Which patients with metastatic hormone-sensitive prostate cancer benefit from docetaxel: a systematic review and meta-analysis of individual participant data from randomised trials.

BACKGROUND: Adding docetaxel to androgen deprivation therapy (ADT) improves survival in patients with metastatic, hormone-sensitive prostate cancer, but uncertainty remains about who benefits most. We therefore aimed to obtain up-to-date estimates of the overall effects of docetaxel and to assess whether these effects varied according to prespecified characteristics of the patients or their tumours. METHODS: The STOPCAP M1 collaboration conducted a systematic review and meta-analysis of individual participant data. We searched MEDLINE (from database inception to March 31, 2022), Embase (from database inception to March 31, 2022), the Cochrane Central Register of Controlled Trials (from database inception to March 31, 2022), proceedings of relevant conferences (from Jan 1, 1990, to Dec 31, 2022), and ClinicalTrials.gov (from database inception to March 28, 2023) to identify eligible randomised trials that assessed docetaxel plus ADT compared with ADT alone in patients with metastatic, hormone-sensitive prostate cancer. Detailed and updated individual participant data were requested directly from study investigators or through relevant repositories. The primary outcome was overall survival. Secondary outcomes were progression-free survival and failure-free survival. Overall pooled effects were estimated using an adjusted, intention-to-treat, two-stage, fixed-effect meta-analysis, with one-stage and random-effects sensitivity analyses. Missing covariate values were imputed. Differences in effect by participant characteristics were estimated using adjusted two-stage, fixed-effect meta-analysis of within-trial interactions on the basis of progression-free survival to maximise power. Identified effect modifiers were also assessed on the basis of overall survival. To explore multiple subgroup interactions and derive subgroup-specific absolute treatment effects we used one-stage flexible parametric modelling and regression standardisation. We assessed the risk of bias using the Cochrane Risk of Bias 2 tool. This study is registered with PROSPERO, CRD42019140591. FINDINGS: We obtained individual participant data from 2261 patients (98% of those randomised) from three eligible trials (GETUG-AFU15, CHAARTED, and STAMPEDE trials), with a median follow-up of 72 months (IQR 55-85). Individual participant data were not obtained from two additional small trials. Based on all included trials and patients, there were clear benefits of docetaxel on overall survival (hazard ratio [HR] 0·79, 95% CI 0·70 to 0·88; p<0·0001), progression-free survival (0·70, 0·63 to 0·77; p<0·0001), and failure-free survival (0·64, 0·58 to 0·71; p<0·0001), representing 5-year absolute improvements of around 9-11%. The overall risk of bias was assessed to be low, and there was no strong evidence of differences in effect between trials for all three main outcomes. The relative effect of docetaxel on progression-free survival appeared to be greater with increasing clinical T stage (pinteraction=0·0019), higher volume of metastases (pinteraction=0·020), and, to a lesser extent, synchronous diagnosis of metastatic disease (pinteraction=0·077). Taking into account the other interactions, the effect of docetaxel was independently modified by volume and clinical T stage, but not timing. There was no strong evidence that docetaxel improved absolute effects at 5 years for patients with low-volume, metachronous disease (-1%, 95% CI -15 to 12, for progression-free survival; 0%, -10 to 12, for overall survival). The largest absolute improvement at 5 years was observed for those with high-volume, clinical T stage 4 disease (27%, 95% CI 17 to 37, for progression-free survival; 35%, 24 to 47, for overall survival). INTERPRETATION: The addition of docetaxel to hormone therapy is best suited to patients with poorer prognosis for metastatic, hormone-sensitive prostate cancer based on a high volume of disease and potentially the bulkiness of the primary tumour. There is no evidence of meaningful benefit for patients with metachronous, low-volume disease who should therefore be managed differently. These results will better characterise patients most and, importantly, least likely to gain benefit from docetaxel, potentially changing international practice, guiding clinical decision making, better informing treatment policy, and improving patient outcomes. FUNDING: UK Medical Research Council and Prostate Cancer UK.

Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews.

BACKGROUND: Systematic reviews and meta-analysis of time-to-event outcomes are frequently published within the Cochrane Database of Systematic Reviews (CDSR). However, these outcomes are handled differently across meta-analyses. They can be analysed on the hazard ratio (HR) scale or can be dichotomized and analysed as binary outcomes using effect measures such as odds ratios (OR) or risk ratios (RR). We investigated the impact of reanalysing meta-analyses from the CDSR that used these different effect measures. METHODS: We extracted two types of meta-analysis data from the CDSR: either recorded in a binary form only ("binary"), or in binary form together with observed minus expected and variance statistics ("OEV"). We explored how results for time-to-event outcomes originally analysed as "binary" change when analysed using the complementary log-log (clog-log) link on a HR scale. For the data originally analysed as HRs ("OEV"), we compared these results to analysing them as binary on a HR scale using the clog-log link or using a logit link on an OR scale. RESULTS: The pooled HR estimates were closer to 1 than the OR estimates in the majority of meta-analyses. Important differences in between-study heterogeneity between the HR and OR analyses were also observed. These changes led to discrepant conclusions between the OR and HR scales in some meta-analyses. Situations under which the clog-log link performed better than logit link and vice versa were apparent, indicating that the correct choice of the method does matter. Differences between scales arise mainly when event probability is high and may occur via differences in between-study heterogeneity or via increased within-study standard error in the OR relative to the HR analyses. CONCLUSIONS: We identified that dichotomising time-to-event outcomes may be adequate for low event probabilities but not for high event probabilities. In meta-analyses where only binary data are available, the complementary log-log link may be a useful alternative when analysing time-to-event outcomes as binary, however the exact conditions need further exploration. These findings provide guidance on the appropriate methodology that should be used when conducting such meta-analyses.

A framework for prospective, adaptive meta-analysis (FAME) of aggregate data from randomised trials.

BACKGROUND: The vast majority of systematic reviews are planned retrospectively, once most eligible trials have completed and reported, and are based on aggregate data that can be extracted from publications. Prior knowledge of trial results can introduce bias into both review and meta-analysis methods, and the omission of unpublished data can lead to reporting biases. We present a collaborative framework for prospective, adaptive meta-analysis (FAME) of aggregate data to provide results that are less prone to bias. Also, with FAME, we monitor how evidence from trials is accumulating, to anticipate the earliest opportunity for a potentially definitive meta-analysis. METHODOLOGY: We developed and piloted FAME alongside 4 systematic reviews in prostate cancer, which allowed us to refine the key principles. These are to: (1) start the systematic review process early, while trials are ongoing or yet to report; (2) liaise with trial investigators to develop a detailed picture of all eligible trials; (3) prospectively assess the earliest possible timing for reliable meta-analysis based on the accumulating aggregate data; (4) develop and register (or publish) the systematic review protocol before trials produce results and seek appropriate aggregate data; (5) interpret meta-analysis results taking account of both available and unavailable data; and (6) assess the value of updating the systematic review and meta-analysis. These principles are illustrated via a hypothetical review and their application to 3 published systematic reviews. CONCLUSIONS: FAME can reduce the potential for bias, and produce more timely, thorough and reliable systematic reviews of aggregate data.

Adjuvant or early salvage radiotherapy for the treatment of localised and locally advanced prostate cancer: a prospectively planned systematic review and meta-analysis of aggregate data.

BACKGROUND: It is unclear whether adjuvant or early salvage radiotherapy following radical prostatectomy is more appropriate for men who present with localised or locally advanced prostate cancer. We aimed to prospectively plan a systematic review of randomised controlled trials (RCTs) comparing these radiotherapy approaches. METHODS: We used a prospective framework for adaptive meta-analysis (FAME), starting the review process while eligible trials were ongoing. RCTs were eligible if they aimed to compare immediate adjuvant radiotherapy versus early salvage radiotherapy, following radical prostatectomy in men (age ≥18 years) with intermediate-risk or high-risk, localised or locally advanced prostate cancer. We searched trial registers and conference proceedings until July 8, 2020, to identify eligible RCTs. By establishing the ARTISTIC collaboration with relevant trialists, we were able to anticipate when eligible trial results would emerge, and we developed and registered a protocol with PROSPERO before knowledge of the trial results (CRD42019132669). We used a harmonised definition of event-free survival, as the time from randomisation until the first evidence of either biochemical progression (prostate-specific antigen [PSA] ≥0·4 ng/mL and rising after completion of any postoperative radiotherapy), clinical or radiological progression, initiation of a non-trial treatment, death from prostate cancer, or a PSA level of at least 2·0 ng/mL at any time after randomisation. We predicted when we would have sufficient power to assess whether adjuvant radiotherapy was superior to early salvage radiotherapy. Investigators supplied results for event-free survival, both overall and within predefined patient subgroups. Hazard ratios (HRs) for the effects of radiotherapy timing on event-free survival and subgroup interactions were combined using fixed-effect meta-analysis. FINDINGS: We identified three eligible trials and were able to obtain updated results for event-free survival for 2153 patients recruited between November, 2007, and December, 2016. Median follow-up ranged from 60 months to 78 months, with a maximum follow-up of 132 months. 1075 patients were randomly assigned to receive adjuvant radiotherapy and 1078 to a policy of early salvage radiotherapy, of whom 421 (39·1%) had commenced treatment at the time of analysis. Patient characteristics were balanced within trials and overall. Median age was similar between trials at 64 or 65 years (with IQRs ranging from 59 to 68 years) across the three trials and most patients (1671 [77·6%]) had a Gleason score of 7. All trials were assessed as having low risk of bias. Based on 270 events, the meta-analysis showed no evidence that event-free survival was improved with adjuvant radiotherapy compared with early salvage radiotherapy (HR 0·95, 95% CI 0·75-1·21; p=0·70), with only a 1 percentage point (95% CI -2 to 3) change in 5-year event-free survival (89% vs 88%). Results were consistent across trials (heterogeneity p=0·18; I2=42%). INTERPRETATION: This collaborative and prospectively designed systematic review and meta-analysis suggests that adjuvant radiotherapy does not improve event-free survival in men with localised or locally advanced prostate cancer. Until data on long-term outcomes are available, early salvage treatment would seem the preferable treatment policy as it offers the opportunity to spare many men radiotherapy and its associated side-effects. FUNDING: UK Medical Research Council.

Comparison of aggregate and individual participant data approaches to meta-analysis of randomised trials: An observational study.

BACKGROUND: It remains unclear when standard systematic reviews and meta-analyses that rely on published aggregate data (AD) can provide robust clinical conclusions. We aimed to compare the results from a large cohort of systematic reviews and meta-analyses based on individual participant data (IPD) with meta-analyses of published AD, to establish when the latter are most likely to be reliable and when the IPD approach might be required. METHODS AND FINDINGS: We used 18 cancer systematic reviews that included IPD meta-analyses: all of those completed and published by the Meta-analysis Group of the MRC Clinical Trials Unit from 1991 to 2010. We extracted or estimated hazard ratios (HRs) and standard errors (SEs) for survival from trial reports and compared these with IPD equivalents at both the trial and meta-analysis level. We also extracted or estimated the number of events. We used paired t tests to assess whether HRs and SEs from published AD differed on average from those from IPD. We assessed agreement, and whether this was associated with trial or meta-analysis characteristics, using the approach of Bland and Altman. The 18 systematic reviews comprised 238 unique trials or trial comparisons, including 37,082 participants. A HR and SE could be generated for 127 trials, representing 53% of the trials and approximately 79% of eligible participants. On average, trial HRs derived from published AD were slightly more in favour of the research interventions than those from IPD (HRAD to HRIPD ratio = 0.95, p = 0.007), but the limits of agreement show that for individual trials, the HRs could deviate substantially. These limits narrowed with an increasing number of participants (p < 0.001) or a greater number (p < 0.001) or proportion (p < 0.001) of events in the AD. On average, meta-analysis HRs from published AD slightly tended to favour the research interventions whether based on fixed-effect (HRAD to HRIPD ratio = 0.97, p = 0.088) or random-effects (HRAD to HRIPD ratio = 0.96, p = 0.044) models, but the limits of agreement show that for individual meta-analyses, agreement was much more variable. These limits tended to narrow with an increasing number (p = 0.077) or proportion of events (p = 0.11) in the AD. However, even when the information size of the AD was large, individual meta-analysis HRs could still differ from their IPD equivalents by a relative 10% in favour of the research intervention to 5% in favour of control. We utilised the results to construct a decision tree for assessing whether an AD meta-analysis includes sufficient information, and when estimates of effects are most likely to be reliable. A lack of power at the meta-analysis level may have prevented us identifying additional factors associated with the reliability of AD meta-analyses, and we cannot be sure that our results are generalisable to all outcomes and effect measures. CONCLUSIONS: In this study we found that HRs from published AD were most likely to agree with those from IPD when the information size was large. Based on these findings, we provide guidance for determining systematically when standard AD meta-analysis will likely generate robust clinical conclusions, and when the IPD approach will add considerable value.

Addition of docetaxel or bisphosphonates to standard of care in men with localised or metastatic, hormone-sensitive prostate cancer: a systematic review and meta-analyses of aggregate data.

BACKGROUND: Results from large randomised controlled trials combining docetaxel or bisphosphonates with standard of care in hormone-sensitive prostate cancer have emerged. In order to investigate the effects of these therapies and to respond to emerging evidence, we aimed to systematically review all relevant trials using a framework for adaptive meta-analysis. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, LILACS, and the Cochrane Central Register of Controlled Trials, trial registers, conference proceedings, review articles, and reference lists of trial publications for all relevant randomised controlled trials (published, unpublished, and ongoing) comparing either standard of care with or without docetaxel or standard of care with or without bisphosphonates for men with high-risk localised or metastatic hormone-sensitive prostate cancer. For each trial, we extracted hazard ratios (HRs) of the effects of docetaxel or bisphosphonates on survival (time from randomisation until death from any cause) and failure-free survival (time from randomisation to biochemical or clinical failure or death from any cause) from published trial reports or presentations or obtained them directly from trial investigators. HRs were combined using the fixed-effect model (Mantel-Haenzsel). FINDINGS: We identified five eligible randomised controlled trials of docetaxel in men with metastatic (M1) disease. Results from three (CHAARTED, GETUG-15, STAMPEDE) of these trials (2992 [93%] of 3206 men randomised) showed that the addition of docetaxel to standard of care improved survival. The HR of 0·77 (95% CI 0·68-0·87; p<0·0001) translates to an absolute improvement in 4-year survival of 9% (95% CI 5-14). Docetaxel in addition to standard of care also improved failure-free survival, with the HR of 0·64 (0·58-0·70; p<0·0001) translating into a reduction in absolute 4-year failure rates of 16% (95% CI 12-19). We identified 11 trials of docetaxel for men with locally advanced disease (M0). Survival results from three (GETUG-12, RTOG 0521, STAMPEDE) of these trials (2121 [53%] of 3978 men) showed no evidence of a benefit from the addition of docetaxel (HR 0·87 [95% CI 0·69-1·09]; p=0·218), whereas failure-free survival data from four (GETUG-12, RTOG 0521, STAMPEDE, TAX 3501) of these trials (2348 [59%] of 3978 men) showed that docetaxel improved failure-free survival (0·70 [0·61-0·81]; p<0·0001), which translates into a reduced absolute 4-year failure rate of 8% (5-10). We identified seven eligible randomised controlled trials of bisphosphonates for men with M1 disease. Survival results from three of these trials (2740 [88%] of 3109 men) showed that addition of bisphosphonates improved survival (0·88 [0·79-0·98]; p=0·025), which translates to 5% (1-8) absolute improvement, but this result was influenced by the positive result of one trial of sodium clodronate, and we found no evidence of a benefit from the addition of zoledronic acid (0·94 [0·83-1·07]; p=0·323), which translates to an absolute improvement in survival of 2% (-3 to 7). Of 17 trials of bisphosphonates for men with M0 disease, survival results from four trials (4079 [66%] of 6220 men) showed no evidence of benefit from the addition of bisphosphonates (1·03 [0·89-1·18]; p=0·724) or zoledronic acid (0·98 [0·82-1·16]; p=0·782). Failure-free survival definitions were too inconsistent for formal meta-analyses for the bisphosphonate trials. INTERPRETATION: The addition of docetaxel to standard of care should be considered standard care for men with M1 hormone-sensitive prostate cancer who are starting treatment for the first time. More evidence on the effects of docetaxel on survival is needed in the M0 disease setting. No evidence exists to suggest that zoledronic acid improves survival in men with M1 or M0 disease, and any potential benefit is probably small. FUNDING: Medical Research Council UK.

Individual Participant Data (IPD) Meta-analyses of Randomised Controlled Trials: Guidance on Their Use.

Jayne Tierney and colleagues offer guidance on how to spot a well-designed and well-conducted individual participant data meta-analysis.

Meta-analysis of time-to-event outcomes from randomized trials using restricted mean survival time: application to individual participant data.

Meta-analysis of time-to-event outcomes using the hazard ratio as a treatment effect measure has an underlying assumption that hazards are proportional. The between-arm difference in the restricted mean survival time is a measure that avoids this assumption and allows the treatment effect to vary with time. We describe and evaluate meta-analysis based on the restricted mean survival time for dealing with non-proportional hazards and present a diagnostic method for the overall proportional hazards assumption. The methods are illustrated with the application to two individual participant meta-analyses in cancer. The examples were chosen because they differ in disease severity and the patterns of follow-up, in order to understand the potential impacts on the hazards and the overall effect estimates. We further investigate the estimation methods for restricted mean survival time by a simulation study.

Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement.

IMPORTANCE: Systematic reviews and meta-analyses of individual participant data (IPD) aim to collect, check, and reanalyze individual-level data from all studies addressing a particular research question and are therefore considered a gold standard approach to evidence synthesis. They are likely to be used with increasing frequency as current initiatives to share clinical trial data gain momentum and may be particularly important in reviewing controversial therapeutic areas. OBJECTIVE: To develop PRISMA-IPD as a stand-alone extension to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, tailored to the specific requirements of reporting systematic reviews and meta-analyses of IPD. Although developed primarily for reviews of randomized trials, many items will apply in other contexts, including reviews of diagnosis and prognosis. DESIGN: Development of PRISMA-IPD followed the EQUATOR Network framework guidance and used the existing standard PRISMA Statement as a starting point to draft additional relevant material. A web-based survey informed discussion at an international workshop that included researchers, clinicians, methodologists experienced in conducting systematic reviews and meta-analyses of IPD, and journal editors. The statement was drafted and iterative refinements were made by the project, advisory, and development groups. The PRISMA-IPD Development Group reached agreement on the PRISMA-IPD checklist and flow diagram by consensus. FINDINGS: Compared with standard PRISMA, the PRISMA-IPD checklist includes 3 new items that address (1) methods of checking the integrity of the IPD (such as pattern of randomization, data consistency, baseline imbalance, and missing data), (2) reporting any important issues that emerge, and (3) exploring variation (such as whether certain types of individual benefit more from the intervention than others). A further additional item was created by reorganization of standard PRISMA items relating to interpreting results. Wording was modified in 23 items to reflect the IPD approach. CONCLUSIONS AND RELEVANCE: PRISMA-IPD provides guidelines for reporting systematic reviews and meta-analyses of IPD.

Surrogate endpoints for overall survival in chemotherapy and radiotherapy trials in operable and locally advanced lung cancer: a re-analysis of meta-analyses of individual patients' data.

BACKGROUND: The gold standard endpoint in clinical trials of chemotherapy and radiotherapy for lung cancer is overall survival. Although reliable and simple to measure, this endpoint takes years to observe. Surrogate endpoints that would enable earlier assessments of treatment effects would be useful. We assessed the correlations between potential surrogate endpoints and overall survival at individual and trial levels. METHODS: We analysed individual patients' data from 15,071 patients involved in 60 randomised clinical trials that were assessed in six meta-analyses. Two meta-analyses were of adjuvant chemotherapy in non-small-cell lung cancer, three were of sequential or concurrent chemotherapy, and one was of modified radiotherapy in locally advanced lung cancer. We investigated disease-free survival (DFS) or progression-free survival (PFS), defined as the time from randomisation to local or distant relapse or death, and locoregional control, defined as the time to the first local event, as potential surrogate endpoints. At the individual level we calculated the squared correlations between distributions of these three endpoints and overall survival, and at the trial level we calculated the squared correlation between treatment effects for endpoints. FINDINGS: In trials of adjuvant chemotherapy, correlations between DFS and overall survival were very good at the individual level (ρ(2)=0.83, 95% CI 0.83-0.83 in trials without radiotherapy, and 0.87, 0.87-0.87 in trials with radiotherapy) and excellent at trial level (R(2)=0.92, 95% CI 0.88-0.95 in trials without radiotherapy and 0.99, 0.98-1.00 in trials with radiotherapy). In studies of locally advanced disease, correlations between PFS and overall survival were very good at the individual level (ρ(2) range 0.77-0.85, dependent on the regimen being assessed) and trial level (R(2) range 0.89-0.97). In studies with data on locoregional control, individual-level correlations were good (ρ(2)=0.71, 95% CI 0.71-0.71 for concurrent chemotherapy and ρ(2)=0.61, 0.61-0.61 for modified vs standard radiotherapy) and trial-level correlations very good (R(2)=0.85, 95% CI 0.77-0.92 for concurrent chemotherapy and R(2)=0.95, 0.91-0.98 for modified vs standard radiotherapy). INTERPRETATION: We found a high level of evidence that DFS is a valid surrogate endpoint for overall survival in studies of adjuvant chemotherapy involving patients with non-small-cell lung cancers, and PFS in those of chemotherapy and radiotherapy for patients with locally advanced lung cancers. Extrapolation to targeted agents, however, is not automatically warranted. FUNDING: Programme Hospitalier de Recherche Clinique, Ligue Nationale Contre le Cancer, British Medical Research Council, Sanofi-Aventis.

Use of multiple covariates in assessing treatment-effect modifiers: A methodological review of individual participant data meta-analyses.

Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate interaction may be due to confounding from a different, related covariate. We aimed to evaluate current practice when estimating treatment-covariate interactions in IPD meta-analysis, specifically focusing on involvement of additional covariates in the models. We reviewed 100 IPD meta-analyses of randomised trials, published between 2015 and 2020, that assessed at least one treatment-covariate interaction. We identified four approaches to handling additional covariates: (1) Single interaction model (unadjusted): No additional covariates included (57/100 IPD meta-analyses); (2) Single interaction model (adjusted): Adjustment for the main effect of at least one additional covariate (35/100); (3) Multiple interactions model: Adjustment for at least one two-way interaction between treatment and an additional covariate (3/100); and (4) Three-way interaction model: Three-way interaction formed between treatment, the additional covariate and the potential effect modifier (5/100). IPD is not being utilised to its fullest extent. In an exemplar dataset, we demonstrate how these approaches lead to different conclusions. Researchers should adjust for additional covariates when estimating interactions in IPD meta-analysis providing they adjust their main effects, which is already widely recommended. Further, they should consider whether more complex approaches could provide better information on who might benefit most from treatments, improving patient choice and treatment policy and practice.

Radiographic Progression-Free Survival and Clinical Progression-Free Survival as Potential Surrogates for Overall Survival in Men With Metastatic Hormone-Sensitive Prostate Cancer.

PURPOSE: Despite major increases in the longevity of men with metastatic hormone-sensitive prostate cancer (mHSPC), most men still die of prostate cancer. Phase III trials assessing new therapies in mHSPC with overall survival (OS) as the primary end point will take approximately a decade to complete. We investigated whether radiographic progression-free survival (rPFS) and clinical PFS (cPFS) are valid surrogates for OS in men with mHSPC and could potentially be used to expedite future phase III clinical trials. METHODS: We obtained individual patient data (IPD) from 9 eligible randomized trials comparing treatment regimens (different androgen deprivation therapy [ADT] strategies or ADT plus docetaxel in the control or research arms) in mHSPC. rPFS was defined as the time from random assignment to radiographic progression or death from any cause whichever occurred first; cPFS was defined as the time from random assignment to the date of radiographic progression, symptoms, initiation of new treatment, or death, whichever occurred first. We implemented a two-stage meta-analytic validation model where conditions of patient-level and trial-level surrogacy had to be met. We then computed the surrogate threshold effect (STE). RESULTS: IPD from 6,390 patients randomly assigned from 1994 to 2012 from 13 units were pooled for a stratified analysis. The median OS, rPFS, and cPFS were 4.3 (95% CI, 4.2 to 4.5), 2.4 (95% CI, 2.3 to 2.5), and 2.3 years (95% CI, 2.2 to 2.4), respectively. The STEs were 0.80 and 0.81 for rPFS and cPFS end points, respectively. CONCLUSION: Both rPFS and cPFS appear to be promising surrogate end points for OS. The STE of 0.80 or higher makes it viable for either rPFS or cPFS to be used as the primary end point that is surrogate for OS in phase III mHSPC trials with testosterone suppression alone as the backbone therapy and would expedite trial conduct.

Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework.

Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute scales, in order to target treatments appropriately-which estimation of an interaction effect does not in itself provide. Also, the focus has been on covariates with only two subgroups, and may exclude relevant data if only a single subgroup is reported. Therefore, in this article we further develop the "within-trial" framework by providing practical methods to (1) estimate within-trial interactions across two or more subgroups; (2) estimate subgroup-specific ("floating") treatment effects that are compatible with the within-trial interactions and make maximum use of available data; and (3) clearly present this data using novel implementation of forest plots. We described the steps involved and apply the methods to two examples taken from previously published meta-analyses, and demonstrate a straightforward implementation in Stata based upon existing code for multivariate meta-analysis. We discuss how the within-trial framework and plots can be utilised with aggregate (or "published") source data, as well as with individual participant data, to effectively demonstrate how treatment effects differ across participant subgroups.

Using individual participant data to improve network meta-analysis projects.

A network meta-analysis combines the evidence from existing randomised trials about the comparative efficacy of multiple treatments. It allows direct and indirect evidence about each comparison to be included in the same analysis, and provides a coherent framework to compare and rank treatments. A traditional network meta-analysis uses aggregate data (eg, treatment effect estimates and standard errors) obtained from publications or trial investigators. An alternative approach is to obtain, check, harmonise and meta-analyse the individual participant data (IPD) from each trial. In this article, we describe potential advantages of IPD for network meta-analysis projects, emphasising five key benefits: (1) improving the quality and scope of information available for inclusion in the meta-analysis, (2) examining and plotting distributions of covariates across trials (eg, for potential effect modifiers), (3) standardising and improving the analysis of each trial, (4) adjusting for prognostic factors to allow a network meta-analysis of conditional treatment effects and (5) including treatment-covariate interactions (effect modifiers) to allow relative treatment effects to vary by participant-level covariate values (eg, age, baseline depression score). A running theme of all these benefits is that they help examine and reduce heterogeneity (differences in the true treatment effect between trials) and inconsistency (differences in the true treatment effect between direct and indirect evidence) in the network. As a consequence, an IPD network meta-analysis has the potential for more precise, reliable and informative results for clinical practice and even allows treatment comparisons to be made for individual patients and targeted populations conditional on their particular characteristics.

Effects of oral anticoagulation in people with atrial fibrillation after spontaneous intracranial haemorrhage (COCROACH): prospective, individual participant data meta-analysis of randomised trials.

BACKGROUND: The safety and efficacy of oral anticoagulation for prevention of major adverse cardiovascular events in people with atrial fibrillation and spontaneous intracranial haemorrhage are uncertain. We planned to estimate the effects of starting versus avoiding oral anticoagulation in people with spontaneous intracranial haemorrhage and atrial fibrillation. METHODS: In this prospective meta-analysis, we searched bibliographic databases and trial registries using the strategies of a Cochrane systematic review (CD012144) on June 23, 2023. We included clinical trials if they were registered, randomised, and included participants with spontaneous intracranial haemorrhage and atrial fibrillation who were assigned to either start long-term use of any oral anticoagulant agent or avoid oral anticoagulation (ie, placebo, open control, another antithrombotic agent, or another intervention for the prevention of major adverse cardiovascular events). We assessed eligible trials using the Cochrane Risk of Bias tool. We sought data for individual participants who had not opted out of data sharing from chief investigators of completed trials, pending completion of ongoing trials in 2028. The primary outcome was any stroke or cardiovascular death. We used individual participant data to construct a Cox regression model of the time to the first occurrence of outcome events during follow-up in the intention-to-treat dataset supplied by each trial, followed by meta-analysis using a fixed-effect inverse-variance model to generate a pooled estimate of the hazard ratio (HR) with 95% CI. This study is registered with PROSPERO, CRD42021246133. FINDINGS: We identified four eligible trials; three were restricted to participants with atrial fibrillation and intracranial haemorrhage (SoSTART [NCT03153150], with 203 participants) or intracerebral haemorrhage (APACHE-AF [NCT02565693], with 101 participants, and NASPAF-ICH [NCT02998905], with 30 participants), and one included a subgroup of participants with previous intracranial haemorrhage (ELDERCARE-AF [NCT02801669], with 80 participants). After excluding two participants who opted out of data sharing, we included 412 participants (310 [75%] aged 75 years or older, 249 [60%] with CHA2DS2-VASc score ≤4, and 163 [40%] with CHA2DS2-VASc score >4). The intervention was a direct oral anticoagulant in 209 (99%) of 212 participants who were assigned to start oral anticoagulation, and the comparator was antiplatelet monotherapy in 67 (33%) of 200 participants assigned to avoid oral anticoagulation. The primary outcome of any stroke or cardiovascular death occurred in 29 (14%) of 212 participants who started oral anticoagulation versus 43 (22%) of 200 who avoided oral anticoagulation (pooled HR 0·68 [95% CI 0·42-1·10]; I2=0%). Oral anticoagulation reduced the risk of ischaemic major adverse cardiovascular events (nine [4%] of 212 vs 38 [19%] of 200; pooled HR 0·27 [95% CI 0·13-0·56]; I2=0%). There was no significant increase in haemorrhagic major adverse cardiovascular events (15 [7%] of 212 vs nine [5%] of 200; pooled HR 1·80 [95% CI 0·77-4·21]; I2=0%), death from any cause (38 [18%] of 212 vs 29 [15%] of 200; 1·29 [0·78-2·11]; I2=50%), or death or dependence after 1 year (78 [53%] of 147 vs 74 [51%] of 145; pooled odds ratio 1·12 [95% CI 0·70-1·79]; I2=0%). INTERPRETATION: For people with atrial fibrillation and intracranial haemorrhage, oral anticoagulation had uncertain effects on the risk of any stroke or cardiovascular death (both overall and in subgroups), haemorrhagic major adverse cardiovascular events, and functional outcome. Oral anticoagulation reduced the risk of ischaemic major adverse cardiovascular events, which can inform clinical practice. These findings should encourage recruitment to, and completion of, ongoing trials. FUNDING: British Heart Foundation.

Sharing individual participant data: through a systematic reviewer lens.

An increasing prevalence of data-sharing models, aimed at making individual participant data (IPD) from clinical trials widely available, should facilitate the conduct of systematic reviews and meta-analyses based on IPD. We have assessed these different data-sharing approaches, from the perspective of experienced IPD reviewers, to examine their utility for conducting systematic reviews based on IPD, and to highlight any challenges. We present an overview of the range of different models, including the traditional, single question approach, topic-based repositories, and the newer generic data platforms, and show that there are benefits and drawbacks to each. In particular, not all of the new models allow researchers to fully realise the well-documented advantages of using IPD for meta-analysis, and we offer potential solutions that can help improve both data quantity and utility. However, to achieve the "nirvana" of an ideal clinical data sharing environment, both for IPD meta-analysis and other secondary research purposes, we propose that data providers, data requestors, funders, and platforms need to adopt a more joined-up and standardised approach.

Duplicated network meta-analysis in advanced prostate cancer: a case study and recommendations for change.

BACKGROUND: Research overlap and duplication is a recognised problem in the context of both pairwise and network systematic reviews and meta-analyses. As a case study, we carried out a scoping review to identify and examine duplicated network meta-analyses (NMAs) in a specific disease setting where several novel therapies have recently emerged: hormone-sensitive metastatic prostate cancer (mHSPC). METHODS: MEDLINE and EMBASE were systematically searched, in January 2020, for indirect or mixed treatment comparisons or network meta-analyses of the systemic treatments docetaxel and abiraterone acetate in the mHSPC setting, with a time-to-event outcome reported on the hazard-ratio scale. Eligibility decisions were made, and data extraction performed, by two independent reviewers. RESULTS: A total of 13 eligible reviews were identified, analysing between 3 and 8 randomised comparisons, and comprising between 1773 and 7844 individual patients. Although the included trials and treatments showed a high degree of overlap, we observed considerable variation between identified reviews in terms of review aims, eligibility criteria and included data, statistical methodology, reporting and inference. Furthermore, crucial methodological details and specific source data were often unclear. CONCLUSIONS AND RECOMMENDATIONS: Variation across duplicated NMAs, together with reporting inadequacies, may compromise identification of best-performing treatments. Particularly in fast-moving fields, review authors should be aware of all relevant studies, and of other reviews with potential for overlap or duplication. We recommend that review protocols be published in advance, with greater clarity regarding the specific aims or scope of the project, and that reports include information on how the work builds upon existing knowledge. Source data and results should be clearly and completely presented to allow unbiased interpretation.

Coenzyme Q10 to manage chronic heart failure with a reduced ejection fraction: a systematic review and economic evaluation.

BACKGROUND: Chronic heart failure is a debilitating condition that accounts for an annual NHS spend of £2.3B. Low levels of endogenous coenzyme Q10 may exacerbate chronic heart failure. Coenzyme Q10 supplements might improve symptoms and slow progression. As statins are thought to block the production of coenzyme Q10, supplementation might be particularly beneficial for patients taking statins. OBJECTIVES: To assess the clinical effectiveness and cost-effectiveness of coenzyme Q10 in managing chronic heart failure with a reduced ejection fraction. METHODS: A systematic review that included randomised trials comparing coenzyme Q10 plus standard care with standard care alone in chronic heart failure. Trials restricted to chronic heart failure with a preserved ejection fraction were excluded. Databases including MEDLINE, EMBASE and CENTRAL were searched up to March 2020. Risk of bias was assessed using the Cochrane Risk of Bias tool (version 5.2). A planned individual participant data meta-analysis was not possible and meta-analyses were mostly based on aggregate data from publications. Potential effect modification was examined using meta-regression. A Markov model used treatment effects from the meta-analysis and baseline mortality and hospitalisation from an observational UK cohort. Costs were evaluated from an NHS and Personal Social Services perspective and expressed in Great British pounds at a 2019/20 price base. Outcomes were expressed in quality-adjusted life-years. Both costs and outcomes were discounted at a 3.5% annual rate. RESULTS: A total of 26 trials, comprising 2250 participants, were included in the systematic review. Many trials were reported poorly and were rated as having a high or unclear risk of bias in at least one domain. Meta-analysis suggested a possible benefit of coenzyme Q10 on all-cause mortality (seven trials, 1371 participants; relative risk 0.68, 95% confidence interval 0.45 to 1.03). The results for short-term functional outcomes were more modest or unclear. There was no indication of increased adverse events with coenzyme Q10. Meta-regression found no evidence of treatment interaction with statins. The base-case cost-effectiveness analysis produced incremental costs of £4878, incremental quality-adjusted life-years of 1.34 and an incremental cost-effectiveness ratio of £3650. Probabilistic sensitivity analyses showed that at thresholds of £20,000 and £30,000 per quality-adjusted life-year coenzyme Q10 had a high probability (95.2% and 95.8%, respectively) of being more cost-effective than standard care alone. Scenario analyses in which the population and other model assumptions were varied all found coenzyme Q10 to be cost-effective. The expected value of perfect information suggested that a new trial could be valuable. LIMITATIONS: For most outcomes, data were available from few trials and different trials contributed to different outcomes. There were concerns about risk of bias and whether or not the results from included trials were applicable to a typical UK population. A lack of individual participant data meant that planned detailed analyses of effect modifiers were not possible. CONCLUSIONS: Available evidence suggested that, if prescribed, coenzyme Q10 has the potential to be clinically effective and cost-effective for heart failure with a reduced ejection fraction. However, given important concerns about risk of bias, plausibility of effect sizes and applicability of the evidence base, establishing whether or not coenzyme Q10 is genuinely effective in a typical UK population is important, particularly as coenzyme Q10 has not been subject to the scrutiny of drug-licensing processes. Stronger evidence is needed before considering its prescription in the NHS. FUTURE WORK: A new independent, well-designed clinical trial of coenzyme Q10 in a typical UK heart failure with a reduced ejection fraction population may be warranted. STUDY REGISTRATION: This study is registered as PROSPERO CRD42018106189. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 4. See the NIHR Journals Library website for further project information.

People living with chronic heart failure suffer from shortness of breath, ankle swelling, tiredness, frequent stays in hospital and reduced quality of life and have shorter lives. The NHS spends over £2 billion each year managing chronic heart failure. Coenzyme Q10 is a vitamin-like substance made by the body that helps cells produce energy. Low levels of coenzyme Q10 in heart muscle may lead to, or exacerbate, chronic heart failure. Taking coenzyme Q10 supplements might improve symptoms or slow deterioration. To the best of our knowledge, we found all randomised clinical trials of coenzyme Q10 in patients with the type of chronic heart failure caused by muscle weakness (i.e. heart failure with reduced ejection fraction, where the heart's pumping function is weaker than normal). We asked the research groups responsible for these trials to provide the patient data that they had collected in their trials. Most research groups did not share their data and so we mainly used information from published trial reports. This limited our planned analyses. We found that taking coenzyme Q10 alongside usual treatment for heart failure with reduced ejection fraction potentially reduced deaths by approximately one-third and reduced readmission to hospital by around 40%. However, these results were uncertain. Side effects were not increased. We had some concerns about how reliable the data were, and it is not clear how well the results apply to UK patients. We also worked out what the benefits and costs to the NHS would be if coenzyme Q10 became available on prescription for patients with heart failure with reduced ejection fraction. Our model found that prescription could be worthwhile; however, a new trial is needed first to make sure that coenzyme Q10 improves outcomes for patients. A new trial would be particularly important because coenzyme Q10 has not been assessed in the same way as prescribed medicines. A new trial could make sure that there is better evidence about whether or not prescribing would be a good use of NHS resources.

Association between tocilizumab, sarilumab and all-cause mortality at 28 days in hospitalised patients with COVID-19: A network meta-analysis.

BACKGROUND: A recent prospective meta-analysis demonstrated that interleukin-6 antagonists are associated with lower all-cause mortality in hospitalised patients with COVID-19, compared with usual care or placebo. However, emerging evidence suggests that clinicians are favouring the use of tocilizumab over sarilumab. A new randomised comparison of these agents from the REMAP-CAP trial shows similar effects on in-hospital mortality. Therefore, we initiated a network meta-analysis, to estimate pairwise associations between tocilizumab, sarilumab and usual care or placebo with 28-day mortality, in COVID-19 patients receiving concomitant corticosteroids and ventilation, based on all available direct and indirect evidence. METHODS: Eligible trials randomised hospitalised patients with COVID-19 that compared tocilizumab or sarilumab with usual care or placebo in the prospective meta-analysis or that directly compared tocilizumab with sarilumab. Data were restricted to patients receiving corticosteroids and either non-invasive or invasive ventilation at randomisation. Pairwise associations between tocilizumab, sarilumab and usual care or placebo for all-cause mortality 28 days after randomisation were estimated using a frequentist contrast-based network meta-analysis of odds ratios (ORs), implementing multivariate fixed-effects models that assume consistency between the direct and indirect evidence. FINDINGS: One trial (REMAP-CAP) was identified that directly compared tocilizumab with sarilumab and supplied results on all-cause mortality at 28-days. This network meta-analysis was based on 898 eligible patients (278 deaths) from REMAP-CAP and 3710 eligible patients from 18 trials (1278 deaths) from the prospective meta-analysis. Summary ORs were similar for tocilizumab [0·82 [0·71-0·95, p = 0·008]] and sarilumab [0·80 [0·61-1·04, p = 0·09]] compared with usual care or placebo. The summary OR for 28-day mortality comparing tocilizumab with sarilumab was 1·03 [95%CI 0·81-1·32, p = 0·80]. The p-value for the global test of inconsistency was 0·28. CONCLUSIONS: Administration of either tocilizumab or sarilumab was associated with lower 28-day all-cause mortality compared with usual care or placebo. The association is not dependent on the choice of interleukin-6 receptor antagonist.

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics.

BACKGROUND: Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. METHODS: We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. RESULTS: Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. CONCLUSIONS: Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim.