BMJ Open Is Committed to Open Peer Review. As Part of This Commitment We Make the Peer Review History of Every Article We Publish Publicly Available

BMJ Open Is Committed to Open Peer Review. As Part of This Commitment We Make the Peer Review History of Every Article We Publish Publicly Available

BMJ Open: first published as 10.1136/bmjopen-2016-014094 on 17 February 2018. Downloaded from BMJ Open is committed to open peer review. As part of this commitment we make the peer review history of every article we publish publicly available. When an article is published we post the peer reviewers’ comments and the authors’ responses online. We also post the versions of the paper that were used during peer review. These are the versions that the peer review comments apply to. The versions of the paper that follow are the versions that were submitted during the peer review process. They are not the versions of record or the final published versions. They should not be cited or distributed as the published version of this manuscript. BMJ Open is an open access journal and the full, final, typeset and author-corrected version of record of the manuscript is available on our site with no access controls, subscription charges or pay- per-view fees (http://bmjopen.bmj.com). If you have any questions on BMJ Open’s open peer review process please email [email protected] http://bmjopen.bmj.com/ on September 29, 2021 by guest. Protected copyright. BMJ Open: first published as 10.1136/bmjopen-2016-014094 on 17 February 2018. Downloaded from BMJ Open Predicting End of Work Disability After Cancer. A 7 years Follow-up Population-based Cohort Study Using Competing Risks Analysis For peer review only Journal: BMJ Open Manuscript ID bmjopen-2016-014094 Article Type: Research Date Submitted by the Author: 30-Aug-2016 Complete List of Authors: Kiasuwa Mbengi, Régine; Scientific Insitute of Public Health, Belgian Cancer Centre ; Universite Libre de Bruxelles, Centre de Recherche en Santé Environnement et Santé au travail Nicolaie, Alina; Universiteit Gent, Statistical Department Goetghebeur, Els; Universiteit Gent, Applied mathematics, computer science and statistics Otter, Renee; Scientific Institute of Public Health, Belgian Cancer Centre Mortelmans, Katrien; KaMoCo Missinnne, Sarah; Scientific Insitute of Public Health, Belgian Cancer Centre Arbyn, Marc; Scientific Insitute of Public Health, Unit Cancer Epidemiology http://bmjopen.bmj.com/ Bouland, Catherine; Universite Libre de Bruxelles, Centre de Recherche en Santé Environnement et Santé au travail de Brouwer, Christophe; Universite Libre de Bruxelles, Centre de Recherche en Santé Environnement et Santé au travail <b>Primary Subject Epidemiology Heading</b>: Secondary Subject Heading: Public health on September 29, 2021 by guest. Protected copyright. Epidemiology < ONCOLOGY, ONCOLOGY, Organisation of health services < Keywords: HEALTH SERVICES ADMINISTRATION & MANAGEMENT For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open: first published as 10.1136/bmjopen-2016-014094 on 17 February 2018. Downloaded from Page 1 of 36 BMJ Open 1 2 3 4 1 Predicting End of Work Disability After Cancer. A 7-year Follow-up 5 2 Population-based Cohort Study Using Competing Risks Analysis. 6 7 8 3 R. Kiasuwa Mbengia,c, M.A Nicolae b, Els Goetghebeurb, R. Ottera, K. Mortlemansd, S. Missinne a, 9 4 M. Arbyne, C. Boulandc and C. de Brouwerc 10 11 5 a Belgian Cancer Centre, Scientific Institute of Public Health, Brussels (WIV-ISP), Belgium 12 6 b Stat-Gent CRESCENDO, University of Ghent 13 7 c Research Centre for Environmental and Occupational Health, Brussels School of Public Health, Université Libre de Bruxelles (ESP-ULB) 8 d Dr. Katrien Mortelmans, PhD Consulting (KaMoCo) 14 9 e Unit Cancer Epidemiology, Scientific Institute of Public Health, Brussels (WIV-ISP), Belgium 15 10 For peer review only 16 11 Corresponding author: Régine Kiasuwa Mbengi 17 12 [email protected] 18 13 14 rue Juliette Wytsman, 1050 Bruxelles - Belgium 19 14 Office: +32 2 642 57 65 20 15 Mobile: +32 479 3926 58 21 22 23 16 ABSTRACT 24 25 17 Objectives 26 18 The number of workers who are disabled due to cancer is increasing dramatically worldwide. One of the 27 19 main priorities is to preserve their quality of life (QoL) and the sustainability of financing systems for 28 20 sickness absence benefits. We have carried out this study in order to assess factors associated with the 29 21 return to ability to work after cancer-related work disability. This should help with planning of 30 22 rehabilitation needs and tailored programmes. 31 23 Participants 32 24 We conducted this register-based cohort study using individual data from the Belgian Disability http://bmjopen.bmj.com/ 33 25 Insurance. Data on 15, 543 socially insured Belgian people who entered into work disability due to cancer 34 26 in 2007-2011 were used. 35 36 27 Primary and secondary outcome measures 37 28 We estimated the time spent in disability and the cause-specific cumulative incidences of return to ability 38 29 to work stratified by age, gender, occupational class, year of entrance into work disability for 11 cancer 39 30 groups using Kaplan Meier analyses and Cox regression allowing for competing risks. 40 31 Results on September 29, 2021 by guest. Protected copyright. 41 32 The overall median time spent into work disability is 1.59 years (95%CI [1.52-1.66]), ranging from 0.75 42 33 to 4.98 across the 11 cancer groups. By the end of follow-up, more than one-third of work disabled cancer 43 34 survivors were able to RTW (35%). While larger proportions of women were able to RTW at the end of 44 35 follow-up, men who do RTW are able to do so sooner. Women, white-collar, younger and having 45 36 haematological, male genital or breast cancers were the most likely to be able to RTW. 46 37 Conclusion 47 38 Good prognostic factors for the ability to RTW are young age, being female, being a white-collar worker, 48 49 39 and having breast or haematological cancers. 50 40 Looking at our results together with the cancer incidence predictions up to 2025 has a high value for the 51 41 purposes of social security and rehabilitation planning and ascertaining patients’ perspectives. 52 42 53 43 Key words: sickness absence, cancer survivors, competing risks, predictive model, social inequalities 54 44 55 45 56 46 57 47 58 59 Version 30 août 2016 60 1 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open: first published as 10.1136/bmjopen-2016-014094 on 17 February 2018. Downloaded from BMJ Open Page 2 of 36 1 2 3 48 Strengths and limitations of this study: 4 49 • (Good) Generalizability: we used a population-based dataset without loss of follow-up; the 5 6 50 external validity is therefore barley not limited; 7 51 • Methods: we add competing risks to the traditional survival analysis to respect the complexity of 8 52 the outcomes which is still rarely performed in disability studies; 9 53 • High value of our results (if linked with cancer incidence predictions) for the planning of 10 54 rehabilitation needs of cancer patients, up to 2025; 11 55 • Identification of cancer survivors being at risk to be socio-economically excluded; 12 56 • We miss information on treatments and job demands: these could have helped to (1) precise the 13 57 risk profile and (2) tailor RTW interventions 14 58 15 For peer review only 16 59 17 60 BACKGROUND 18 19 61 The direct and indirect effects of work disability represent an important burden for people who are absent 20 21 62 due to sickness, their families and employers [1]. Long-term work disability may lead to social exclusion, 22 23 63 deprivation or economic insecurity [2], as well as poor health [3]. The negative impact of work disability 24 25 64 on both social and health status is of high importance for public health [4] but studies identifying those 26 27 65 cancer survivors who are at risk of experiencing long-term work disability and identifying the avoidable 28 29 30 66 proportion of work disability are lagging behind. 31 32 67 http://bmjopen.bmj.com/ 33 68 Work disability imposes significant costs on society [5,6] with up to 5% of GDP in Organisation for 34 35 36 69 Economic Co-operation and Development (OECD) countries being spent on disability benefits [5]. In 37 38 70 2010, the OECD published a report describing the barriers to (re)integration in the labour market for 39 40 71 people in work disability (i.e. greater competition, heavier workload and work pressure) [5]. The report on September 29, 2021 by guest. Protected copyright. 41 42 72 also describes the underlying social and economic tragedies. Since the results for Belgium were poor, 43 44 73 with a decrease in the number of people with disabilities employed over the past decade, authorities and 45 46 74 social security administrators have been looking for measures or interventions to reverse the trend. A 47 48 49 75 number of studies have been performed to support the authorities, but these are mainly qualitative and are 50 51 76 based on a small sample of cancer survivors [7-13]. 52 53 77 54 55 56 57 58 59 Version 30 août 2016 60 2 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open: first published as 10.1136/bmjopen-2016-014094 on 17 February 2018. Downloaded from Page 3 of 36 BMJ Open 1 2 3 78 Insurance medicine researchers and epidemiologists acknowledge differences between diagnoses in terms 4 5 79 6 of the duration of work disability [14,15]. Overall, the leading causes of work disability are 7 8 80 musculoskeletal disorders and mental health problems, which have been widely studied [16]. 9 10 81 In Belgium, cancer is the fifth largest cause of work disability, with 18,462 people in work disability due 11 12 82 to cancer in 2013 (6.2% of all disabled workers in Belgium) [17] (Table 1).

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