Quality of missing data reporting and handling in palliative care trials demonstrates that further development of the CONSORT statement is required: a systematic review.

OBJECTIVES: Assess (i) the quality of reporting and handling of missing data (MD) in palliative care trials, (ii) whether there are differences in the reporting of criteria specified by the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement compared with those not specified, and (iii) the association of the reporting of MD with journal impact factor and CONSORT endorsement status. STUDY DESIGN AND SETTING: Systematic review of palliative care randomized controlled trials. CENTRAL, MEDLINE, and EMBASE (2009-2014) were searched. RESULTS: One hundred and eight trials (15,560 participants) were included. MD was incompletely reported and not handled in accordance with current guidance. Reporting criteria specified by the CONSORT statement were better reported than those not specified (participant flow, 69%; number of participants not included in the primary outcome analysis, 94%; and the reason for MD, 71%). However, MD in items contributing to scale summaries (10%) and secondary outcomes (9%) were poorly reported, so the proportion of MD stated is likely to be an underestimate. The reason for MD provided was unclear for 54% of participants and only 16% of trials with MD reported a MD sensitivity analysis. The odds of reporting most of the MD and other risk of bias reporting criteria were increased as the journal impact factor increased and in journals that endorsed the CONSORT statement. CONCLUSION: Further development of the CONSORT MD reporting guidance is likely to improve the quality of reporting. Reporting recommendations are provided

Patient and health care professional decision-making to commence and withdraw from renal dialysis: A systematic review of qualitative research

Background and objectives. To ensure decisions to start and stop dialysis in end stage kidney disease are shared, the factors that affect patients and healthcare professionals in making such decisions need to be understood. This systematic review aims to explore how and why different factors mediate the choices about dialysis treatment. Design, setting, participants, and measurements. Medline, Embase, CINAHL and PsychINFO were searched for qualitative studies of factors that affect patients’ and/or healthcare professionals’ decisions to commence or withdraw from dialysis. A thematic synthesis was conducted. Results. Of 494 articles screened, 12 studies (conducted: 1985-2014) were included. These involved 206 predominantly haemodialysis patients and 64 healthcare professionals (age range: patients 26-93; professionals 26-61 years). (i) Commencing dialysis: patients based their choice on ‘gut-instinct’ as well as deliberating the impact of treatment on quality-of-life and survival. How individuals coped with decision-making was influential, some tried to take control of the problem of progressive renal failure, whilst others focussed on controlling their emotions. Healthcare professionals weighed-up biomedical factors and were led by an instinct to prolong life. Both patients and healthcare professionals described feeling powerless. (ii) Dialysis withdrawal: Only after prolonged periods of time on dialysis, were the realities of life on dialysis fully appreciated and past choice questioned. By this stage however patients were physically treatment dependent. Similar to commencing dialysis, individuals coped with treatment withdrawal in a problem or emotion-controlling way. Families struggled to differentiate choosing versus allowing death. Healthcare teams avoided and queried discussions regarding dialysis withdrawal. Patients however missed the dialogue they experienced during pre-dialysis education. Conclusions. Decision-making in end stage kidney disease is complex, dynamic, and evolves over time and towards death. The factors at work are multi-faceted and operate differently for patients and health professionals. More training and research on open-communication and shared decision-making is needed

Missing data in randomized controlled trials testing palliative interventions pose a significant risk of bias and loss of power: a systematic review and meta-analyses

Objectives To assess the risk posed by missing data (MD) to the power and validity of trials evaluating palliative interventions. Study Design and Setting A systematic review of MD in published randomized controlled trials (RCTs) of palliative interventions in participants with life-limiting illnesses was conducted, and random-effects meta-analyses and metaregression were performed. CENTRAL, MEDLINE, and EMBASE (2009-2014) were searched with no language restrictions. Results One hundred and eight RCTs representing 15,560 patients were included. The weighted estimate for MD at the primary endpoint was 23.1% (95% confidence interval [CI] 19.3, 27.4). Larger MD proportions were associated with increasing numbers of questions/tests requested (odds ratio [OR] , 1.19; 95% CI 1.05, 1.35) and with longer study duration (OR, 1.09; 95% CI 1.02, 1.17). Meta-analysis found evidence of differential rates of MD between trial arms, which varied in direction (OR, 1.04; 95% CI 0.90, 1.20; I 2 35.9, P = 0.001). Despite randomization, MD in the intervention arms (vs. control) were more likely to be attributed to disease progression unrelated to the intervention (OR, 1.31; 95% CI 1.02, 1.69). This was not the case for MD due to death (OR, 0.92; 95% CI 0.78, 1.08). Conclusion The overall proportion and differential rates and reasons for MD reduce the power and potentially introduce bias to palliative care trials

Development of guidelines to reduce, handle and report missing data in palliative care trials: A multi-stakeholder modified nominal group technique

Background: Missing data can introduce bias and reduce the power, precision and generalisability of study findings. Guidelines on how to address missing data are limited in scope and detail, and poorly implemented. Aim: To develop guidelines on how best to (i) reduce, (ii) handle and (iii) report missing data in palliative care clinical trials. Design: Modified nominal group technique. Setting/participants: Patient and public research partners, palliative care clinicians, trialists, methodologists and statisticians attended a 1-day workshop, following which a multi-stakeholder development group drafted the guidelines. Results: Seven main recommendations for reducing missing data, nine for handling missing data and twelve for reporting missing data were developed. The top five recommendations were: (i) train all research staff on missing data, (ii) prepare for missing data at the trial design stage, (iii) address missing data in the statistical analysis plan, (iv) collect the reasons for missing data and (v) report descriptive statistics comparing the baseline characteristics of those with missing and observed data. Reducing missing data, preparing for missing data and understanding the reasons for missing data were greater priorities for stakeholders than how to deal with missing data once they had occurred. Conclusion: Comprehensive guidelines on how to address missing data were developed by stakeholders involved in palliative care trials. Implementation of the guidelines will require endorsement of research funders and research journals

Intention-to-treat analyses for randomised controlled trials in hospice/palliative care: the case for analyses to be of people exposed to the intervention.

© 2019 American Academy of Hospice and Palliative Medicine Context: Minimizing bias in randomized controlled trials (RCTs) includes intention-to-treat analyses. Hospice/palliative care RCTs are constrained by high attrition unpredictable when consenting, including withdrawals between randomization and first exposure to the intervention. Such withdrawals may systematically bias findings away from the new intervention being evaluated if they are considered nonresponders. Objectives: This study aimed to quantify the impact within intention-to-treat principles. Methods: A theoretical model was developed to assess the impact of withdrawals between randomization and first exposure on study power and effect sizes. Ten reported hospice/palliative care studies had power recalculated accounting for such withdrawal. Results: In the theoretical model, when 5% of withdrawals occurred between randomization and first exposure to the intervention, change in power was demonstrated in binary outcomes (2.0%–2.2%), continuous outcomes (0.8%–2.0%), and time-to-event outcomes (1.6%–2.0%), and odds ratios were changed by 0.06–0.17. Greater power loss was observed with larger effect sizes. Withdrawal rates were 0.9%–10% in the 10 reported RCTs, corresponding to power losses of 0.1%–2.2%. For studies with binary outcomes, withdrawal rates were 0.3%–1.2% changing odds ratios by 0.01–0.22. Conclusion: If blinding is maintained and all interventions are available simultaneously, our model suggests that excluding data from withdrawals between randomization and first exposure to the intervention minimizes one bias. This is the safety population as defined by the International Committee on Harmonization. When planning for future trials, minimizing the time between randomization and first exposure to the intervention will minimize the problem. Power should be calculated on people who receive the intervention

How to appraise a qualitative study

Qualitative research is increasingly being published in medical journals to explore important clinical questions. Methods, vocabulary and theoretical underpinnings may be unfamiliar to some doctors. This article explores an approach to understanding qualitative studies. </jats:p

How to appraise a systematic review

Systematic reviews are a vital tool in evidence-based practice, allowing a comprehensive synthesis of research evidence. This article provides guidance for appraising systematic reviews and resources for more detailed assessments