Predicting future outcomes of patients is essential to clinical practice, with many prediction models published each year. Empirical evidence suggests that published studies often have severe methodological limitations, which undermine their usefulness. This article presents a step-by-step guide to help researchers develop and evaluate a clinical prediction model. The guide covers best practices in defining the aim and users, selecting data sources, addressing missing data, exploring alternative modelling options, and assessing model performance. The steps are illustrated using an example from relapsing-remitting multiple sclerosis. Comprehensive R code is also provided.

Individual participant data (IPD) meta‐analysis is an increasingly used approach for synthesizing and investigating treatment effect estimates. Over the past few years, numerous methods for conducting an IPD meta‐analysis (IPD‐MA) have been proposed, often making different assumptions and modeling choices while addressing a similar research question. We conducted a literature review to provide an overview of methods for performing an IPD‐MA using evidence from clinical trials or non‐randomized studies when investigating treatment efficacy. With this review, we aim to assist researchers in choosing the appropriate methods and provide recommendations on their implementation when planning and conducting an IPD‐MA. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Objective Meta-analysing studies with low event rates is challenging as some of the standard methods for meta-analysis are not well suited to handle rare outcomes. This is more evident when some studies have zero events in one or both treatment groups. In this article, we discuss why rare events require special attention in meta-analysis, we present an overview of some approaches suitable for meta-analysing rare events and we provide practical recommendations for their use. Methods We go through several models suggested in the literature for performing a rare events meta-analysis, highlighting their respective advantages and limitations. We illustrate these models using a published example from mental health. We provide the software code needed to perform all analyses in the appendix. Results Different methods may give different results, and using a suboptimal approach may lead to erroneous conclusions. When data are very sparse, the choice between the available methods may have a large impact on the results. Methods that use the so-called continuity correction (eg, adding 0.5 to the number of events and non-events in studies with zero events in one treatment group) may lead to biased estimates. Conclusions Researchers should define the primary analysis a priori, in order to avoid selective reporting. A sensitivity analysis using a range of methods should be used to assess the robustness of results. Suboptimal methods such as using a continuity correction should be avoided.

To examine if cognitive restructuring (CR), behavioral activation (BA), and cognitive-behavioral therapy (CBT) result in differential effects in the treatment of adult depression. We extracted randomized controlled trials (RCTs) from a database updated yearly from PubMed, PsycINFO, Embase, and Cochrane Library. Network and pairwise meta-analyses were conducted to investigate the effects of CR, BA, and CBT delivered in a face-to-face individual format, compared with waiting list (WL) and care-as-usual (CAU), on adult depression. The primary outcome was a standardized mean difference (SMD) in posttreatment depression severity. Tolerability of treatments and depression severity at follow-up were also assessed. A total of 45 studies with 3,382 participants were included. There was no evidence of a difference in effectiveness between CR, BA, and CBT. All three interventions were superior to CAU; SMD 0.57, 95% confidence interval [CI 0.08-1.07]; 0.52 [0.34-0.71]; 0.44 [0.28-0.60], respectively and WL 1.20 [0.69-1.70]; 1.15 [0.90-1.40]; 1.07 [0.87-1.26]. No difference in tolerability was found (risk ratio [RR] vs. CAU: 1.01 [0.04-22.81], 0.84 [0.63-1.11], and 0.96 [0.76-1.21], respectively). Metaregression and sensitivity analyses did not produce material differences. Results suggest that CR or BA alone and their combination (CBT) may be effective interventions in comparison to WL and CAU in the treatment of adult depression. There was no evidence suggesting differences in effectiveness among the three treatments. More research is needed to derive conclusions about the performance of CR. (PsycInfo Database Record (c) 2021 APA, all rights reserved).