Cancer survivors who fully participate in the PROFILES registry have better health-related quality of life than those who drop out

Patient-reported outcomes (PRO) are patients’ self-reports about the impacts of a health condition on functioning, symptoms, and health-related quality of life (HRQOL) as well as experiences of treatment and care. PRO data can support the provision of patient-centred care by informing decision-making at the individual level, driving quality improvement at a system level, and determining factors that influence patient outcomes on a population level [1]. Missing data poses a challenge for PRO research, particularly as it relates to attrition (i.e. when a participant drops out and is never observed again) [2]. Despite its implications for data quality, analysis, and interpretation, the mechanisms of attrition in population-based PRO research are not well understood [2].

The Netherlands PROFILES registry is a unique system for comprehensive population-level PRO monitoring, which seeks to understand the burden and trajectory of outcomes experienced by cancer survivors post-treatment [3]. Since 2008, PROFILES has collected longitudinal PRO data from over 20,000 cancer survivors, with participation rates similar to or higher than comparable observational studies [4‐6]. Through population-level reach, PROFILES provides a novel way to surmount some of the challenges associated with recruiting and retaining post-treatment cancer survivors in longitudinal clinical research, allowing greater external validity and generalizability [7]. Other advantages include data linkage with the Netherlands Cancer Registry (NCR), which records clinical and sociodemographic information about all individuals newly diagnosed with cancer in the Netherlands. However, this type of observational research requires dedicated participants who are able and willing to participate long term.

Attrition is a ubiquitous problem in longitudinal research [8]. Because it may be selective (e.g. due to declining health or death), attrition can bias the representativeness of the sample [8]. Factors associated with attrition in oncology trials include death, symptom burden, illness, advanced disease, increased age, low socioeconomic status, and being from a minority group [9‐11]. A cross-sectional study comparing invited cancer survivors who did not participate in PROFILES with those who did found that non-participants had lower survival and lower estimated HRQOL than participants [12], but it is not known whether similar differences exist between those who participate long term and those who drop out. Furthermore, there have been few attempts to document the pattern of and reasons for attrition in population-based cohort studies of cancer survivors generally [2, 13]. Understanding how, why, and who is likely to participate in this context has important implications for interpreting findings from PROFILES, estimating sample sizes, and improving participant retention in future studies.

This study aimed to determine the rate of and factors associated with attrition among colorectal cancer survivors participating in the largest cohort of the PROFILES registry, and to assess the impact of attrition on observed HRQOL outcomes over time. This population provides a useful case to examine  the challenges of conducting longitudinal PRO research; colorectal cancer is the third most common cancer in Europe and the world, and the 5-year survival rate in the Netherlands is 65% [14]. The study objectives were to (1) examine sociodemographic and clinical factors that influence the likelihood of attrition in PROFILES, and (2) investigate differences in longitudinal HRQOL, anxiety, and depressive symptoms according to time of dropout.

Compared with full responders, colorectal cancer survivors who dropped out of PROFILES were more likely to be women, older, less educated, and to have depressive symptoms, and less likely to have high SES. Full responders reported better HRQOL at each assessment than participants who dropped out, with poorer outcomes generally indicating earlier dropout. Participants who dropped out after the second, third, or fourth wave showed a steeper decline in global HRQOL and physical functioning and a steeper increase in depressive symptoms  than full responders. Participants who dropped out after the third or fourth wave also showed a steeper decline in social functioning, emotional functioning, and the summary score. Sensitivity analyses suggested this trend was driven by mortality, although first wave dropouts still reported worse initial HRQOL than full responders, unrelated to mortality.

Non-response and attrition have consistently been associated with sociodemographic factors including low education and SES in longitudinal studies with cancer patients [4, 11] and general populations [29‐31] and the link between low SES and poor health—another predictor of attrition—is well established [30‐33]. Cancer patients with low SES are often underrepresented in clinical trials [4, 34, 35], in some instances even after accounting for education and comorbidity [35]. The higher rate of dropout among women in our sample was not unexpected, given that men are more likely to participate in PROFILES than women [12]. This is contrary to evidence that participation in population-based research is generally higher among women than men [36, 37] although studies have also observed the opposite [38, 39]. The results also differ from numerous studies with cancer populations that did not find associations between sex and participation [4‐6] or attrition [9‐11]. An explanation may be provided by growing evidence for sex-based differences in response to anticancer treatments, showing that women experience higher incidence of toxicity and adverse reactions than men [40, 41]. It is possible that women in our sample experienced more treatment-related symptoms than men, which made them more likely to discontinue participation. Further research is needed to give insight into sex differences in cancer and the resulting impact on research participation and other behaviours.

Associations between older age and attrition have been reported in clinical cancer trials [34], and linked with cognitive impairment and poorer health [42]. Contrary to evidence demonstrating a link between higher prevalence of health-related problems and attrition, having a higher number of comorbid conditions was not associated with dropout [31, 38]. Cancer stage did not predict likelihood of full response, although other studies have found that patients with more advanced cancer are more likely to drop out [11].

Participants who dropped out reported higher prevalence of depressive symptoms, which increased more steeply over time, compared with full responders. Epidemiologic studies have found underestimation of psychiatric disorders due to non-participation [31, 43] although the relationship between anxiety, depression, and research participation among cancer survivors is understudied. Depression frequently appears to be associated with reduced physical functioning and cancer-related symptoms including fatigue and pain [44, 45]; all of which may limit a person’s willingness or capacity to participate in research.

Our results demonstrate that participants who drop out of PROFILES have significantly lower (statistically and clinically) HRQOL than those who participate until the final assessment. Independent of mortality, first wave dropouts reported worse HRQOL at baseline than full responders, which could be explained by cancer or other illness hindering study participation. Given the recent finding that PROFILES participants survive longer than non-participants [12], our results reinforce that cancer survivors with the poorest health are likely to be underrepresented in population-based research. The problem of selection bias in PRO research has been highlighted in studies of ovarian and head and neck cancer patients undergoing or up to 1 year post-treatment [2, 13, 46], where participants with the lowest baseline HRQOL were more likely to drop out. After separating participants with attrition due to death, one study observed fewer group differences at baseline after adjustment for sociodemographic and clinical factors [47]. With 5-year follow-up and a large population-based sample allowing subgroup analysis, our study builds upon this work, providing longer-term insight into the impact of attrition on HRQOL estimates. Since dropout may be an indicator of poorer health as well as withdrawal from other activities, access to PROFILES participation data could help clinicians identify patients at risk and refer them to clinical interventions.

It is likely that participation was influenced by factors beyond those measured. Participation in population-based research is in decline, possibly owing to increased requests to participate in research, heightened demands and complexity of research procedures, and a general decrease in volunteerism [29]. Characteristics of longitudinal studies with high retention include individually tailored retention strategies, iterative adaptation and refinement of retention processes, and innovative and persistent research teams [48]. Our results suggest that efforts to address representativeness and retention in PROFILES might best be directed towards recruitment and the first follow-up. To increase participation, PROFILES has recently implemented phone calls to consenting patients to explain the study. This strategy appears to have improved the initial response rate, but it is unknown whether it will help to minimize attrition. Formal evaluation of this approach is recommended.

To our knowledge, no studies have explored the impact of attrition on HRQOL in cancer survivors using a longitudinal and population-based cohort of this size. Study merits include the sampling frame and availability of objective sociodemographic and clinical data on participants and non-participants. Limitations include the lack of data on reasons for non-response, which could facilitate a better understanding of attrition in this population. Data on participant’s racial and ethnic backgrounds were also lacking. Given that individuals from racial minorities are underrepresented in research [49] and less likely to participate in palliative oncology trials [9], this information should be considered. Because clinical data from the NCR was only available at diagnosis, a lack of information about recurrence and disease progression was another limitation. Finally, because all participants were colorectal cancer survivors, the results cannot be generalized beyond this group. Due to differences in the timing and methods of data collection between different PROFILES cohorts, we elected to focus this investigation on one sample. Examining whether patterns of attrition vary between cohorts of cancer survivors participating in PROFILES is an avenue for future investigation.

The study findings suggest that further investigation of statistical methods to adjust for non-response and attrition in longitudinal HRQOL studies is warranted. Transparent reporting of participation and justification for how missing data were handled in future studies will facilitate interpretation. Although attrition is not fully preventable, strategies designed to retain participants [48, 50] particularly those at higher risk of attrition could improve representativeness. Financial incentives have been repeatedly associated with higher participant retention in population-based cohort studies [51] and retention rates have been found to increase with the value of monetary incentive offered [50, 51]. Tailored strategies including regular newsletters and personalized reminders, non-financial incentives, educational discussion forums, and annual events have been successfully implemented in longitudinal cohort studies with high retention rates [48]. It is hypothesised that these approaches may promote participant engagement, reinforce study benefits and identity, strengthen staff-participant relationships, and foster a sense of community, although rigorous evaluation of their (cost-)effectiveness is lacking [48]. Evidence suggests that retention rates increase with the number of strategies used [50] and therefore using a combination of methods appropriate to the study population and context is recommended.

Our findings support and expand upon other longitudinal studies in oncology showing a selection bias, whereby loss of participants due to death or illness during follow-up produces overestimates of HRQOL [13, 46, 47]. Cancer survivors with the poorest health are at the highest risk of dropping out of PROFILES and therefore of withdrawing from other activities too, including those that may benefit well-being. Thus, optimizing participation in PROFILES—a potential mechanism for providing information and access to support—is an avenue for keeping this at-risk group engaged. Understanding the biasing effects of selective attrition on PRO will help to contextualize findings from PROFILES and inform strategies for recruitment, retention, and analysis in population-based research.