gender differences in adverse drug reactions.
      ]. Severe side effects up to premature death were also reported more frequent in females in a landmark study in the United States [
      • Obias-Manno D.
      • Scott P.E.
      • Kaczmarczyk J.
      • et al.
      The food and drug administration office of women's health: impact of science on regulatory policy.
      ].
      In addition to biological sex, gender might also impact the health of patients with cancer [
      • Wagner A.D.
      • Oertelt-Prigione S.
      • Adjei A.
      • et al.
      Gender medicine and oncology: report and consensus of an ESMO workshop.
      ]. Gender is a multilayered construct that takes different dimensions into account: e.g. gender identities, norms and relationships [
      • Tannenbaum C.
      • Greaves L.
      • Graham I.D.
      Why sex and gender matter in implementation research.
      ]. Gender identity defines how an individual identifies, e.g. as a woman or a non-binary person; gender norms represent the expectations placed on individuals by their environment, e.g. the expectations that women should be more caring and men more assertive; and gender relationships represent the consequences of power imbalances in human interaction, e.g. the ability to negotiate time allocation within a partnership [
      • Tannenbaum C.
      • Greaves L.
      • Graham I.D.
      Why sex and gender matter in implementation research.
      ]. Gender can impact health independently of sex [
      • Pelletier R.
      • Khan N.A.
      • Cox J.
      • et al.
      Sex versus gender-related characteristics: which predicts outcome after acute coronary syndrome in the young?.
      ] and is seldom taken into account in medical research.
      Cancer therapy has evolved in the past decades, improving the prognosis for patients [
      • Ribas A.
      • Wolchok J.D.
      Cancer immunotherapy using checkpoint blockade.
      ,
      • Biankin A.V.
      • Piantadosi S.
      • Hollingsworth S.J.
      Patient-centric trials for therapeutic development in precision oncology.
      ]. Many survivors are classified as ‘disease free’ from a medical standpoint; however, the quality of their lives is still significantly impaired even in the absence of persistent malignancy. This can be due to physical and psychological symptoms, as well as social aspects and financial difficulties [
      • van de Poll-Franse L.V.
      • Horevoorts N.
      • van Eenbergen M.
      • et al.
      The Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship registry: scope, rationale and design of an infrastructure for the study of physical and psychosocial outcomes in cancer survivorship cohorts.
      ]. Impaired Health-related Quality of Life (HRQoL) has been correlated with female sex and feminine gender. These findings are recapitulated in people living with cancer [
      • Schmidt C.E.
      • Bestmann B.
      • Kuchler T.
      • et al.
      Gender differences in quality of life of patients with rectal cancer. A five-year prospective study.
      ,
      • Miaskowski C.
      Gender differences in pain, fatigue, and depression in patients with cancer.
      ,
      • de Graeff A.
      • de Leeuw J.R.
      • Ros W.J.
      • et al.
      Long-term quality of life of patients with head and neck cancer.
      ] and in their caregivers [
      • Hagedoorn M.
      • Buunk B.P.
      • Kuijer R.G.
      • et al.
      Couples dealing with cancer: role and gender differences regarding psychological distress and quality of life.
      ]; however, the available knowledge is limited. Importantly, most studies do not detail if biological sex or gender identity was considered. Although more common in female patients, reduced HRQoL is occasionally also reported in male patients, e.g. in stroke, lupus erythematosus, lumbar degenerative disease [
      • Phan H.T.
      • Blizzard C.L.
      • Reeves M.J.
      • et al.
      Sex differences in long-term quality of life among survivors after stroke in the INSTRUCT.
      ,
      • Jolly M.
      • Sequeira W.
      • Block J.A.
      • et al.
      Sex differences in quality of life in patients with systemic lupus erythematosus.
      ,
      • Gautschi O.P.
      • Corniola M.V.
      • Smoll N.R.
      • et al.
      Sex differences in subjective and objective measures of pain, functional impairment, and health-related quality of life in patients with lumbar degenerative disc disease.
      ] and in some specific forms of cancer [
      • Hammerlid E.
      • Taft C.
      Health-related quality of life in long-term head and neck cancer survivors: a comparison with general population norms.
      ]. These differences originate from a combination of the severity of disease, treatment, and presence of comorbidity, among other factors [
      • Phan H.T.
      • Blizzard C.L.
      • Reeves M.J.
      • et al.
      Sex differences in long-term quality of life among survivors after stroke in the INSTRUCT.
      ]. Some authors have suggested the potential impact of gender roles on subjective quality of life [
      • Norris C.M.
      • Murray J.W.
      • Triplett L.S.
      • et al.
      Gender roles in persistent sex differences in health-related quality-of-life outcomes of patients with coronary artery disease.
      ]. Gender — identity, norms and relations — is challenging to measure according to traditional medical methodology, yet it can significantly impact people’s risk behaviour and their resources and resilience after disease [
      • Bale T.L.
      • Epperson C.N.
      Sex differences and stress across the lifespan.
      ]. This variable could, thus, represent a meaningful source of information to improve patients’ long-term journeys.
      In the present study, we analyzed the impact of sex differences on long-term, i.e. up to 10 years, symptoms and functioning in cancer survivors and explored if cohort studies, not intentionally designed to investigate gender, could give any indication of its impact on the life of survivors. Comparing diminished functioning in male and female survivors to a reference population generates insight into the relative impact of these impairments, which are hidden in a simple comparison between female and male cancer survivors. Since the ageing process can naturally impact functioning domains, a direct comparison with cancer-free individuals of the same sex/gender is necessary to reveal potential sex-specific and gender-specific consequences of living with a tumour.

      2. Materials and methods

      2.1 Design and data-collection

      This is a secondary cross-sectional analysis of data collected by the PROFILES (Patient-Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship) registry [
      • van de Poll-Franse L.V.
      • Horevoorts N.
      • van Eenbergen M.
      • et al.
      The Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship registry: scope, rationale and design of an infrastructure for the study of physical and psychosocial outcomes in cancer survivorship cohorts.
      ]. The PROFILES registry is an ongoing cohort study of cancer survivors initiated in 2008. A detailed description of the data collection has been previously published [
      • van de Poll-Franse L.V.
      • Horevoorts N.
      • van Eenbergen M.
      • et al.
      The Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship registry: scope, rationale and design of an infrastructure for the study of physical and psychosocial outcomes in cancer survivorship cohorts.
      ]. Data from the PROFILES registry are freely available for noncommercial scientific research, subject to submission of a study question, privacy and confidentiality restrictions, and registration (www.profilesregistry.nl).

      2.2 Patient population

      The analysis covers four study cohorts from the PROFILES registry, only including nonsex specific cancer types: colorectal, hematologic cancers (chronic lymphocytic leukaemia, non-Hodgkin lymphoma, Hodgkin lymphoma and multiple myeloma), basal cell/squamous cell and thyroid cancer. Patients were recruited between January 2009 and June 2014. Detailed information about the inclusion of the study samples is published elsewhere [
      • Mols F.
      • Husson O.
      • Roukema J.A.
      • et al.
      Depressive symptoms are a risk factor for all-cause mortality: results from a prospective population-based study among 3,080 cancer survivors from the PROFILES registry.
      ,
      • Husson O.
      • Haak H.R.
      • Buffart L.M.
      • et al.
      Health-related quality of life and disease specific symptoms in long-term thyroid cancer survivors: a study from the population-based PROFILES registry.
      ,
      • Oerlemans S.
      • Husson O.
      • Mols F.
      • et al.
      Perceived information provision and satisfaction among lymphoma and multiple myeloma survivors–results from a Dutch population-based study.
      ,
      • Arts L.P.J.
      • Waalboer-Spuij R.
      • de Roos K.P.
      • et al.
      Health-related quality of life, satisfaction with care, and cosmetic results in relation to treatment among patients with keratinocyte cancer in the head and neck area: results from the PROFILES registry.
      ]. Participants were excluded if they were not able to complete a Dutch questionnaire according to their (former) attending specialist (due to, i.e. cognitive impairment, non-native speaker, too ill to participate). Individuals who died or emigrated prior to the start of the study, according to data from the Dutch municipal personal records database and/or data from the hospital of diagnosis, were also excluded. Ethical approval was obtained for all study samples separately from a local certified medical ethics committee (Maxima Medical Centre Veldhoven, the Netherlands).

      2.3 Demographic, social and clinical measures

      Sociodemographic information was obtained from the NCR (sex and age at diagnosis) or self-reported questionnaires (age at questionnaire, education, marital status and comorbidity). Sex was defined in a binary manner (female/male). The questionnaires did not include specific items to assess gender identity and norms. Comorbidity was assessed using the adapted Self-administered Comorbidity Questionnaire (SCQ) [
      • Sangha O.
      • Stucki G.
      • Liang M.H.
      • et al.
      The Self-Administered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research.
      ].
      Clinical data (age at diagnosis, tumour type, primary treatments, date of diagnosis), were also obtained from the NCR. Tumour type was classified according to the third International Classification of Diseases for Oncology (ICDO-3) [
      • Fritz A.
      • Percy C.
      • Jack A.
      • et al.
      International classification of diseases for oncology.
      ,
      • Sobin L.H.
      • Gospodarowicz M.K.
      • Wittekind C.
      TNM classification of malignant tumours, 7th edition.
      ], and cancer stage was classified according to TNM or Ann Arbor Code (Non-Hodgkin lymphoma and Hodgkin lymphoma). Primary treatments received were classified into surgery, systemic therapy (chemotherapy, targeted therapy, immune therapy), radiation therapy (including brachytherapy), hormone therapy, no treatment/active surveillance or unknown.

      2.4 Symptoms and functioning

      The EORTC QLQ-C30 (version 3.0) was used to assess health-related quality of life (symptoms and functioning) [
      • Aaronson N.K.
      • Ahmedzai S.
      • Bergman B.
      • et al.
      The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.
      ]. The questionnaire addresses five different functioning dimensions: physical, role, emotional, cognitive and social. Symptom scales included were fatigue, nausea/vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhoea. Answers were linearly transformed into a score ranging from 0 to 100 [
      • Fayers P.
      • Aarson N.
      • Bjordal K.
      • et al.
      QLQ C-30 scoring manual/EORTC study group on quality of life.
      ]. The total number of symptoms was calculated by summing dichotomized symptom scales (a little, quite a bit or very much agreement with the proposed symptom).
      We employed the Hospital Anxiety and Depression Scale (HADS) to assess symptoms of anxiety and depression. The HADS includes separate anxiety and depression scales, which both consist of seven items. All items were scored on a 0 to 3-point Likert scale, with higher scores indicating more symptoms. Total scores for anxiety and depression ranged from 0 to 21 [
      • Zigmond A.S.
      • Snaith R.P.
      The hospital anxiety and depression scale.
      ].

      2.5 Data of the reference population

      Since 2009, the PROFILES registry annually collects information on symptoms, functioning, comorbidities and lifestyle in a cohort representative of the Dutch-speaking population in the Netherlands [
      • Mols F.
      • Husson O.
      • Oudejans M.
      • et al.
      Reference data of the EORTC QLQ-C30 questionnaire: five consecutive annual assessments of approximately 2000 representative Dutch men and women.
      ]. A random selection of one cancer-free member per household (N = 1408) was made to ensure the independence of observations and was randomly matched to the patient sample based on sex and age group (<40, 40–49, 50–59, 60–69, ≥70) based on the frequency distribution. By using frequency matching, a total of 389 panel members could be matched to the patients included in this study (ratio norm population: cancer patients is 1:0.07). For supplementary analyses, 365 and 629 panel members were matched to colorectal and hematologic cancer patients, respectively (ratio cancer patients: norm population is 0.14 and 0.36).

      2.6 Statistical analysis

      Differences in baseline characteristics between male and female patients, in the total sample and by cancer type, were assessed using independent sample t-tests for continuous variables and Pearson’s χ2 tests for categorical variables. All analyses were two-sided, and p values < 0.05 were considered significant. The clinical significance of the EORTC QLQ-C30 scales was evaluated based on the literature [
      • Cocks K.
      • King M.T.
      • Velikova G.
      • et al.
      Evidence-based guidelines for determination of sample size and interpretation of the European organisation for the research and treatment of cancer quality of life questionnaire core 30.
      ].
      General linear models were computed to assess the differences in functioning and symptoms, between male and female patients, in the total sample and by tumour type, adjusted for predetermined covariates (i.e. age, tumour type, treatments received, cancer stage, number of comorbidities, the time between diagnosis and questionnaire, partner status, educational level, employment status).
      General linear models were used to separately compare patients to a reference population for male and female patients. For supplementary analyses, we additionally assessed the two larger cohorts, colorectal and hematologic cancer patients, separately. We adjusted for covariates that were available in both patient and norm samples (i.e. age at questionnaire, number of comorbidities, partner status, employment status). Statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC, 1999).

      3. Results

      We included a total of 5339 survivors, 2926 male (55%) and 2413 female (45%) (Table 1). As previously reported [
      • de Rooij B.H.
      • Ezendam N.P.M.
      • Mols F.
      • et al.
      Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry.
      ], a higher proportion of females compared to males participated in the study cohorts (72% versus 66%). The participants had a history of four types of cancer: colorectal (N = 2593, 55% male, 49% of the total sample), hematologic (N = 1751, 61% male, 33% of the total sample), basal/squamous cell (N = 691, 51% male, 13% of the total sample) and thyroid (N = 304, 25% male, 6% of the total sample).
      Table 1Sociodemographic and clinical characteristics, by cancer type.
      TotalColorectal cancerHematologic cancers
      Includes indolent (including chronic lymphocytic leukemia) and aggressive B-cell non-Hodgkin lymphoma, Hodgkin lymphoma and multiple myeloma.
      Basal/squamous cell cancerThyroid cancer
      MenWomenMenWomenMenWomenMenWomenMenWomen
      N, %2926 (55)2413 (45)1432 (55)1161 (45)1064 (61687 (39)355 (51)336 (49)75 (25)229 (75)
      Age at diagnosis, M (SD)62.2 (12)60.9 (14)∗∗63.7 (9)63.8 (10)59.3 (14)58.7 (15)67.9 (11)66.4 (13)49.7 (15)45.3 (15)∗
      Age at questionnaire, M (SD)66.8 (12)66.1 (13)∗69.3 (9)69.6 (10)63.2 (14)62.9 (15)69.4 (11)67.9 (13)59.5 (14)55.4 (15)∗
      Disease stage
      According to TNM. Ann Arbor Code was used for Hodgkin lymphoma and Non-Hodgkin lymphoma. For Chronic lymphocytic leukaemia and Multiple myeloma tumour stage was not determined or registered.
      , N (%)
      I652 (22)598 (25)∗400 (28)297 (26)∗189 (18)136 (20)32 (9)26 (8)31 (41)139 (61)∗
      II689 (24)628 (26)506 (35)462 (40)163 (15)124 (20)3 (1)0 (0)17 (23)42 (18)
      III582 (20)471 (20)426 (30)350 (30)140 (13)88 (13)1 (0)0 (0)15 (20)33 (14)
      IV288 (10)184 (8)77 (5)36 (3)203 (19)136 (20)0 (0)0 (0)8 (11)12 (5)
      Not applicable/unknown715 (24)532 (22)23 (2)16 (1)369 (35)203 (30)319 (90)310 (92)4 (5)3 (1)
      Primary treatments received yes/no, N

      (%)
      Surgery1540 (53)1442 (60)∗∗1409 (98)1156 (100)∗∗0 (0)0 (0)58 (16)59 (18)72 (97)227 (99)
      Systemic therapy
      Systemic therapies were: chemotherapy, targeted therapy and immune therapy.
      1155 (39)812 (34)∗∗444 (31)356 (31)707 (66)453 (66)4 (1)3 (1)0 (0)0 (0)
      Radiotherapy748 (26)697 (29)∗∗421 (29)332 (29)272 (26)199 (29)1 (0)0 (0)54 (72)166 (72)
      Hormonal therapy3 (0)6 (0)2 (0)1 (0)0 (0)0 (0)0 (0)0 (0)1 (1)5 (2)
      No therapy/active surveillance257 (9)143 (6)∗∗3 (0)1 (1)253 (24)141 (21)0 (0)0 (0)1 (1)1 (0)
      Unknown319 (11)303 (49)1 (0)1 (0)25 (2)28 (4)∗293 (83)274 (82)0 (0)0 (0)
      Time between diagnosis and invitation, N (%)
      <2 years857 (29)646 (27)∗∗107 (7)92 (8)397 (37)215 (31)352 (99)335 (100)1 (1)4 (2)
      2–3 years660 (23)472 (20)400 (28)280 (24)251 (23)177 (26)1 (0)0 (0)8 (11)25 (11)
      3–5 years489 (17)385 (16)295 (21)229 (20)181 (17)121 (18)1 (0)1 (0)12 (16)34 (15)
      >5 years920 (31)900 (37)630 (44)560 (48)235 (22)174 (25)1 (0)0 (0)54 (72)166 (72)
      Comorbidities, N (%)
      0640 (29)443 (24)∗∗282 (27)194 (23)∗∗237 (29)137 (26)100 (37)69 (28)∗∗21 (36)43 (25)
      1768 (35)592 (33)351 (34)280 (32)309 (38)185 (35)92 (34)74 (30)16 (28)53 (30)
      >1775 (35)779 (43)399 (39)388 (45)275 (34)208 (39)80 (29)105 (42)21 (36)78 (45)
      Heart condition608 (23)327 (15)∗∗298 (22)164 (15)∗∗218 (25)95 (18)∗∗81 (25)46 (16)∗∗11 (17)22 (11)
      Stroke78 (3)45 (2)∗42 (3)24 (2)24 (3)10 (2)11 (4)8 (3)1 (2)3 (2)
      High blood pressure814 (32)723 (33)459 (34)398 (37)230 (27)154 (28)107 (34)110 (36)18 (28)61 (29)
      Lung disease289 (11)269 (13)138 (10)129 (12)106 (13)74 (14)38 (13)43 (15)7 (11)23 (12)
      Diabetes368 (15)228 (11)∗∗224 (17)131 (12)∗∗95 (12)50 (10)42 (14)32 (11)7 (11)15 (7)
      Ulcer53 (2)40 (2)25 (2)16 (1)∗23 (3)12 (2)3 (1)9 (3)∗2 (3)3 (2)
      Kidney disease98 (4)70 (3)65 (5)35 (3)24 (3)18 (4)5 (2)13 (5)4 (4)4 (2)
      Liver disease70 (3)28 (1)∗∗56 (4)22 (2)∗∗13 (2)3 (1)0 (0)3 (1)1 (2)0 (0)
      Blood disease180 (7)164 (8)59 (4)58 (5)109 (14)76 (15)10 (3)19 (7)2 (3)11 (6)
      Thyroid disease85 (3)231 (11)∗∗32 (2)85 (8)∗∗27 (3)56 (11)∗∗6 (2)22 (8)∗∗20 (32)68 (34)
      Depression162 (7)184 (9)∗∗72 (5)98 (9)∗∗76 (10)51 (10)11 (4)18 (7)3 (5)17 (9)
      Arthritis529 (21)792 (37)∗∗240 (18)396 (36)∗∗197 (24)187 (35)∗∗78 (26)147 (49)∗∗14 (22)62 (30)
      Backache706 (28)724 (34)∗∗333 (25)333 (31)∗∗259 (31)185 (35)96 (32)126 (44)∗∗18 (27)80 (40)
      Rheumatism166 (7)197 (10)∗∗82 (6)82 (8)58 (7)50 (10)21 (7)44 (16)∗∗5 (8)21 (11)
      Partner, N (%)
       Yes2389 (83)1667 (70)∗∗1191 (84)774 (67)∗∗847 (81)485 (71)∗∗291 (83)232 (70)∗∗60 (80)176 (77)
       No501 (17)728 (30)226 (16)382 (33)200 (19)194 (29)60 (17)99 (30)15 (20)53 (23)
      Educational level, N (%)
       Lower470 (16)525 (22)∗∗234 (16)279 (24)∗∗123 (12)139 (21)∗∗104 (30)83 (25)∗∗9 (12)24 (11)
       Secondary702 (24)838 (35)318 (22)413 (36)226 (22)224 (33)142 (40)154 (46)16 (21)47 (21)
       Vocational985 (34)694 (29)512 (36)311 (27)381 (36)203 (30)66 (19)79 (24)26 (35)101 (44)
       Higher734 (25)326 (14)356 (25)146 (13)315 (30)109 (16)39 (11)15 (5)24 (32)56 (24)
      Employment status, N (%)
       Employed700 (24)477 (20)∗∗265 (19)139 (12)∗∗311 (29)140 (20)∗∗90 (25)80 (24)34 (45)118 (52)
       Not employed2226 (76)1936 (80)1167 (81)1022 (88)753 (71)547 (80)265 (75)256 (76)41 (55)111 (48)
      Household hours per week, M (SD)4.4 (7)13.6 (13)∗∗4.2 (7)13.1 (13)∗∗4.9 (8)13.4 (13)∗∗//5.1 (6)16.4 (15)∗∗
      Gardening hours per week, M (SD)2.7 (6)1.5 (3)∗∗2.8 (6)1.5 (3)∗∗2.4 (5)1.4 (3)∗∗//2.0 (4)2.4 (5)
      Independent sample t-tests were used for continuous variables and Pearson’s χ2 tests for categorical variables. Abbreviations: M = mean; SD=Standard Deviation, ∗p < 0.05, ∗∗p < 0.01.
      Percentages may not always add up to 100 because they have been rounded off to whole numbers.
      a Includes indolent (including chronic lymphocytic leukemia) and aggressive B-cell non-Hodgkin lymphoma, Hodgkin lymphoma and multiple myeloma.
      b According to TNM. Ann Arbor Code was used for Hodgkin lymphoma and Non-Hodgkin lymphoma. For Chronic lymphocytic leukaemia and Multiple myeloma tumour stage was not determined or registered.
      c Systemic therapies were: chemotherapy, targeted therapy and immune therapy.
      The female patients reported having a partner less often than the males (70% versus 83%, p < 0.01), were less likely to be employed (20% versus 24%, p < 0.01), and had received less formal education. Overall, female patients were more often diagnosed in stage I, a finding primarily attributable to the thyroid cancer cohort. No sex differences were detected at all other cancer stages.
      Overall, female patients appeared more likely to obtain surgery as well as radiotherapy compared to males. Male patients were more likely to obtain systemic therapy. No significant sex differences could be identified in the time since diagnosis and invitation to participate in the study.
      The number of male patients with no comorbidities was higher than that of females (29% versus 24%, p < 0.01) and this difference was consistent across all cohorts (Table 1). Males reported more cardiovascular diseases and diabetes than females (23% versus 15%, p < 0.01 and 15% versus 11%, respectively). Females reported more thyroid disease, depression, arthritis and backache (Table 1).
      Female patients consistently reported more physical symptoms than male patients (Table 2). Female patients described more nausea and vomiting, insomnia, appetite loss, constipation and diarrhoea. Most patients reported more than one symptom, females significantly more than males (mean 2.7 [95% CI = 2.7; 2.8] versus. 2.2 [95% CI = 2.1; 2.3] respectively) except among thyroid cancer patients where no sex differences in the number of reported symptoms were identified. Furthermore, female patients reported significantly higher scores of anxiety (HADS: 5.2 [95% CI = 5.0; 5.4] versus 4.2 [95% CI = 4.0; 4.3], p < 0.01) whereas male patients reported higher scores of depression (HADS: 4.5 [95% CI = 4.4; 4.7] versus 4.2 [95% CI = 4.0; 4.3], p < 0.01) and more financial difficulties (8.2 [95% CI = 7.4; 9.0] versus 6.9 [95% CI = 6.2; 7.7], p < 0.01).
      Table 2General linear models of differences between female and male cancer survivors on quality of life, symptoms, anxiety and depression.
      N, %TotalColorectal cancerHematologic cancersBasal/squamous cell cancerThyroid cancer
      MaleFemaleMaleFemaleMaleFemaleMaleFemaleMaleFemale
      2926 (55)2413 (45)1432 (55)1161 (45)1064 (61)687 (39)355 (51)336 (49)75 (25)229 (75)
      Symptoms
       EORTC QLQ-C30 (0–100), M (SD)
      Fatigue22.8 (25)26.1 (25)∗20.6 (23)23.8 (24)28.9 (28)32.3 (26)12.6 (18)18.6 (24)∗23.0 (24)29.4 (26)
      Nausea and vomiting3.2 (11)5.0 (14)∗∗3.1 (10)4.7 (13)∗4.1 (12)6.6 (16)∗1.1 (5)3.3 (10)∗3.6 (12)4.5 (11)
      Pain14.3 (23)19.7 (27)∗∗13.9 (23)19.7 (26)∗∗17.4 (26)22.9 (29)∗6.8 (14)14.1 (24)∗∗13.8 (24)18.5 (25)
      Dyspnea15.6 (26)14.8 (24)∗14.8 (26)14.5 (25)18.3 (27)17.5 (25)∗10.4 (21)11.5 (22)15.6 (23)13.3 (22)
      Insomnia15.9 (26)26.1 (31)∗∗15.5 (25)27.6 (31)∗∗18.8 (29)27.0 (31)∗∗8.8 (18)20.5 (30)∗∗16.0 (28)24.4 (29)
      Appetite loss5.5 (17)7.9 (20)∗∗4.6 (15)7.3 (18)∗∗7.6 (21)11.0 (24)2.5 (9.8)5.2 (16)4.9 (16)6.3 (19)
      Constipation7.2 (18)10.7 (22)∗∗7.1 (18)10.7 (22)∗∗7.5 (19)11.9 (23)∗∗6.4 (17.2)8.0 (19)7.1 (16)10.9 (21)
      Diarrhoea7.8 (19)9.5 (21)∗∗9.8 (21)12.3 (23)∗∗6.7 (17)7.9 (19)3.5 (12)5.5 (17)7.2 (18)6.3 (17)
      Financial difficulties8.2 (21)6.9 (18)∗∗7.8 (20)6.6 (18)∗∗10.1 (23)8.6 (20)∗∗2.8 (13)4.0 (14)15.3 (25)8.0 (20)∗∗
      Total number of symptoms
      Sum of symptoms fatigue, nausea/vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhoea, if a little, quite a bit or very much endorsement of any item of the symptom-scale.
      2.2 (1.9)2.7 (2.0)∗∗2.2 (1.8)2.8 (1.9)∗∗2.5 (1.9)3.0 (2.0)∗∗1.5 (1.7)2.0 (2.1)∗∗2.2 (1.9)2.7 (1.9)
       HADS (0–21), M (SD)
      Anxiety symptoms4.2 (3.7)5.2 (3.9)∗∗4.2 (3.7)5.2 (3.9)∗∗4.2 (3.8)5.3 (4.0)∗∗N/AN/A4.1 (3.9)4.8 (3.8)
      Depression symptoms4.5 (3.9)4.2 (3.6)∗∗4.5 (3.8)4.2 (3.7)∗∗4.5 (4.0)4.4 (3.7)∗∗N/AN/A4.3 (3.5)3.2 (2.9)∗∗
      Functioning
       EORTC QLQ-C30 (0–100), M (SD)
      Global quality of life76.8 (20)75.5 (19)77.8 (19)76.1 (19)73.8 (21)72.0 (20)81.8 (17)80.6 (18)75.5 (20)75.7 (20)
      Physical Functioning82.5 (20)77.5 (21)∗∗82.4 (20)76.7 (21)∗∗80.2 (21)74.1 (22)∗∗89.4 (17)83.5 (21)∗∗84.1 (19)82.5 (20)
      Role Functioning80.3 (28)78.7 (28)80.3 (28)78.9 (27)76.0 (30)73.1 (29)93.0 (17)87.9 (23)∗82.7 (27)81.5 (27)
      Emotional functioning86.3 (20)83.4 (21)∗87.3 (19)84.1 (20)83.5 (22)80.5 (22)91.2 (15)87.3 (20)∗83.1 (22)83.3 (20)
      Cognitive functioning84.6 (21)84.1 (21)84.7 (20)85.2 (20)82.9 (23)80.6 (23)90.2 (17)88.8 (19)82.2 (21)82.0 (23)
      Social functioning86.7 (23)85.9 (23)86.7 (22)86.1 (22)83.0 (24)81.9 (25)95.8 (12)94.1 (15)85.4 (26)85.2 (25)
      Crude means (M) and standard deviations (SD) are shown. General linear models are adjusted for age, tumour type, treatments received, cancer stage, number of comorbidities, the time between diagnosis and questionnaire, partner status, educational level, employment status. ∗p < 0.05, ∗∗p < 0.01.
      a Sum of symptoms fatigue, nausea/vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhoea, if a little, quite a bit or very much endorsement of any item of the symptom-scale.
      Considering the functioning dimensions of the EORTC questionnaire, female patients reported significantly lower physical (77.5 [95% CI = 76.6; 78.3] versus 82.5 [95% CI = 81.8; 83.2], p < 0.01) and emotional functioning (83.4 [95% CI = 82.6; 84.3] versus 86.3 [95% CI = 85.6; 87.0], p < 0.01) compared to male patients.
      Females in the Dutch reference population also reported all symptoms more frequently than males, resulting in a lower net-difference between female patients and reference females compared to male patients and reference males (Table 3). Due to this trend, the overall long-term cancer burden appears relatively smaller in female patients compared to male patients. Specifically, only insomnia and appetite loss were more frequent in female cancer patients compared to male patients (insomnia: mean differences of +5.9 [95% CI 3.2; 8.6; ] in females versus +4.5 [95% CI 2.8; 6.0] in males; appetite loss: mean difference of +4.0 [95% CI 2.9; 5.0] in females versus +3.1 [95% CI 2.4; 3.8] in males, compared to respective cancer-free populations). Fatigue and dyspnea displayed the highest net discrepancy in male cancer patients versus reference males (fatigue: +7.5% [95% CI 6.0; 9.0] in males versus +4.3% [95% CI = 2.2; 6.4] in females; dyspnea: +7.6% [95% CI = 6.1; 9.1] in males versus +4.4% [95% CI = 2,6; 6.2] in females). When compared to the reference population, anxiety and depressive symptoms were higher in male patients than in females (anxiety symptoms: +1.5 [95% CI = 1,3; 1.7] in males versus +0.9 [95% CI = 0.6; 1.3] in females; depression symptoms: +0.7 [95% CI = 0.5; 1.1] in males versus +0.2 [95% CI = 0.2; 0.5] in females).
      Table 3Comparison between cancer survivors and the age-matched reference population.
      N, %Total patientsReference population
      Reference population was randomly matched to patients based on age (<40, 40–49, 50–59, 60–69, >70) and sex.
      Mean difference patients and reference population
      Reference population was randomly matched to patients based on age (<40, 40–49, 50–59, 60–69, >70) and sex.
      MaleFemaleMaleFemaleMaleFemale
      2926 (55)2413 (45)213 (55)176 (45)
      Symptoms
       EORTC QLQ-C30 (0–100), M (SD)
      Fatigue22.8 (25)26.1 (25)15.3 (18)21.8 (21)+7.5∗∗+4.3∗
      Nausea and vomiting3.2 (11)5.0 (14)1.5 (8)3.7 (9)−1.7∗+1.3
      Pain14.3 (23)19.7 (27)14.0 (20)20.8 (24)+0.3−1.1
      Dyspnea15.6 (26)14.8 (24)8.0 (18)10.4 (19)+ 7.6∗∗+4.4∗
      Insomnia15.9 (26)26.1 (31)11.4 (19)20.3 (27)+4.5∗+5.9∗
      Appetite loss5.5 (17.1)7.9 (20)2.3 (10)4.0 (12)+3.1∗∗+4.0∗∗
      Constipation7.2 (18)10.7 (22)5.0 (13)7.8 (16)+2.1+2.9
      Diarrhoea7.8 (19)9.5 (21)3.0 (10)4.9 (13)+4.9∗∗+4.6∗∗
      Financial difficulties8.2 (21)6.9 (18)2.2 (11)6.3 (18)+6.0∗∗+0.7
      Total number of symptoms
      Sum of symptoms fatigue, nausea/vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhoea, if a little, quite a bit or very much endorsement of the symptom-item or on any item of the symptom-scale.
      2.2 (1.9)2.7 (2.0)1.9 (1.6)2.5 (1.8)+0.3∗+0.2
       HADS (0–21)
      HADS data was missing for basal/squamous cell survivors.
      Anxiety symptoms, M (SD)4.2 (3.7)5.2 (3.9)2.7 (2.7)4.3 (3.8)+1.5∗∗+0.9∗∗
      N (%)453 (18)513 (25)11 (5)28 (16)
      Depression symptoms, M (SD)4.5 (3.9)4.2 (3.6)3.8 (3.2)4.0 (3.2)+0.7∗∗+0.2
      N (%)504 (20)366 (18)23 (11)21 (12)
      Functioning
       EORTC QLQ-C30 (0–100), M (SD)
      Global quality of life76.8 (20)75.5 (19)79.7 (15)74.2 (18)−3.0∗∗+1.3
      Physical Functioning82.5 (20)77.5 (21)89.4 (15)83.6 (19)−6.9∗∗−6.1∗∗
      Role Functioning80.3 (28)78.7 (28)90.2 (17)81.0 (26)−9.9∗∗−2.2
      Emotional functioning86.3 (20)83.4 (21)90.6 (14)84.7 (20)−4.4∗∗−1.3
      Cognitive functioning84.6 (21)84.1 (21)90.6 (16)89.3 (18)−6.0∗∗−5.2∗∗
      Social functioning86.7 (23)85.9 (23)94.5 (14)89.3 (20)−7.8∗∗−3.4
      Analyses were adjusted for covariates available in both patient and norm samples (i.e. age at questionnaire, number of comorbidities, partner status, employment status). ∗p < 0.05, ∗∗p < 0.01.
      a Reference population was randomly matched to patients based on age (<40, 40–49, 50–59, 60–69, >70) and sex.
      b Sum of symptoms fatigue, nausea/vomiting, pain, dyspnea, insomnia, appetite loss, constipation and diarrhoea, if a little, quite a bit or very much endorsement of the symptom-item or on any item of the symptom-scale.
      c HADS data was missing for basal/squamous cell survivors.
      We compared the functioning scores of the female and male cancer patients with the reference population. This comparison highlighted significantly diminished functioning in all dimensions in the male patient population compared to the reference population. In the female patient population, the difference between patients and reference population only affected physical and cognitive functioning (−6.1 [95% CI = −8.1; −4,1] and −5.2 respectively [95% CI = −7; −3.5]). In the male patient population, the highest net losses were observed in the role and social functioning (−9.9 [95% CI = −11.2; −8.6] and −7.7 [95% CI = −9.6; −7.6] respectively; Table 3, Fig. 1). These differences between the male patients and reference males are to be considered clinically relevant, albeit all differences were trivial to small [
      • Cocks K.
      • King M.T.
      • Velikova G.
      • et al.
      Evidence-based guidelines for determination of sample size and interpretation of the European organisation for the research and treatment of cancer quality of life questionnaire core 30.
      ]. We performed a separate analysis of the colorectal and hematologic cancer survivors to assess the robustness of the general trend within subgroups with potentially different underlying physical burdens. Although the severity of symptoms might differ between these subtypes, the general trend of increased functional impairment in the male survivor population could be confirmed (Supplementary Tables 1a and 1b).
      Fig. 1
      Fig. 1EORTC QLQC30 functioning scales comparing patients and normative population, by sex.

      4. Discussion

      To our knowledge, this study represents the first examination of sex differences in symptoms and functioning in long-term cancer survivors. Overall, female patients reported more comorbidities, more symptoms and lower functioning scores in direct comparison to male patients. However, comparison to an age-matched reference population without cancer reduced or inverted these differences. Contrary to our expectation, several symptoms such as fatigue and dyspnea, as well as anxiety and depression, were reported more frequently in the male patients than in the female ones when adjusted to an age-matched reference population. In addition to a higher level of physical and psychological symptoms, males also displayed a more significant net loss in the role and social functioning than females compared to a reference population.
      Long-term symptoms can impact the physical, mental and functional domains of patients’ lives. According to our results, female and male patients experience these effects at different rates. However, these differences are not consistently addressed when providing information, care and counselling to cancer patients. If female and male patients experience a different risk of long-term physical symptoms, this should be openly discussed when therapeutic decisions are made. Although knowledge of future symptoms will not modify their occurrence, awareness can increase patients’ agency. More detailed and nuanced information, if desired, might support their resilience and coping abilities [
      • Bale T.L.
      • Epperson C.N.
      Sex differences and stress across the lifespan.
      ,
      • Tamres L.K.
      • Janicki D.
      • Helgeson V.S.
      Sex differences in coping behavior: a meta-analytic review and an examination of relative coping.
      ].
      Long-term symptoms after cancer therapy can lead to a significant impairment of HRQoL and restrictions in individual functioning. In addition to the physical and psychological effects, broader domains of personal and professional life are affected. Females in the general population, as well as female patients, appear to experience lower levels of functioning and higher levels of symptoms compared to males [
      • Phan H.T.
      • Blizzard C.L.
      • Reeves M.J.
      • et al.
      Sex differences in long-term quality of life among survivors after stroke in the INSTRUCT.
      ,
      • Jolly M.
      • Sequeira W.
      • Block J.A.
      • et al.
      Sex differences in quality of life in patients with systemic lupus erythematosus.
      ,
      • Gautschi O.P.
      • Corniola M.V.
      • Smoll N.R.
      • et al.
      Sex differences in subjective and objective measures of pain, functional impairment, and health-related quality of life in patients with lumbar degenerative disc disease.
      ]. Most studies base their comparisons on patient populations without including reference controls. A recent publication by Nolte and colleagues [
      • Nolte S.
      • Liegl G.
      • Petersen M.A.
      • et al.
      General population normative data for the EORTC QLQ-C30 health-related quality of life questionnaire based on 15,386 persons across 13 European countries, Canada and the Unites States.
      ] provided norm data on the EORTC QLQ-C30, which recapitulate the higher incidence of symptoms in females and the relatively higher functioning scales in males in the general population. Sex differences are, thus, present in the general population. In our sample, female patients reported significantly more physical symptoms. By using a sample of the general population as a reference, only insomnia and appetite loss were significantly worse in female cancer patients compared to males. The net prevalence of symptoms was much lower in female patients than expected by the direct comparison to male patients. In the male patient population, this effect was reversed. Although in a direct comparison with female patients, male patients seemed to experience fewer symptoms, they actually reported more symptoms than females when compared to their age-matched peers without cancer. These findings should be taken into account when providing patients with information before starting therapy and in designing regimens to mitigate its long-term impact. If we are striving for more person-centred care, services should be sex-specific since the persistence of symptoms does not appear to be the same in both sexes.
      In addition to the clinical relevance of our findings [
      • Cocks K.
      • King M.T.
      • Velikova G.
      • et al.
      Evidence-based guidelines for interpreting change scores for the European organisation for the research and treatment of cancer quality of life questionnaire core 30.
      ], there is also a theoretical one. In this study we also tried to explore if the available data would point towards a role of gender, not solely biological sex. The influence of gender has been reported as distinct from biological sex in predicting the recurrence of cardiovascular disease after an initial event [
      • Pelletier R.
      • Khan N.A.
      • Cox J.
      • et al.
      Sex versus gender-related characteristics: which predicts outcome after acute coronary syndrome in the young?.
      ,
      • Pelletier R.
      • Ditto B.
      • Pilote L.
      A composite measure of gender and its association with risk factors in patients with premature acute coronary syndrome.
      ]. Although sex and gender influence each other throughout the life course [
      • Regitz-Zagrosek V.
      Sex and gender differences in health. Science & society series on sex and science.
      ], their impact on health might differ, as reported by Pilote and colleagues. The instrument used in their study includes multiple questions addressing different dimensions of gender, e.g. norms and relations [
      • Pelletier R.
      • Ditto B.
      • Pilote L.
      A composite measure of gender and its association with risk factors in patients with premature acute coronary syndrome.
      ]. We propose that the role and social functioning scales of the EORTC QLQ-C30 questionnaires could be considered in this light. The cohorts included in our analysis do not offer any specific information about gender assessed with validated instruments, but the identified impact on functional domains highlights how the consequences of living with cancer cannot be solely attributed to biological differences. While the prevalence of physical symptoms might be primarily related to biological differences, role and social functioning transcend biology [
      • Tannenbaum C.
      • Ellis R.P.
      • Eyssel F.
      • et al.
      Sex and gender analysis improves science and engineering.
      ]. The diminished role and social functioning identified in male patients compared to the reference population might, therefore, exemplify the impact of cancer on gender norms and relations [
      • Tannenbaum C.
      • Greaves L.
      • Graham I.D.
      Why sex and gender matter in implementation research.
      ,
      • Tate C.C.
      • Youssef C.P.
      • Bettergarcia J.N.
      Integrating the study of transgender spectrum and cisgender experiences of self-categorization from a personality perspective.
      ].
      Gender norms and relations define people’s interaction with their environment and shape their identity and choices. Next to their role as potential predictors of recurrence [
      • Pelletier R.
      • Khan N.A.
      • Cox J.
      • et al.
      Sex versus gender-related characteristics: which predicts outcome after acute coronary syndrome in the young?.
      ] and coping behaviour [
      • Tamres L.K.
      • Janicki D.
      • Helgeson V.S.
      Sex differences in coping behavior: a meta-analytic review and an examination of relative coping.
      ], gender dimensions could have a wider impact on cancer survivors’ long-term health. When informing patients about the long-term consequences of cancer therapy, we should not only include information about sex differences but also about the potential gender-specific impact of functionality changes. Male patients reported a higher level of depression and anxiety than females compared to the reference population. These effects could be related to loss of role and social functioning. Our current data does not allow investigating these dynamics, and future studies are needed to address these questions.
      The current study includes a large, well-characterized population of cancer survivors and reference population, which allowed us to gain insight into previously unaddressed aspects of survivorship. Nevertheless, some limitations need to be considered. The included population is a selected group of patients willing to participate in a cohort study and might, thus, not fully represent the general population of cancer patients. Previous reports have described higher survival rates and increased male participation in this cohort [
      • de Rooij B.H.
      • Ezendam N.P.M.
      • Mols F.
      • et al.
      Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry.
      ]. The female patients in the study reported lower education obtainment than the male patients, as well as living alone more frequently. Although these differences are statistically significant, they are representative of the sex differences in the general Dutch population and are also present in the matched reference population. The included cancer types also differ in their physical expression, and the timing of diagnosis might differ between the populations. Nevertheless, the trends identified in the whole group were clearly shared in the single subgroups, pointing towards a general trend.
      In conclusion, we report significantly higher physical and psychological symptoms and lower functioning in male cancer survivors compared to a matched reference population of cancer-free individuals. Not only did males experience more pronounced levels of symptoms compared to females, but they also experienced a more significant loss of role and social functioning. These differences should be further explored, ideally employing mixed-methods approaches that can allow for an in-depth exploration of the psychosocial, emotional and cultural aspects involved. Furthermore, we propose to specifically investigate the impact of gender norms and relations on the quality of life of cancer survivors, given the identified difference in role and social functioning. The present findings suggest that details on the impact of both sex and gender might be needed to provide adequate counselling and care for long-term cancer survivors.

      Author contribution

      SOP and LvdP conceptualized the research, FM, SO, OH, BdR performed the data collection, BdR performed analysis, SOP and LvdP reviewed data analysis, SOP drafted the paper, all authors reviewed the manuscript and contributed important intellectual content, LvdP, FM, SO and OH acquired funding.

      Funding

      No funds were specifically allocated to the performance of this study. The PROFILES registry was funded by the Dutch Research Council- Investment Grant Large (2016/04981/ZONMW-91101002).

      Conflict of interest statement

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

      Acknowledgements

      We acknowledge the data collection support of the PROFILES registry group.

      Appendix ASupplementary data

      The following is the Supplementary data to this article:

      References

        • Bray F.
        • Ferlay J.
        • Soerjomataram I.
        • et al.
        Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
        CA Cancer J Clin. 2018; 68: 394-424
        • Clocchiatti A.
        • Cora E.
        • Zhang Y.
        • et al.
        Sexual dimorphism in cancer.
        Nat Rev Cancer. 2016; 16: 330-339
        • Klein S.L.
        • Flanagan K.L.
        Sex differences in immune responses.
        Nat Rev Immunol. 2016; 16: 626-638
        • Parekh A.
        • Fadiran E.O.
        • Uhl K.
        • et al.
        Adverse effects in women: implications for drug development and regulatory policies.
        Expet Rev Clin Pharmacol. 2011; 4: 453-466
        • Tran C.
        • Knowles S.R.
        • Liu B.A.
        • et al.
        Gender differences in adverse drug reactions.
        J Clin Pharmacol. 1998; 38: 1003-1009
        • Obias-Manno D.
        • Scott P.E.
        • Kaczmarczyk J.
        • et al.
        The food and drug administration office of women's health: impact of science on regulatory policy.
        J Womens Health (Larchmt). 2007; 16: 807-817
        • Wagner A.D.
        • Oertelt-Prigione S.
        • Adjei A.
        • et al.
        Gender medicine and oncology: report and consensus of an ESMO workshop.
        Ann Oncol. 2019; (1093/annonc/mdz414): 10
        • Tannenbaum C.
        • Greaves L.
        • Graham I.D.
        Why sex and gender matter in implementation research.
        BMC Med Res Methodol. 2016; 16: 145
        • Pelletier R.
        • Khan N.A.
        • Cox J.
        • et al.
        Sex versus gender-related characteristics: which predicts outcome after acute coronary syndrome in the young?.
        J Am Coll Cardiol. 2016; 67: 127-135
        • Ribas A.
        • Wolchok J.D.
        Cancer immunotherapy using checkpoint blockade.
        Science. 2018; 359: 1350-1355
        • Biankin A.V.
        • Piantadosi S.
        • Hollingsworth S.J.
        Patient-centric trials for therapeutic development in precision oncology.
        Nature. 2015; 526: 361-370
        • van de Poll-Franse L.V.
        • Horevoorts N.
        • van Eenbergen M.
        • et al.
        The Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship registry: scope, rationale and design of an infrastructure for the study of physical and psychosocial outcomes in cancer survivorship cohorts.
        Eur J Cancer. 2011; 47: 2188-2194
        • Schmidt C.E.
        • Bestmann B.
        • Kuchler T.
        • et al.
        Gender differences in quality of life of patients with rectal cancer. A five-year prospective study.
        World J Surg. 2005; 29: 1630-1641
        • Miaskowski C.
        Gender differences in pain, fatigue, and depression in patients with cancer.
        J Natl Cancer Inst Monogr. 2004; (1093/jncimonographs/lgh024(32):139-43): 10
        • de Graeff A.
        • de Leeuw J.R.
        • Ros W.J.
        • et al.
        Long-term quality of life of patients with head and neck cancer.
        Laryngoscope. 2000; 110: 98-106
        • Hagedoorn M.
        • Buunk B.P.
        • Kuijer R.G.
        • et al.
        Couples dealing with cancer: role and gender differences regarding psychological distress and quality of life.
        Psycho Oncol. 2000; 9: 232-242
        • Phan H.T.
        • Blizzard C.L.
        • Reeves M.J.
        • et al.
        Sex differences in long-term quality of life among survivors after stroke in the INSTRUCT.
        Stroke. 2019; 50: 2299-2306
        • Jolly M.
        • Sequeira W.
        • Block J.A.
        • et al.
        Sex differences in quality of life in patients with systemic lupus erythematosus.
        Arthritis Care Res (Hoboken). 2019; 71: 1647-1652
        • Gautschi O.P.
        • Corniola M.V.
        • Smoll N.R.
        • et al.
        Sex differences in subjective and objective measures of pain, functional impairment, and health-related quality of life in patients with lumbar degenerative disc disease.
        Pain. 2016; 157: 1065-1071
        • Hammerlid E.
        • Taft C.
        Health-related quality of life in long-term head and neck cancer survivors: a comparison with general population norms.
        Br J Cancer. 2001; 84: 149-156
        • Norris C.M.
        • Murray J.W.
        • Triplett L.S.
        • et al.
        Gender roles in persistent sex differences in health-related quality-of-life outcomes of patients with coronary artery disease.
        Gend Med. 2010; 7: 330-339
        • Bale T.L.
        • Epperson C.N.
        Sex differences and stress across the lifespan.
        Nat Neurosci. 2015; 18: 1413-1420
        • Mols F.
        • Husson O.
        • Roukema J.A.
        • et al.
        Depressive symptoms are a risk factor for all-cause mortality: results from a prospective population-based study among 3,080 cancer survivors from the PROFILES registry.
        J Cancer Surviv. 2013; 7: 484-492
        • Husson O.
        • Haak H.R.
        • Buffart L.M.
        • et al.
        Health-related quality of life and disease specific symptoms in long-term thyroid cancer survivors: a study from the population-based PROFILES registry.
        Acta Oncol. 2013; 52: 249-258
        • Oerlemans S.
        • Husson O.
        • Mols F.
        • et al.
        Perceived information provision and satisfaction among lymphoma and multiple myeloma survivors–results from a Dutch population-based study.
        Ann Hematol. 2012; 91: 1587-1595
        • Arts L.P.J.
        • Waalboer-Spuij R.
        • de Roos K.P.
        • et al.
        Health-related quality of life, satisfaction with care, and cosmetic results in relation to treatment among patients with keratinocyte cancer in the head and neck area: results from the PROFILES registry.
        Dermatology. 2020; 236: 133-142
        • Sangha O.
        • Stucki G.
        • Liang M.H.
        • et al.
        The Self-Administered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research.
        Arthritis Rheum. 2003; 49: 156-163
        • Fritz A.
        • Percy C.
        • Jack A.
        • et al.
        International classification of diseases for oncology.
        in: WHO. World Health Organization, Geneva2000
        • Sobin L.H.
        • Gospodarowicz M.K.
        • Wittekind C.
        TNM classification of malignant tumours, 7th edition.
        Wiley-Blackwell, 2011
        • Aaronson N.K.
        • Ahmedzai S.
        • Bergman B.
        • et al.
        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: 365-376
        • Fayers P.
        • Aarson N.
        • Bjordal K.
        • et al.
        QLQ C-30 scoring manual/EORTC study group on quality of life.
        in: Brussels. 1995
        • Zigmond A.S.
        • Snaith R.P.
        The hospital anxiety and depression scale.
        Acta Psychiatr Scand. 1983; 67: 361-370
        • Mols F.
        • Husson O.
        • Oudejans M.
        • et al.
        Reference data of the EORTC QLQ-C30 questionnaire: five consecutive annual assessments of approximately 2000 representative Dutch men and women.
        Acta Oncol. 2018; 57: 1381-1391
        • Cocks K.
        • King M.T.
        • Velikova G.
        • et al.
        Evidence-based guidelines for determination of sample size and interpretation of the European organisation for the research and treatment of cancer quality of life questionnaire core 30.
        J Clin Oncol. 2011; 29: 89-96
        • de Rooij B.H.
        • Ezendam N.P.M.
        • Mols F.
        • et al.
        Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry.
        Qual Life Res. 2018; 27: 3313-3324
        • Tamres L.K.
        • Janicki D.
        • Helgeson V.S.
        Sex differences in coping behavior: a meta-analytic review and an examination of relative coping.
        Pers Soc Psychol Rev. 2002; 6: 2-30
        • Nolte S.
        • Liegl G.
        • Petersen M.A.
        • et al.
        General population normative data for the EORTC QLQ-C30 health-related quality of life questionnaire based on 15,386 persons across 13 European countries, Canada and the Unites States.
        Eur J Cancer. 2019; 107: 153-163
        • Cocks K.
        • King M.T.
        • Velikova G.
        • et al.
        Evidence-based guidelines for interpreting change scores for the European organisation for the research and treatment of cancer quality of life questionnaire core 30.
        Eur J Cancer. 2012; 48: 1713-1721
        • Pelletier R.
        • Ditto B.
        • Pilote L.
        A composite measure of gender and its association with risk factors in patients with premature acute coronary syndrome.
        Psychosom Med. 2015; 77: 517-526
        • Regitz-Zagrosek V.
        Sex and gender differences in health. Science & society series on sex and science.
        EMBO Rep. 2012; 13: 596-603
        • Tannenbaum C.
        • Ellis R.P.
        • Eyssel F.
        • et al.
        Sex and gender analysis improves science and engineering.
        Nature. 2019; 575: 137-146
        • Tate C.C.
        • Youssef C.P.
        • Bettergarcia J.N.
        Integrating the study of transgender spectrum and cisgender experiences of self-categorization from a personality perspective.
        Rev Gen Psychol. 2014; 18: 302-312