A systematic review and development of a classification framework for factors associated with missing patient-reported outcome data

Completeness of repeated patient-reported outcome measures in adult rehabilitation: a randomized controlled trial in a diverse clinical population

BACKGROUND

Data collection through patient-reported outcome measures (PROMs) is essential for the purpose of rehabilitation research and registries. Existing problems with incomplete PROM data may relate to the patient burden and data set length. This study aimed to analyse response patterns and degree of data completeness in systematic outcome assessments conducted within a clinical study in a multidisciplinary rehabilitation setting, comparing completeness of a brief and a longer set of PROMs.

METHODS

The Norwegian RehabNytte Cohort was developed to monitor patients' long-term benefit of rehabilitation and progress on PROMs. Adults admitted to one of 17 institutions providing mostly inpatient rehabilitation in secondary healthcare were included between January 2019 and March 2020, and followed for one year. For the purpose of the current randomized controlled trial, the Cohort-patients in 16/17 institutions were randomized to complete either a brief or a longer set of PROMs at admission, discharge, and after 3, 6 and 12 months. The brief set comprised the EQ-5D-5L and additional generic PROMs commonly used in rehabilitation settings. The longer data set expanded upon the brief set by including the Patient-Specific Functional Scale and the 29-item version of the PROMIS Profile instruments. Completeness was measured as the extent of present applicable PROM data at each time point. In addition, we assessed response patterns in terms of dropout rates and intermittently missed assessment events. The RehabNytte study is registered under ClinicalTrial.gov (NCT03764982, first posted 05.12.2018).

RESULTS

Of the 2904 patients included, 1455 were assigned to the brief data set and 1449 to the longer data set. The majority of patients were referred to rehabilitation for rheumatic and musculoskeletal diseases (39.3%) or cancer (26.9%). The data set completeness was significantly higher in the brief set compared to the longer (p < 0.001). From admission to 12 months follow-up, differences in completeness between groups ranged from 6.5 to 12.6 percentage points, consistently favouring the brief set. Completeness was highest at admission, reaching 96.8% (95% CI 0.96-0.98) for the brief set and 84.2% (95% CI 0.82-0.86) for the longer set. The lowest completeness was observed at discharge, with 46.0% (95% CI 0.43-0.49) for the brief set and 39.5% (95% CI 0.37-0.42) for the longer one. Discharge was the only time point without automatic reminders to non-responders from the digital data collection system. Patients responding to the longer data set exhibited the highest dropout rates, while degree of intermittent missing data was comparable between groups. In both groups, only one-third of patients provided complete or partly responses at all five time points.

CONCLUSIONS

This study demonstrated that a brief set of PROMs achieved higher data completeness compared to a longer set, when used for repeated measurements in a rehabilitation research setting.

Enhancing representativeness of patient-reported outcomes in routine radiation oncology care: a quality improvement protocol to address non-response

INTRODUCTION

Non-response significantly undermines the representativeness of patient-reported outcome (PRO) data, thereby compromising its utility for facilitating high-value, equitable, patient-centred care in cancer clinics. Quality improvement studies are needed to assess the representativeness of PRO data collected in routine care, identify the underlying causes of non-response and develop novel methods to ensure data representativeness. Using a multilevel framework and a mixed-methods approach, we have three aims: (1) characterise the non-response of the Global-10 across clinic, provider and patient levels; (2) identify multilevel causes of non-response and potential strategies to improve representativeness in PRO collection; and (3) develop effective modifications to missing-data methods to enhance the representativeness of pre-existing PRO data.

METHODS AND ANALYSIS

Our primary data source is the Patient Reported Outcomes Measurement Information System Global-10, collected as part of routine care at the Radiation Oncology clinics within the Mass General Brigham (MGB) healthcare system. Other sources include (1) Harvard Catalyst for provider-specific data, (2) MGB administrative data, (3) public Centers for Medicare & Medicaid Services data and (4) the National Plan and Provider Enumeration System. We will conduct quantitative analyses to assess variations in Global-10 non-response across multilevel factors. Additionally, we will use qualitative interviews with patients and clinical professionals to understand the causes of non-response and to formulate strategies to expand the reach of PRO collection to underrepresented cancer patients, improve their completions and enhance overall data representativeness. Finally, we will integrate implementation science knowledge and findings from the first two aims into missing-data methods to manage non-response in the pre-existing Global-10 data and to evaluate their performance in preserving representativeness.

ETHICS AND DISSEMINATION

The study protocol was reviewed and approved by the Institutional Review Board at the Dana-Farber/Harvard Cancer Center (24-225). Written informed consent will be obtained from participants. Study findings will be disseminated through peer-reviewed publications and presentations at national and international conferences.

Several methods for assessing research waste in reviews with a systematic search: a scoping review

Background

Research waste is present in all study designs and can have significant consequences for science, including reducing the reliability of research findings and contributing to the inefficient use of resources. Estimates suggest that as much as 85% of all biomedical research is wasted. However, it is uncertain how avoidable research waste is assessed in specific types of study designs and what methods could be used to examine different aspects of research waste. We aimed to investigate which methods, systematic reviews, scoping reviews, and overviews of reviews discussing research waste, have used to assess avoidable research waste.

Materials and Methods

We published a protocol in the Open Science Framework prospectively (https://osf.io/2fbp4). We searched PubMed and Embase with a 30-year limit (January 1993-August 2023). The concept examined was how research waste and related synonyms (e.g., unnecessary, redundant, duplicate, etc.) were assessed in reviews with a systematic search: systematic, scoping, or overviews of reviews. We extracted data on the method used in the review to examine for research waste and for which study design this method was applied.

Results

The search identified 4,285 records of which 93 reviews with systematic searches were included. The reviews examined a median of 90 (range 10-6,781) studies, where the study designs most commonly included were randomized controlled trials (48%) and systematic reviews (33%). In the last ten years, the number of reports assessing research waste has increased. More than 50% of examined reviews reported evaluating methodological research waste among included studies, typically using tools such as one of Cochrane Risk of Bias tools (n = 8) for randomized controlled trials or AMSTAR 1 or 2 (n = 12) for systematic reviews. One fourth of reviews assessed reporting guideline adherence to e.g., CONSORT (n = 4) for randomized controlled trials or PRISMA (n = 6) for systematic reviews.

Conclusion

Reviews with systematic searches focus on methodological quality and reporting guideline adherence when examining research waste. However, this scoping review revealed that a wide range of tools are used, which may pose difficulties in comparing examinations and performing meta-research. This review aids researchers in selecting methodologies and contributes to the ongoing discourse on optimizing research efficiency.

Relationship between reasons for intermittent missing patient-reported outcomes data and missing data mechanisms

PURPOSE

Non-response (NR) to patient-reported outcome (PRO) questionnaires may cause bias if not handled appropriately. Collecting reasons for NR is recommended, but how reasons for NR are related to missing data mechanisms remains unexplored. We aimed to explore this relationship for intermittent NRs.

METHODS

Patients with multiple myeloma completed validated PRO questionnaires at enrolment and 12 follow-up time-points. NR was defined as non-completion of a follow-up assessment within seven days, which triggered contact with the patient, recording the reason for missingness and an invitation to complete the questionnaire (denoted "salvage response"). Mean differences between salvage and previous on-time scores were estimated for groups defined by reasons for NR using linear regression with clustered standard errors. Statistically significant mean differences larger than minimal important difference thresholds were interpreted as "missing not at random" (MNAR) mechanism (i.e. assumed to be related to declining health), and the remainder interpreted as aligned with "missing completely at random" (MCAR) mechanism (i.e. assumed unrelated to changes in health).

RESULTS

Most (7228/7534 (96%)) follow-up questionnaires were completed; 11% (802/7534) were salvage responses. Mean salvage scores were compared to previous on-time scores by reason: those due to hospital admission, mental or physical reasons were worse in 10/22 PRO domains; those due to technical difficulties/procedural errors were no different in 21/22 PRO domains; and those due to overlooked/forgotten or other/unspecified reasons were no different in any domains.

CONCLUSION

Intermittent NRs due to hospital admission, mental or physical reasons were aligned with MNAR mechanism for nearly half of PRO domains, while intermittent NRs due to technical difficulties/procedural errors or other/unspecified reasons generally were aligned with MCAR mechanism.

Comparing patient-reported outcomes measurement information system® (PROMIS®)-16 domain scores with the PROMIS-29 and 5-item PROMIS cognitive function scores

PURPOSE

This study evaluates the interpretability of Patient-Reported Outcomes Measurement Information System® (PROMIS®)-16 profile domain scores (physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function - abilities, and fatigue) compared to the PROMIS-29 scores and a 5-item PROMIS cognitive function score. The study aims to provide insights into using these measures in clinical and research settings.

METHODS

Analyses were conducted using data from 4130 adults from a nationally representative, probability-based internet panel between September and October 2022. A subset of 1256 individuals with back pain was followed up at six months. We compared the PROMIS-16 profile with the corresponding domain scores from the PROMIS-29 and a custom five-item cognitive function measure. We evaluated (1) reliability through inter-item correlations within each domain and (2) criterion validity by comparing PROMIS-16 profile with the corresponding longer PROMIS measures: (a) standardized mean differences in domain scores, (b) correlations, and (c) concordance of change (i.e., got worse, stayed the same, got better) among those with back pain from baseline to six months later using the reliable change index. We report the Kappa coefficient of agreement and the frequency and percentage of participants with concordant classifications.

RESULTS

Inter-item correlations for the PROMIS-16 domains ranged from 0.65 in cognitive function to 0.92 in pain interference. Standardized mean differences between PROMIS-16 and the scores for the corresponding longer PROMIS domains were minimal (< 0.2). Correlations among the corresponding domain scores ranged from 0.82 for sleep disturbance to 0.98 for pain interference. The percentage of concordance in change groups ranged from 63% for sleep disturbance to 88% for pain interference. Except for sleep disturbance, the change groups derived from the PROMIS-16 showed moderate to substantial agreement with scores estimated from the longer PROMIS measures (Kappa coefficients ≥ 0.41).

CONCLUSION

The PROMIS-16 domain scores perform similarly to the longer PROMIS measures and can be interpreted in the same way. This similarity indicates that PROMIS-16 can be useful for research as a brief health-related quality-of-life profile measure.

Missingness mechanisms and generalizability of patient reported outcome measures in colorectal cancer survivors - assessing the reasonableness of the "missing completely at random" assumption

BACKGROUND

Patient-Reported Outcome Measures (PROM) provide important information, however, missing PROM data threaten the interpretability and generalizability of findings by introducing potential bias. This study aims to provide insight into missingness mechanisms and inform future researchers on generalizability and possible methodological solutions to overcome missing PROM data problems during data collection and statistical analyses.

METHODS

We identified 10,236 colorectal cancer survivors (CRCs) above 18y, diagnosed between 2014 and 2018 through the Danish Clinical Registries. We invited a random 20% (2,097) to participate in a national survey in May 2023. We distributed reminder e-mails at day 10 and day 20, and compared Initial Responders (response day 0-9), Subsequent Responders (response day 10-28) and Non-responders (no response after 28 days) in demographic and cancer-related characteristics and PROM-scores using linear regression.

RESULTS

Of the 2,097 CRCs, 1,188 responded (57%). Of these, 142 (7%) were excluded leaving 1,955 eligible CRCs. 628 (32%) were categorized as initial responders, 418 (21%) as subsequent responders, and 909 (47%) as non-responders. Differences in demographic and cancer-related characteristics between the three groups were minor and PROM-scores only marginally differed between initial and subsequent responders.

CONCLUSION

In this study of long-term colorectal cancer survivors, we showed that initial responders, subsequent responders, and non-responders exhibit comparable demographic and cancer-related characteristics. Among respondents, Patient-Reported Outcome Measures were also similar, indicating generalizability. Assuming Patient-Reported Outcome Measures of subsequent responders represent answers by the non-responders (would they be available), it may be reasonable to judge the missingness mechanism as Missing Completely At Random.

A review of patient-reported outcomes used for regulatory approval of oncology medicinal products in the European Union between 2017 and 2020

Introduction

Cancer and corresponding available treatments are associated with substantial symptoms and functional limitations. In this context, collection of patient-reported outcomes (PRO) in clinical trials gained special interest and is recommended by regulatory authorities. Within clinical trials framework, PRO may provide evidence to support medicines approval, labeling and marketing claims. This study aims to analyze the existing evidence based on PRO as part of new oncology indications receiving positive opinions issued by the European Medicines Agency (EMA) between 2017 and 2020 and to identify PRO related label claims granted.

Methodology

Oncology medicinal products and indications approved by the European Commission following a positive opinion from the EMA between 2017 and 2020 were identified. European Public Assessment Report (EPAR) and Summary of Product Characteristics (SmPC) were reviewed for each medicinal product to identify use of PRO and PRO label claims.

Results

A total of 128 oncology indications, corresponding to 76 medicines, were approved; of those, 100 (78.1%) included PRO in the confirmatory clinical trials. Thirty-seven indications were supported by double-blind randomized trials and the remainder 63 by open-label trials. Out of the 104 confirmatory trials analyzed, PRO were defined as a secondary endpoint in 60 studies (57.7%), exploratory in 31 (29.8%) and as both in 13 (12.5%). In total, 54 different PRO measures (PROM) were used, of those 41 (75.9%) were disease-specific measures. Nevertheless, PROM selected relied on the EORTC (41.3%), FACIT (17.1%) and EQ-5D (29.2%) measures. A total of 76 indications (59.4%) had PRO reviewers comments included in the EPAR, however only 22 indications (17.8%) included label claims in the SmPC. The reasons identified in the EMA assessment supporting the exclusion of PRO claims were described for 34 indications (44.7%).

Conclusions

Despite growing recognition of the value of PRO data for the development of improved cancer therapies, PRO implementation remains challenging. The main reasons identified in our study are related with study design, missing data, study conduct and PROM selection.

Improving the patient-reported outcome sections of clinical trial protocols: a mixed methods evaluation of educational workshops

Introduction

Failure to incorporate key patient-reported outcome (PRO) content in trial protocols affects the quality and interpretability of the collected data, contributing to research waste. Our group developed evidence-based training specifically addressing PRO components of protocols. We aimed to assess whether 2-day educational workshops improved the PRO completeness of protocols against consensus-based minimum standards provided in the SPIRIT-PRO Extension in 2018.

Method

Annual workshops were conducted 2011–2017. Participants were investigators/trialists from cancer clinical trials groups. Although developed before 2018, workshops covered 15/16 SPIRIT-PRO items. Participant feedback immediately post-workshop and, retrospectively, in November 2017 was summarised descriptively. Protocols were evaluated against SPIRIT-PRO by two independent raters for workshop protocols (developed post-workshop by participants) and control protocols (contemporaneous non-workshop protocols). SPIRIT-PRO items were assessed for completeness (0 = not addressed, 10 = fully addressed). Mann–Whitney U tests assessed whether workshop protocols scored higher than controls by item and overall.

Results

Participants (n = 107) evaluated the workshop positively. In 2017, 16/41 survey responders (39%) reported never applying in practice; barriers included role restrictions (14/41, 34%) and lack of time (5/41, 12%). SPIRIT-PRO overall scores did not differ between workshop (n = 13, median = 3.81/10, interquartile range = 3.24) and control protocols (n = 9, 3.51/10 (2.14)), (p = 0.35). Workshop protocols scored higher than controls on two items: ‘specify PRO concepts/domains’ (p = 0.05); ‘methods for handling missing data’ (p = 0.044).

Conclusion

Although participants were highly satisfied with these workshops, the completeness of PRO protocol content generally did not improve. Additional knowledge translation efforts are needed to assist protocol writers address SPIRIT-PRO guidance and avoid research waste that may eventuate from sub-optimal PRO protocol content.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-022-03127-w.

Knowledge translation concerns for the CONSORT-PRO extension reporting guidance: a review of reviews

This review of reviews aimed to appraise the use of the CONSORT-PRO Extension as an evaluation tool for assessing the reporting of patient-reported outcome (PROs) in publications, and to describe the reporting of PRO research across reviews. We also outlined how variation in such evaluations impacts knowledge translation and may lead to potential misuse of the CONSORT-PRO Extension. We systematically searched Medline, Pubmed and CINAHL from 2013 to 2025 March 2021 for reviews of the completeness of reporting of PRO endpoints according to CONSORT-PRO criteria. Two reviewers extracted details of each review, the percentage of included studies that addressed each CONSORT-PRO item, and key recommendations from each review. Fourteen reviews met inclusion criteria, and only six of these used the full CONSORT-PRO checklist with minimal justified modifications. The remaining eight studies made significant or unjustified adjustments to the CONSORT-PRO Extension. Review studies also varied in how they scored multi-component CONSORT-PRO items. CONSORT-PRO items were often unreported in trial reports, and certain CONSORT-PRO items were reported less often than others. The reporting of statistical approaches to dealing with missing PRO data were poor in RCTs included in all 14 review articles. Studies reviewing PRO publications often omitted recommended CONSORT-PRO items from their evaluations, which may cause confusion among readers regarding how best to report their PRO research according to the CONSORT-PRO extension. Many trials published since CONSORT-PRO's release did not report recommended CONSORT-PRO items, which may lead to misinterpretation and consequently to research waste.

Developing an online, searchable database to systematically map and organise current literature on retention research (ORRCA2)

BACKGROUND

Addressing recruitment and retention challenges in trials is a key priority for methods research, but navigating the literature is difficult and time-consuming. In 2016, ORRCA (www.orrca.org.uk) launched a free, searchable database of recruitment research that has been widely accessed and used to support the update of systematic reviews and the selection of recruitment strategies for clinical trials. ORRCA2 aims to create a similar database to map the growing volume and importance of retention research.

METHODS

Searches of Medline (Ovid), CINAHL, PsycINFO, Scopus, Web of Science Core Collection and the Cochrane Library, restricted to English language and publications up to the end of 2017. Hand searches of key systematic reviews were undertaken and randomised evaluations of recruitment interventions within the ORRCA database on 1 October 2020 were also reviewed for any secondary retention outcomes. Records were screened by title and abstract before obtaining the full text of potentially relevant articles. Studies reporting or evaluating strategies, methods and study designs to improve retention within healthcare research were eligible. Case reports describing retention challenges or successes and studies evaluating participant reported reasons for withdrawal or losses were also included. Studies assessing adherence to treatments, attendance at appointments outside of research and statistical analysis methods for missing data were excluded. Eligible articles were categorised into one of the following evidence types: randomised evaluations, non-randomised evaluations, application of retention strategies without evaluation and observations of factors affecting retention. Articles were also mapped against a retention domain framework. Additional data were extracted on research outcomes, methods and host study context.

RESULTS

Of the 72,904 abstracts screened, 4,364 full texts were obtained, and 1,167 articles were eligible. Of these, 165 (14%) were randomised evaluations, 99 (8%) non-randomised evaluations, 319 (27%) strategies without evaluation and 584 (50%) observations of factors affecting retention. Eighty-four percent (n = 979) of studies assessed the numbers of participants retained, 27% (n = 317) assessed demographic differences between retained and lost participants, while only 4% (n = 44) assessed the cost of retention strategies. The most frequently reported domains within the 165 studies categorised as 'randomised evaluations of retention strategies' were participant monetary incentives (32%), participant reminders and prompts (30%), questionnaire design (30%) and data collection location and method (26%).

CONCLUSION

ORRCA2 builds on the success of ORRCA extending the database to organise the growing volume of retention research. Less than 15% of articles were randomised evaluations of retention strategies. Mapping of the literature highlights several areas for future research such as the role of research sites, clinical staff and study design in enhancing retention. Future studies should also include cost-benefit analysis of retention strategies.

Patient-Reported Outcomes in Cardiovascular Trials

Patient-reported outcomes (PROs) are reports of a person's health status that provide a global perspective of patient well-being. PROs can be classified into 4 primary domains: global, mental, physical, and social health. In this descriptive review, we focus on how PROs can be used in cardiac clinical trials, with an emphasis on cardiac surgical trials for patients with coronary heart disease and heart failure. We also highlight ongoing challenges and provide specific suggestions and novel opportunities to advance cardiac clinical trials. Current challenges include the long-term measurement of PROs in clinical trials beyond 1 year, inconsistency in the choice of the outcome measures among studies, and the lack of measurement of PROs across multiple domains. Opportunities for advancement include measuring PROs using consumer health informatics tools, including returning information back to participants in formats that they can understand using visualization. Future opportunities include quantifying cohort-specific minimal clinically important differences for PROs.

SPIRIT-PRO Extension explanation and elaboration: guidelines for inclusion of patient-reported outcomes in protocols of clinical trials

Patient-reported outcomes (PROs) are used in clinical trials to provide valuable evidence on the impact of disease and treatment on patients' symptoms, function and quality of life. High-quality PRO data from trials can inform shared decision-making, regulatory and economic analyses and health policy. Recent evidence suggests the PRO content of past trial protocols was often incomplete or unclear, leading to research waste. To address this issue, international, consensus-based, PRO-specific guidelines were developed: the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT)-PRO Extension. The SPIRIT-PRO Extension is a 16-item checklist which aims to improve the content and quality of aspects of clinical trial protocols relating to PRO data collection to minimise research waste, and ultimately better inform patient-centred care. This SPIRIT-PRO explanation and elaboration (E&E) paper provides information to promote understanding and facilitate uptake of the recommended checklist items, including a comprehensive protocol template. For each SPIRIT-PRO item, we provide a detailed description, one or more examples from existing trial protocols and supporting empirical evidence of the item's importance. We recommend this paper and protocol template be used alongside the SPIRIT 2013 and SPIRIT-PRO Extension paper to optimise the transparent development and review of trial protocols with PROs.

Single Assessment Numeric Evaluation for instability as an alternative to the Rowe score

BACKGROUND

Several functional outcome scores have been proposed for the evaluation of shoulder instability. Most are multiple-item questionnaires, which can be time-consuming and difficult for patients to understand, as well as leading to lack of compliance. The Single Assessment Numeric Evaluation (SANE) score is a single question that has recently gained widespread acceptance based on its simplicity and correlation with more complex scoring systems. The purpose of this study was to assess the correlation of a new modified version of the SANE score, the SANE-instability score, with the Rowe score after treatment for shoulder instability.

MATERIALS AND METHODS

We prospectively evaluated a consecutive series of 253 patients (268 shoulders) treated surgically or nonoperatively for shoulder instability between November 2017 and November 2019, for whom the Rowe and SANE-instability scores were collected before treatment and/or after treatment. The SANE-instability score was assessed with the following question: "What is the overall percent value of your shoulder if a completely stable shoulder represents 100%?" Correlations were tested using the Pearson coefficient (r) and interpreted as very high (r = 0.90-1.00), high (r = 0.70-0.89), moderate (r = 0.50-0.69), low (r = 0.30-0.49), or negligible (r = 0.00-0.29). Subgroup analyses were also performed to observe correlation variations according to follow-up length (before treatment and at 6, 12, 26, 52, and 104 weeks after treatment), patient age (<20, 20-29, 30-39, or ≥40 years), and type of treatment (nonoperative or surgical).

RESULTS

The overall correlation between the SANE-instability and Rowe scores was high (r = 0.85, P < .001). Subgroup analyses revealed that the correlation between the 2 scores was high before treatment (r = 0.74); moderate at 6 and 12 weeks after treatment (r = 0.66 and r = 0.57, respectively); and then high at 26, 52, and 104 weeks after treatment (r = 0.75, r = 0.75, and r = 0.78, respectively) (P < .001). The correlation was high across all types of treatment (r = 0.76-0.85), high for patients aged ≥ 20 years (r = 0.80-0.86), and very high for patients aged < 20 years (r = 0.93) (P < .001).

CONCLUSION

This study demonstrated a significant correlation between the SANE-instability and Rowe scores before and after treatment, as well as across all patient age groups and treatments. Owing to its high simplicity, the SANE-instability score could be used as an alternative to the Rowe score for patient follow-up at various time points.

Clinical research associates experience with missing patient reported outcomes data in cancer randomized controlled trials

Background

Missing patient reported outcomes data threaten the validity of PRO‐specific findings and conclusions from randomized controlled trials by introducing bias due to data missing not at random. Clinical Research Associates are a largely unexplored source for informing understanding of potential causes of missing PRO data. The purpose of this qualitative research was to describe factors that influence missing PRO data, as revealed through the lived experience of CRAs.

Methods

Maximum variation sampling was used to select CRAs having a range of experiences with missing PRO data from academic or nonacademic centers in different geographic locations of Canada. Semistructured interviews were audio‐recorded, transcribed verbatim, and analyzed according to descriptive phenomenology.

Results

Eleven CRAs were interviewed. Analysis revealed several factors that influence missing PRO data that were organized within themes. PROs for routine clinical care compete with PROs for RCTs. Both the paper and electronic formats have benefits and drawbacks. Missing PRO data are influenced by characteristics of the instruments and of the patients. Assessment of PROs at progression of disease is particularly difficult. Deficiencies in center research infrastructure can contribute. CRAs develop relationships with patients that may help reduce missing PRO data. It is not always possible to provide sufficient time to complete the instrument. There is a need for field guidance and a motivation among CRAs to contribute their knowledge to address issues.

Conclusion

These results enhance understanding of factors influencing missing PRO data and have important implications for designing operational solutions to improve data quality on cancer RCTs.

Factors predicting missing instruments in three cancer randomized clinical trials

PURPOSE

Missing patient-reported outcome (PRO) data can seriously threaten the validity of randomized clinical trials (RCTs). Identifying which factors predict missing instruments may help researchers develop strategies to prevent it from happening. This study examined the association of factors with time to the first missing instrument after randomization in three cooperative group RCTs.

METHODS

We performed descriptive analyses and Cox proportional hazards regressions for three RCTs selected from the Canadian Cancer Trials Group: MA17 (breast cancer), PR7 (prostate cancer), and LY12 (non-Hodgkin's lymphoma). The outcome was the time from randomization to the first missing instrument. Variables for 15 factors were used as covariates based on availability and previously-reported putative associations with missing PRO data.

RESULTS

Nine percent of 1352 subjects on MA17, 37% of 923 subjects on PR7, and 59% of 477 subjects on LY12 had a missing instrument. Twenty-five percent of subjects on MA17 had first missing instrument within 4.6 years. The median time to first missing instrument was: not observed for MA17, 7.3 years for PR7, 0.12 years for LY12. Cox regression revealed statistically significant independent associations with outcome for only five factors: baseline age (PR7) and level of well-being (LY12), and centre level of activity (LY12), presence of post-graduate residency training program (MA17, PR7), and centre geographic location (PR7, LY12).

CONCLUSION

Many factors reported to have association with missing instruments do not seem to predict time to the first missing instrument after randomization in RCTs. Context is important in understanding the few that may.

Health-related quality-of-life assessment of patients with solid tumors on immuno-oncology therapies

Immuno-oncology therapies have been approved for various solid tumors; however, the high cost of these treatments and their potential toxicities require a thorough assessment of their risks and benefits. Collection of data directly from patients through patient-reported outcome instruments can improve the precision and reliability of adverse event detection, assess tolerability of adverse events, and provide an evaluation of health-related quality of life (HRQOL) changes from immuno-oncology therapies. There is robust development in HRQOL tools specifically for patients treated with immuno-oncology agents. This review examines the history and basic concepts of HRQOL and patient-reported outcome assessments commonly used in oncological trials, highlighting the strengths and weaknesses of current approaches when applied to immunotherapies, as well as some of the current efforts to develop tools for this field and opportunities for future research. LAY SUMMARY: Immuno-oncology (IO) therapies are costly and carry potential toxicities known as immune-related adverse events. Evaluation of health-related quality of life (HRQOL) can impact the risk-benefit assessment of IO therapies. Integration of HRQOL end points and patient-reported outcome data for IO therapies are urgently needed. Ongoing robust development of patient-reported outcome tools specific to IO therapies are currently underway and will permit the evaluation of HRQOL for IO agents. Improvement in precision and reliability of HRQOL evaluation will enhance the ultimate true value of these expensive and effective drugs.

International standards for the analysis of quality-of-life and patient-reported outcome endpoints in cancer randomised controlled trials: recommendations of the SISAQOL Consortium

Patient-reported outcomes (PROs), such as symptoms, function, and other health-related quality-of-life aspects, are increasingly evaluated in cancer randomised controlled trials (RCTs) to provide information about treatment risks, benefits, and tolerability. However, expert opinion and critical review of the literature showed no consensus on optimal methods of PRO analysis in cancer RCTs, hindering interpretation of results. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium was formed to establish PRO analysis recommendations. Four issues were prioritised: developing a taxonomy of research objectives that can be matched with appropriate statistical methods, identifying appropriate statistical methods for PRO analysis, standardising statistical terminology related to missing data, and determining appropriate ways to manage missing data. This Policy Review presents recommendations for PRO analysis developed through critical literature reviews and a structured collaborative process with diverse international stakeholders, which provides a foundation for endorsement; ongoing developments of these recommendations are also discussed.

Strategies to improve patient-reported outcome completion rates in longitudinal studies

Purpose

The quality of patient-reported outcome (PRO) data can be compromised by non-response (NR) to scheduled questionnaires, particularly if reasons for NR are related to health problems, which may lead to unintended bias. The aim was to investigate whether electronic reminders and real-time monitoring improve PRO completion rate.

Methods

The population-based study “Quality of life in Danish multiple myeloma patients” is a longitudinal, multicentre study with consecutive inclusion of treatment-demanding newly diagnosed or relapsed patients with multiple myeloma. Education of study nurses in the avoidance of NR, electronic reminders, 7-day response windows and real-time monitoring of NR were integrated in the study. Patients complete PRO assessments at study entry and at 12 follow-up time points using electronic or paper questionnaires. The effect of the electronic reminders and real-time monitoring were investigated by comparison of proportions of completed questionnaires before and after each intervention.

Results

The first 271 included patients were analysed; of those, 249 (85%) chose electronic questionnaires. Eighty-four percent of the 1441 scheduled PRO assessments were completed within the 7-day response window and 11% after real-time monitoring, achieving a final PRO completion rate of 95%. A significant higher proportion of uncompleted questionnaires were completed after the patients had received the electronic reminder and after real-time monitoring.

Conclusions

Electronic reminders and real-time monitoring contributed to a very high completion rate in the study. To increase the quality of PRO data, we propose integrating these strategies in PRO studies, however highlighting that an increase in staff resources is required for implementation.

Methodological aspects of health-related quality of life measurement and analysis in patients with multiple myeloma

Multiple myeloma (MM) is an incurable but treatment-sensitive cancer. For most patients, this means treatment with multiple lines of anti-myeloma therapy and a life with disease- and treatment-related symptoms and complications. Health-related quality of life (HRQoL) issues play an important role in treatment decision-making. Methodological challenges in longitudinal HRQoL measurements and analyses have been identified, including non-responses (NR) to scheduled questionnaires. Publications were identified for inclusion in a systematic review of longitudinal HRQoL studies in MM, focussing on methodological aspects of HRQoL measurement and analysis. Diversity in timing of HRQoL data collection and applied statistical methods were noted. We observed a high rate of NR, but the impact of NR was investigated in only 8/23 studies. Thus, evidence-based knowledge of HRQoL in patients with MM is compromised. To improve quality of HRQoL results and their implementation in daily practice, future studies should follow established guidelines.

The importance of patient-reported outcomes in clinical trials and strategies for future optimization

Patient-reported outcomes (PROs) can be included in clinical trials as primary or secondary endpoints and are increasingly recognized by regulators, clinicians, and patients as valuable tools to collect patient-centered data. PROs provide unique information on the impact of a medical condition and its treatment from the patient's perspective; therefore, PROs can be included in clinical trials to ensure the impact of a trial intervention is comprehensively assessed. This review first discusses examples of how PRO endpoints have added value to clinical trial interpretation. Second, it describes the problems with current practices in designing, implementing, and reporting PRO studies, and how these problems may be addressed by complying with guidance for protocol development, selecting appropriate PRO measures to match clinically motivated PRO hypotheses, minimizing the rates of avoidable missing PRO data, analyzing and interpreting PRO data, and transparently reporting PRO findings.