Missing Patient Reported Outcome Data Research Articles

Fixing the Leaky Pipe: How to Improve the Uptake of Patient-Reported Outcomes-Based Prognostic and Predictive Models in Cancer Clinical Practice.

This discussion paper outlines challenges and proposes solutions for successfully implementing prediction models that incorporate patient-reported outcomes (PROs) in cancer practice. We organized a full-day multidisciplinary meeting of people with expertise in cancer care delivery, PRO collection, PRO use in prediction modeling, computing, implementation, and decision science. The discussions presented here focused on identifying challenges to the development, implementation and use of prediction models incorporating PROs, and suggesting possible solutions. Specific challenges and solutions were identified across three broad areas. (1) Understanding decision making and implementation: necessitating multidisciplinary collaboration in the early stages and throughout; early stakeholder engagement to define the decision problem and ensure acceptability of PROs in prediction; understanding patient/clinician interpretation of PRO predictions and uncertainty to optimize prediction impact; striving for model integration into existing electronic health records; and early regulatory alignment. (2) Recognizing the limitations to PRO collection and their impact on prediction: incorporating validated, clinically important PROs to maximize model generalizability and clinical engagement; and minimizing missing PRO data (resulting from both structural digital exclusion and time-varying factors) to avoid exacerbating existing inequalities. (3) Statistical and modeling challenges: incorporating statistical methods to address missing data; ensuring predictive modeling recognizes complex causal relationships; and considering temporal and geographic recalibration so that model predictions reflect the relevant population. Developing and implementing PRO-based prediction models in cancer care requires extensive multidisciplinary working from the earliest stages, recognition of implementation challenges because of PRO collection and model presentation, and robust statistical methods to manage missing data, causality, and calibration. Prediction models incorporating PROs should be viewed as complex interventions, with their development and impact assessment carried out to reflect this.

MSR19 Missing Patient Reported Outcome Data in Clinical Trials: An Overview and Simulation Study

Missing data occur in clinical trials and can have a negative impact on the results. In this study, we (1) outlined concepts related to missing patient reported outcomes (PRO) data, including patterns of missingness, missing data types (missing completely at random [MCAR], missing at random [MAR], missing not at random [MNAR]), and commonly used analytic strategies that address missingness (multiple imputation [MI], mixed model repeated measures [MMRM]), and (2) investigated the potential impact of missing data on PRO results in clinical trial settings.

Using Patient-Reported Outcomes in Dose-Finding Oncology Trials: Surveys of Key Stakeholders and the National Cancer Research Institute Consumer Forum.

BackgroundPatient-reported adverse events may be a useful adjunct for assessing a drug’s tolerability in dose-finding oncology trials (DFOT). We conducted surveys of international stakeholders and the National Cancer Research Institute (NCRI) Consumer Forum to understand attitudes about patient-reported outcome (PRO) use in DFOT.MethodsA 35-question survey of clinicians, trial managers, statisticians, funders, and regulators of DFOT was distributed via professional bodies examining experience using PROs, benefits/barriers, and their potential role in defining tolerable doses. An 8-question survey of the NCRI Consumer Forum explored similar themes.Results International survey: 112 responses from 15 September–30 November 2020; 103 trialists [48 clinicians (42.9%), 38 statisticians (34.0%), 17 trial managers (15.2%)], 7 regulators (6.3%), 2 funders (1.8%)]. Most trialists had no experience designing (73, 70.9%), conducting (52, 50.5%), or reporting (88, 85.4%) PROs in DFOT. Most agreed that PROs could identify new toxicities (75, 67.0%) and provide data on the frequency (86, 76.8%) and duration (81, 72.3%) of toxicities. The top 3 barriers were lack of guidance regarding PRO selection (73/103, 70.9%), missing PRO data (71/103, 68.9%), and overburdening staff (68/103, 66.0%). NCRI survey: 57 responses on 21 March 2021. A total of 28 (49.1%) were willing to spend <15 min/day completing PROs. Most (55, 96.5%) preferred to complete PROs online. 61 (54.5%) trialists and 57 (100%) consumers agreed that patient-reported adverse events should be used to inform dose-escalation decisions.ConclusionStakeholders reported minimal experience using PROs in DFOT but broadly supported their use. Guidelines are needed to standardize PRO selection, analysis, and reporting in DFOT.

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

BackgroundMissing 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.MethodsMaximum 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.ResultsEleven 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.ConclusionThese 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.

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. 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. 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 4.6years. The median time to first missing instrument was: not observed for MA17, 7.3years for PR7, 0.12years 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). 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.

Under-Reporting of Patient-Reported Outcome in Hematological Malignancies Trials

Introduction: Patient-reported outcomes (PRO) provide meaningful insight into patient perspectives on treatment effect. Clinically relevant outcomes such as improvements in overall survival (OS) and quality of life (QOL) should guide clinical decision-making, furthermore, the FDA encourages the implementation of patient-centric PRO measures in clinical trials. Objectives: To evaluate the frequency at which PRO measures included in clinical trials, are made publicly available when trial results are published. Methods: We searched Citeline® Trialtrove database, a registry of clinical trials, for randomized phase 2/3 and 3 clinical trials evaluating patients with hematological malignancies, completing enrollment between the years 2007-2017, for which PRO endpoints were listed. We excluded trials evaluating supportive care. We recorded the following data: indication, treatment and comparator, phase, primary endpoint, type of scale or questionnaire used for PRO endpoint. We then identified all available publications associated with the trial, and recorded type of publication (abstract or full text), year, reported outcomes, and 13 criteria of CONSORT-PRO that reflect the completeness of reporting. Results: We identified 362 trials through our search. 53 trials were listed as including at least one PRO endpoint, of which 8 were never published. Indications are listed in Table. PRO endpoints were assessed utilizing 26 PRO different tools, 7 were disease specific, 2 were treatment specific. PRO was the primary outcome in two trials. EORTC-QLQ-30 was most frequently used tool. Study sponsor was industry-only in 21 trials, industry-academic in six, and academic in 18. Of the 45 trials analyzed, only 19 (42%) published any PRO data. Eleven of all trials (24%) were judged as comprehensively reporting PRO. The median number of CONSORT-PRO quality indicators was eight criteria. Of the 45 trials, 12 provided information about missing PRO data. Of the 15 trials that showed PFS benefit with no OS benefit, 8(53%) did not publish any results the PRO, to support a patient centric outcome. 36 of the trials were published as full-text, and nine as abstract. In considering the 36 full text publications, 17 (47%) did not report any PRO. Nine of the full-text publications, reported PRO as part of the primary publication or within the following 6 months. Conclusions: Despite a growing emphasis on QOL and use of PROs in oncology clinical trials, and despite patient and health provider efforts to record PRO data, most hematologic malignancies randomized trials still do not report the PRO endpoints. In several cases they were published later and in a partial manner, minimizing their impact on treatment decisions. This may indicate a disregard to PRO data collected, incomplete collection or methodological flaws in data analysis. Regardless of the reason, PRO data should be routinely included in study publications to allow for a complete assessment of investigational treatment outcome - including disease related outcomes, as well as those reported by the patients themselves. Disclosures No relevant conflicts of interest to declare.

Patient-Reported Outcome Results from the U.S. Life after Stopping TKIs (LAST) Study in Patients with Chronic Myeloid Leukemia

Patient-Reported Outcome Results from the U.S. Life after Stopping TKIs (LAST) Study in Patients with Chronic Myeloid Leukemia

Patient-reported outcomes in randomised clinical trials of bladder cancer: an updated systematic review

BackgroundDespite international recommendations of including patient-reported outcomes (PROs) in randomised clinical trials (RCTs), a 2014 review concluded that few RCTs of bladder cancer (BC) report PRO as an outcome. We therefore aimed to update the 2014 review to synthesise current evidence-based knowledge of PROs from RCTs in BC. A secondary objective was to examine whether quality of PRO reporting has improved over time and to provide evidence-based recommendations for future studies in this area.MethodsWe conducted a systematic literature search using PubMed/Medline, from April 2014 until June 2018. We included the RCTs identified in the previous review as well as newly published RCTs. Studies were evaluated using a predefined electronic-data extraction form that included information on basic trial demographics, clinical and PRO characteristics and standards of PRO reporting based on recommendation from the International Society of Quality of Life Research.ResultsSince April 2014 only eight new RCTs for BC included PROs as a secondary outcome. In terms of methodology, only the proportion of RCTs documenting the extent of missing PRO data (75% vs 11.1%, p = 0.03) and the identification of PROs in trial protocols (50% vs 0%, p = 0.015) improved. Statistical approaches for dealing with missing data were not reported in most new studies (75%).ConclusionLittle improvement into the uptake and assessment of PRO as an outcome in RCTs for BC has been made during recent years. Given the increase in (immunotherapy) drug trials with a potential for severe adverse events, there is urgent need to adopt the recommendations and standards available for PRO use in bladder cancer RCTs.

Patient Demographic and Surgical Factors that Affect Completion of Patient-Reported Outcomes 90 Days and 1 Year After Spine Surgery: Analysis from the Michigan Spine Surgery Improvement Collaborative (MSSIC)

The Michigan Spine Surgery Improvement Collaborative is a statewide multicenter quality improvement registry. Because missing data can affect registry results, we used MSSIC to find demographic and surgical characteristics that affect the completion of patient-reported outcomes (PROs) at 90 days and 1 year. A total of 24,404 patients who had lumbar surgery (17,813 patients) or cervical surgery (6591 patients) were included. Multivariate logistic regression models of patient disease were constructed to identify risk factors for failure to complete scheduled PRO surveys. Patients ≥65 years old and female patients were both more likely to respond at 90 days and 1 year. Increasing education was associated with greater response rate at 90 days and 1 year. Whites and African Americans had no differences in response rates. Calling provided the highest response rate at 90 days and 1 year. For cervical spine patients, only discharge to rehabilitation increased completion rates, at 90 days but not 1 year. For lumbar spine patients, spondylolisthesis or stenosis (vs. herniated disc) had a greater response rate at 1 year. Patients with leg (vs. back) pain had a greater response only at 1 year. Patients with multilevel surgery had an increased response at 1 year. Patients who underwent fusion were more likely to respond at 90 days, but not 1 year. Discharge to rehabilitation increased response at 90 days and 1 year. A multivariate analysis from a multicenter prospective database identified surgical factors that affect PRO follow-up, up to 1 year. This information can be helpful for imputing missing PRO data and could be used to strengthen data derived from large prospective databases.

Reporting of patient reported outcome (PRO) in clinical trials: A systematic review of clinical trials.

6590 Background: Clinically relevant outcomes as improvements in overall survival (OS) or quality of life (QOL) should guide decision-making. The FDA encourages the implementation of patient-centric measures in clinical trials. Over the past decade a growing number of protocols have included PROs in their outcome measures. We aimed to evaluate the frequency at which PRO measures, incorporated into clinical trials, are made publicly available, when trial results are published. Methods: We searched Citeline Trialtrove database, a registry of clinical trials, for randomized phase 3 trials of patients with non-small cell lung cancer (NSCLC), recruiting during 2006-2016, with PRO listed. We excluded trials evaluating supportive treatment, and those unpublished. We identified publications associated with the trial, and extracted various parameters, including whether or not PRO outcome was published. Results: Of 158 NSCLC trials identified, 99 listed at least 1 PRO. 24 trials were excluded (supportive care, unpublished). The commonly used scales were EORTC-QLQ C30, QLQ-LC13, LCSS, FACT-L, and EQ-5D. Study sponsor was industry in 45 trials, and industry-academic in 12 trials. Of 75 trials analyzed, 41 (55%) published the results of the PRO endpoint. Only 37% of the 75 included a comprehensive report of PRO, and many publications referenced the PRO briefly. Of 41 trials that reported PRO, only 21 (51%) provided information about missing PRO data. 59 trials were published as full-text, of which 40 (68%) reported the PRO, and 53% reported the PRO more than 6 months after the initial full publication. Of the trials that showed PFS benefit, with no OS benefit, 22/34 (65%) published the results of the PRO endpoints. Conclusions: Despite a growing emphasis on QOL and the inclusion of PROs in oncology clinical trials, and despite patient and healthcare provider efforts to record PRO data, a significant number of NSCLC randomized trials do not report the PRO. The collection of PRO data should result in routine, timely and appropriate reporting as part of the trial outcome publication, to allow for a thorough assessment of investigational clinically relevant treatment effect.

Analytical approaches and estimands to take account of missing patient-reported data in longitudinal studies.

Patient-reported outcomes, such as quality of life, functioning, and symptoms, are used widely in therapeutic and behavioral trials and are increasingly used in drug development to represent the patient voice. Missing patient reported data is common and can undermine the validity of results reporting by reducing power, biasing estimates, and ultimately reducing confidence in the results. In this paper, we review statistically principled approaches for handling missing patient-reported outcome data and introduce the idea of estimands in the context of behavioral trials. Specifically, we outline a plan that considers missing data at each stage of research: design, data collection, analysis, and reporting. The design stage includes processes to prevent missing data, define the estimand, and specify primary and sensitivity analyses. The analytic strategy considering missing data depends on the estimand. Reviewed approaches include maximum likelihood-based models, multiple imputation, generalized estimating equations, and responder analysis. We outline sensitivity analyses to assess the robustness of the primary analysis results when data are missing. We also describe ad-hoc methods, including approaches to avoid. Last, we demonstrate methods using data from a behavioral intervention, where the primary outcome was self-reported cognition.

Preoperative Patient-Reported Outcomes and Clinical Characteristics as Predictors of 90-Day Cost/Utilization and Complications

BackgroundWith the advent of mandatory bundle payments for total joint arthroplasty (TJA), assessing patients’ risk for increased 90-day complications and resource utilization is crucial. This study assesses the degree to which preoperative patient-reported outcomes predict 90-day complications, episode costs, and utilization in TJA patients. MethodsAll TJA cases in 2017 at 2 high-volume hospitals were queried. Preoperative HOOS/KOOS JR (Hip Injury and Osteoarthritis Outcome Score/Knee Injury and Osteoarthritis Outcome Score) and Veterans RAND 12-item health survey (VR-12) were administered to patients preoperatively via e-collection platform. For patients enrolled in the Medicare bundle, cost data were extracted from claims. Bivariate and multivariate regression analyses were performed. ResultsIn total, 2108 patients underwent TJA in 2017; 1182 (56%) were missing patient-reported outcome data and were excluded. The final study population included 926 patients, 199 (21%) of which had available cost data. Patients with high bundle costs tended to be older, suffer from vascular disease and anemia, and have higher Charlson scores (P < .05 for all). These patients also had lower baseline VR-12 Physical Component Summary Score (PCS; 24 vs 30, P ≤ .001) and higher rates of extended length of stay, skilled nursing facility discharge, 90-day complications, and 90-day readmission (P ≤ .04 for all). In multivariate analysis, higher baseline VR-12 PCS was protective against extended length of stay, skilled nursing facility discharge, >75th percentile bundle cost, and 90-day bundle cost exceeding target bundle price (P < .01 for all). Baseline VR-12 Mental Component Summary Score and HOOS/KOOS JR were not predictive of complications or bundle cost. ConclusionLow baseline VR-12 PCS is predictive of high 90-day bundle costs. Baseline HOOS/KOOS JR scores were not predictive of utilization or cost. Neither VR-12 nor HOOS/KOOS JR was predictive of 90-day readmission or complications.

A Review of Patient-Reported Outcomes Labeling for Oncology Drugs Approved by the FDA and the EMA (2012-2016)

ObjectivesTo compare US Food and Drug Administration (FDA) and European Medicines Agency (EMA) labeling for evidence based on patient-reported outcomes (PROs) of new oncology treatments approved by both agencies. MethodsOncology drugs and indications approved between 2012 and 2016 by both the FDA and the EMA were identified. PRO-related language and analysis reported in US product labels and drug approval packages and EMA summaries of product characteristics were compared for each indication. ResultsIn total, 49 oncology drugs were approved for a total of 64 indications. Of the 64 indications, 45 (70.3%) included PRO data in either regulatory submission. No FDA PRO labeling was identified. PRO language was included in the summary of product characteristics for 21 (46.7%) of 45 indications. European Organisation for Research and Treatment of Cancer and Functional Assessment of Cancer Therapy measures were used frequently in submissions. FDA’s comments suggest that aspects of study design (eg, open labels) or the validity of PRO measures was the primary reason for the lack of labeling based on PRO endpoints. Both agencies identified missing PRO data as problematic for interpretation. ConclusionsDuring this time period, the FDA and the EMA used different evidentiary standards to assess PRO data from oncology studies, with the EMA more likely to accept data from open-label studies and broad concepts such as health-related quality of life. An understanding of the key differences between the agencies may guide sponsor PRO strategy when pursuing labeling. Patient-focused proximal concepts are more likely than distal concepts to receive positive reviews.

Under-Reporting of Patient Reported Outcome (PRO) in Clinical Trials

Introduction: Clinically relevant outcomes as improvements in overall survival (OS) or quality of life (QOL) should guide decision-making. The FDA encourages the implementation of patient-centric PRO measures in clinical trials. In the recent decade there have been a growing number of protocols including PROs in their outcome measures, and an increase in pre-market submissions including those measures. We aimed to evaluate the frequency at which PRO measures, incorporated into clinical trials, are made publicly available, when trial results are published.Methods: We searched Citeline® Trialtrove database, a registry of clinical trials, for randomized phase 2/3 and 3 clinical trials including patients with chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma (NHL), initiated between the years 2005-2015, with PRO endpoints listed. We excluded trials involving patients with acute leukemia or involving stem cell transplantation. For these trials we recorded the following data: indication, treatment and comparator, phase, primary endpoint, type of scale or questionnaire used for PRO endpoint. We then identified all available publications associated with the trial, and recoded type of publication (abstract or full text), year, number of randomized patients, reported outcomes.Results: 120 CLL and NHL trials were identified through our search. 44 trials (23 CLL, 21 NHL) were listed with at least one PRO endpoint. Eleven trials were excluded (1 extension of an included trial, 4 not completed, 4 not published, 2 cancelled with little or no recruitment). PRO endpoints were assessed utilizing - EORTC-QLQ30 QoL, QLQ-CLL16, FACIT-fatigue, FACT-leu, FACT-lym, EQ-5D, Skindex-29, and Rituximab Administration Satisfaction Questionnaire as relevant per indication. PRO was the primary outcome in two trials, and secondary in the other 31. Study sponsor was industry-only in 27 trials, and industry-academic in five. Of the 33 trials analyzed, 14 (42%) published results of the PRO endpoint - 6/17 (35%) of CLL trials, and 8/16 (50%) of NHL trials. 26/33 of the trials were published as full-text, 6/33 as abstract, and 1 published on clinicaltrials.gov. Of the 26 full text publications, 12 (46%) reported PRO. In 8 of full-text PRO were reported as part of the primary publication or published within 6 months. Nine of all trials provided a comprehensive report of PRO endpoints. Of the 33 trials, only 2 provided information about missing PRO data. 54% of trials in which primary endpoint was reached, and 12.5% of trials in which it was not reached, were published listing PRO results. Of the trials that showed PFS benefit, with no OS benefit, 9/15 (60%) published the results of the PRO endpoints.Conclusions: Despite a growing emphasis on QOL and use of PROs in oncology clinical trials, and despite patient and health provider efforts to record PRO data, most CLL and NHL randomized trials still do not report the PRO endpoints. In several cases they were published later and in a partial manner, minimizing their impact on treatment decisions. This may indicate a disregard to PRO data collected, incomplete collection or methodological flaws in data analysis. Regardless of the reason, PRO data should be routinely included in study publications to allow for a complete assessment of investigational treatment outcome - including disease related outcomes, as well as those reported by the patients themselves. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

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.

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

Missing patient-reported outcome data can lead to biased results, to loss of power to detect between-treatment differences, and to research waste. Awareness of factors may help researchers reduce missing patient-reported outcome data through study design and trial processes. The aim was to construct a Classification Framework of factors associated with missing patient-reported outcome data in the context of comparative studies. The first step in this process was informed by a systematic review. Two databases (MEDLINE and CINAHL) were searched from inception to March 2015 for English articles. Inclusion criteria were (a) relevant to patient-reported outcomes, (b) discussed missing data or compliance in prospective medical studies, and (c) examined predictors or causes of missing data, including reasons identified in actual trial datasets and reported on cover sheets. Two reviewers independently screened titles and abstracts. Discrepancies were discussed with the research team prior to finalizing the list of eligible papers. In completing the systematic review, four particular challenges to synthesizing the extracted information were identified. To address these challenges, operational principles were established by consensus to guide the development of the Classification Framework. A total of 6027 records were screened. In all, 100 papers were eligible and included in the review. Of these, 57% focused on cancer, 23% did not specify disease, and 20% reported for patients with a variety of non-cancer conditions. In total, 40% of the papers offered a descriptive analysis of possible factors associated with missing data, but some papers used other methods. In total, 663 excerpts of text (units), each describing a factor associated with missing patient-reported outcome data, were extracted verbatim. Redundant units were identified and sequestered. Similar units were grouped, and an iterative process of consensus among the investigators was used to reduce these units to a list of factors that met the guiding principles. The list was organized on a framework, using an iterative consensus-based process. The resultant Classification Framework is a summary of the factors associated with missing patient-reported outcome data described in the literature. It consists of 5 components (instrument, participant, centre, staff, and study) and 46 categories, each with one or more sub-categories or examples. A systematic review of the literature revealed 46 unique categories of factors associated with missing patient-reported outcome data, organized into 5 main component groups. The Classification Framework may assist researchers to improve the design of new randomized clinical trials and to implement procedures to reduce missing patient-reported outcome data. Further research using the Classification Framework to inform quantitative analyses of missing patient-reported outcome data in existing clinical trials and to inform qualitative inquiry of research staff is planned.

A systematic evaluation of compliance and reporting of patient-reported outcome endpoints in ovarian cancer randomised controlled trials: implications for generalisability and clinical practice

BackgroundThis study aimed to evaluate the patient-reported outcome (PRO) content of ovarian cancer randomised-controlled trial (RCT) publications, describe PRO compliance, and explore potential relationships among these and completeness of PRO protocol content.MethodsPublications of Phase III ovarian cancer RCTs with PRO endpoints were identified by Medline and Cochrane systematic search: January 2000 to February 2016. Two reviewers determined the number of Consolidated Standards of Reporting Trials (CONSORT)-PRO Extension items addressed in publications. Compliance rates (defined as the proportion of participants included in the principal PRO analysis, of those from whom PRO assessments were expected) were extracted. The relationship between CONSORT-PRO score and compliance rates was explored using scatter plots. Additionally CONSORT-PRO score and PRO compliance rates respectively were compared with corresponding PRO protocol scores obtained from a previous study.ResultsThirty-six eligible RCTs (n = 33 with secondary PRO endpoint) were identified and analysed. The average number of CONSORT-PRO items addressed in publications was 6.7 (48%; Range 0–13.5/14). Three RCTs did not report PRO results; in 1 case due to poor compliance. Some compliance information was reported in 26 RCTs, but was considered complete for only 10 (28%) RCTs. Compliance rates were poor overall, ranging from 59 to 83%; therefore missing PRO data from 17 to 41% of participants in these trials could have been avoided.Of the 26 (73%) RCTs for which PRO protocol completeness scores were available, 6 RCTs reported complete compliance information and the 3 of these RCTs with highest PRO compliance had highest protocol checklist scores.ConclusionsFew RCTs reported PRO compliance information in a manner enabling assessment of the generalisability of PRO results. This information is particularly important in RCTs of advanced ovarian cancer because it is important to be able to determine if missing data was due to worsening illness compared to methodological issues. Poor compliance appeared related to poor PRO protocol content, and in one case prevented PRO results from being reported, highlighting the need to address compliance strategies in the protocol. Adhering to protocol and CONSORT-PRO reporting guidance should improve PRO implementation and reporting respectively in ovarian cancer RCTs and allow results to meaningfully inform clinical practice.

Current practices in patient-reported outcome (PRO) data collection in clinical trials: a cross-sectional survey of UK trial staff and management.

ObjectivesPatient-reported outcome measures (PROMs) collected in clinical trials should be administered in a standardised way across sites and routinely screened for avoidable missing data in order to maximise data quality/minimise risk of bias. Recent qualitative findings, however, have raised concerns about the consistency of PROM administration in UK trials. The purpose of this study was to determine the generalisability of these findings across the wider community of trial personnel.DesignOnline cross-sectional survey.SettingParticipants were recruited from 55 UK Clinical Research Collaboration Registered Clinical Trials Units and 19 Comprehensive Local Research Networks.ParticipantsResearch nurses, data managers/coordinators, trial managers and chief/principal investigators involved in clinical trials collecting PROMs.AnalysisWe undertook descriptive analyses of the quantitative data and directed thematic analysis of free-text comments. Factors associated with the management of missing PRO data were explored using logistic regression.ResultsSurvey data from 767 respondents supported the generalisability of qualitative study findings, suggesting inconsistencies in PROM administration with regard to: the level of assistance given to trial participants; the timing of PROM completion in relation to the clinical consultation; and the management of missing data. Having ≥10 years experience in a research role was significantly associated with the appropriate management of missing PROM data (OR 2.26 (95% CI 1.06 to 4.82), p=0.035). There was a consensus that more PROM guidance was needed in future trials and agreement between professional groups about the necessary components.ConclusionsThere are inconsistencies in the way PROMs are administered by trial staff. Such inconsistencies may reduce the quality of data and have the potential to introduce bias. There is a need for improved guidance in future trials that support trial personnel in conducting optimal PROM data collection to inform patient care.

Ovarian cancer study dropouts had worse health-related quality of life and psychosocial symptoms at baseline and over time.

Participant drop out is a major barrier to high-quality patient-reported outcome (PRO) data analysis in cancer research as patients with worsening health are more likely to dropout. To test the hypothesis that ovarian cancer patients with worse PROs would drop out earlier, we examined how patients differed by time of dropout on health-related quality of life (HRQOL), anxiety, depression, optimism and insomnia. This analysis included 619 participants, stratified by time of dropout, from the Australian Ovarian Cancer Study - Quality of Life substudy, in which participants completed PRO questionnaires at three-monthly intervals for 21 months. Trends in PROs over time were examined. Pearson correlations examined the relationship between time of dropout and baseline PROs. Multiple linear regression models including age, disease stage and time since diagnosis examined relationships between baseline and final PRO scores, and final PRO scores and dropout group. Participants who dropped out earlier had significantly worse baseline HRQOL (p<0.0001) and higher depression (p<0.0001). For all five PROs, final scores were significantly associated with baseline scores (p<0.0001). Time of dropout was significantly associated with final HRQOL (p=0.003), anxiety (p=0.05), depression (p=0.02) and optimism (p=0.02) scores. Depression, HRQOL and anxiety worsened at a faster rate overtime in dropouts than study completers. Poorer HRQOL and higher depression at baseline, and final HRQOL, anxiety, depression and optimism scores were predictive of time of dropout. These results highlight the importance of collecting auxiliary data to inform careful and considered handling of missing PRO data during analysis, interpretation and reporting.

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review

ObjectivesPatient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed...