Individual patient data network meta-analysis using either restricted mean survival time difference or hazard ratios: is there a difference? A case study on locoregionally advanced nasopharyngeal carcinomas

Role of chemotherapy in patients with nasopharynx carcinoma treated with radiotherapy (MAC-NPC): an updated individual patient data network meta-analysis

BACKGROUND

The meta-analysis of chemotherapy for nasopharynx carcinoma (MAC-NPC) collaborative group previously showed that the addition of adjuvant chemotherapy to concomitant chemoradiotherapy had the highest survival benefit of the studied treatment regimens in nasopharyngeal carcinoma. Due to the publication of new trials on induction chemotherapy, we updated the network meta-analysis.

METHODS

For this individual patient data network meta-analysis, trials of radiotherapy with or without chemotherapy in patients with non-metastatic nasopharyngeal carcinoma that completed accrual before Dec 31, 2016, were identified and updated individual patient data were obtained. Both general databases (eg, PubMed and Web of Science) and Chinese medical literature databases were searched. Overall survival was the primary endpoint. A frequentist network meta-analysis approach with a two-step random effect stratified by trial based on hazard ratio Peto estimator was used. Global Cochran Q statistic was used to assess homogeneity and consistency, and p score to rank treatments, with higher scores indicating higher benefit therapies. Treatments were grouped into the following categories: radiotherapy alone, induction chemotherapy followed by radiotherapy, induction chemotherapy without taxanes followed by chemoradiotherapy, induction chemotherapy with taxanes followed by chemoradiotherapy, chemoradiotherapy, chemoradiotherapy followed by adjuvant chemotherapy, and radiotherapy followed by adjuvant chemotherapy. This study is registered with PROSPERO, CRD42016042524.

FINDINGS

The network comprised 28 trials and included 8214 patients (6133 [74·7%] were men, 2073 [25·2%] were women, and eight [0·1%] had missing data) enrolled between Jan 1, 1988, and Dec 31, 2016. Median follow-up was 7·6 years (IQR 6·2-13·3). There was no evidence of heterogeneity (p=0·18), and inconsistency was borderline (p=0·10). The three treatments with the highest benefit for overall survival were induction chemotherapy with taxanes followed by chemoradiotherapy (hazard ratio 0·75; 95% CI 0·59-0·96; p score 92%), induction chemotherapy without taxanes followed by chemoradiotherapy (0·81; 0·69-0·95; p score 87%), and chemoradiotherapy followed by adjuvant chemotherapy (0·88; 0·75-1·04; p score 72%), compared with concomitant chemoradiotherapy (p score 46%).

INTERPRETATION

The inclusion of new trials modified the conclusion of the previous network meta-analysis. In this updated network meta-analysis, the addition of either induction chemotherapy or adjuvant chemotherapy to chemoradiotherapy improved overall survival over chemoradiotherapy alone in nasopharyngeal carcinoma.

FUNDING

Institut National du Cancer and Ligue Nationale Contre le Cancer.

A Comparison of Alternative Network Meta-Analysis Methods in the Presence of Nonproportional Hazards: A Case Study in First-Line Advanced or Metastatic Renal Cell Carcinoma

OBJECTIVES

Network meta-analysis (NMA) of time-to-event outcomes based on constant hazard ratios can result in biased findings when the proportional hazards (PHs) assumption does not hold in a subset of trials. We aimed to summarize the published non-PH NMA methods for time-to-event outcomes, demonstrate their application, and compare their results.

METHODS

The following non-PH NMA methods were compared through an illustrative case study in oncology of 4 randomized controlled trials in terms of progression-free survival and overall survival: (1) 1-step or (2) 2-step multivariate NMAs based on traditional survival distributions or fractional polynomials, (3) NMAs with restricted cubic splines for baseline hazard, and (4) restricted mean survival NMA.

RESULTS

For progression-free survival, the PH assumption did not hold across trials and non-PH NMA methods better reflected the relative treatment effects over time. The most flexible models (fractional polynomials and restricted cubic splines) fit better to the data than the other approaches. Estimated hazard ratios obtained with different non-PH NMA methods were similar at 5 years of follow-up but differed thereafter in the extrapolations. Although there was no strong evidence of PH violation for overall survival, non-PH NMA methods captured this uncertainty in the relative treatment effects over time.

CONCLUSIONS

When the PH assumption is questionable in a subset of the randomized controlled trials, we recommend assessing alternative non-PH NMA methods to estimate relative treatment effects for time-to-event outcomes. We propose a transparent and explicit stepwise model selection process considering model fit, external constraints, and clinical validity. Given inherent uncertainty, sensitivity analyses are suggested.

Individual Patient Data Meta-Analysis of 10-Year Follow-Up after Endovascular and Open Repair for Ruptured Abdominal AorticAneurysms

BACKGROUND

Endovascular aortic repair (EVAR) has conferred an early survival advantage compared to an open surgical repair (OSR) in patients with ruptured abdominal aortic aneurysms (rAAA). However, the long-term survival benefit after EVAR was not displayed among randomized controlled trials (RCTs), whereas many non-RCTs have provided conflicting results. We conducted a time-to-event individual patient data (IPD) meta-analysis on long-term rAAA data.

METHODS

All studies comparing mortality after EVAR versus OSR for rAAA were included. We used restricted mean survival times (RMSTs) as a measure of life expectancy for EVAR and OSR.

RESULTS

A total of 21 studies, including 12,187 patients (4952 EVAR and 7235 OSR) were finally deemed eligible. A secondary IPD analysis included 725 (372 EVAR and 353 OSR) patients only from the 3 RCTs (Immediate Management of the Patient With Rupture : Open Versus Endovascular Repair, Endovasculaire ou Chirurgie dans les Anévrysmes aorto-iliaques Rompus and Amsterdam Acute Aneurysm Trial trials). Among all studies, the median survival was 4.20 (95% confidence interval [CI]: 3.70-4.58) years for EVAR and 1.91 (95% CI: 1.57-2.39) years for OSR. Although EVAR presented with increased hazard risk from 4 to 7 years, which peaked at 6 years after the operation, the RMST difference was 0.54 (95% CI: 0.35-0.73; P < 0.001) years gained with EVAR at the end of the 10-year follow-up. IPD meta-analysis of RCTs did not demonstrate significant differences.

CONCLUSIONS

At 10-years follow-up, EVAR was associated with a 6.5 month increase in life expectancy when compared to OSR after analyzing all eligible studies. Evidence from our study suggests that a strict follow-up program would be desirable, especially for patients with long-life expectancy.

Identifying optimal PD-1/PD-L1 inhibitors in first-line treatment of patients with advanced squamous non-small cell lung cancer in China: Updated systematic review and network meta-analysis

Objective: After Gemstone-302 was published in Lancet in January 2022, seven PD-(L)1 inhibitors launched or about to be launched in China, but there are no head-to-head RCTs reporting the comparative efficacy for squamous non-small cell lung cancer (sq-NSCLC). Therefore, we aimed to indirectly compare the efficacy of these treatments to provide evidence for clinical decision and Chinese national reimbursement drug listing.

Methods: We collected phase III clinical trials targeted on stage IIIB–IV patients for first-line immunotherapy of sq-NSCLC by systematically searching databases. Relative effects of competing treatments were assessed by Bayesian network meta-analysis and non-parametric restricted mean survival time (RMST) model. Hazard ratio (HR), severe adverse events (SAEs, grade 3–5), progression-free survival (PFS) and overall survival (OS) years were the outcomes. Subgroup analysis was done according to PD-(L)1 expression, smoking, gender, Eastern Cooperative Oncology Group performance status, age and disease stage. Sensitivity analysis using the range of parameters distribution as well as different comparison methods was performed to test the robustness of the results.

Results: A total of 7 clinical trials with 2,640 patients were included. For OS, the efficiency (HR, 95%CI) ranks from high to low were sugemalimab (0.48, 0.32–0.73), camrelizumab (0.55, 0.40–0.76), sintilimab (0.56, 0.35–0.90), pembrolizumab (0.71, 0.58–0.87) and atezolizumab (0.88, 0.73–1.05). For PFS, the efficiency ranks from high to low were sugemalimab (0.33, 0.24–0.45), camrelizumab (0.37, 0.30–0.46), tislelizumab (0.53, 0.36–0.79), sintilimab (0.54, 0.42–0.69), toripalimab (0.56, 0.38–0.83), pembrolizumab (0.57, 0.47–0.70) and atezolizumab (0.71, 0.59–0.85). Proportional hazard models and non-proportional hazard models showed consistent efficiency ranks. When extrapolated to long-term survival benefit, under non-proportional hazard ratio, sugemalimab achieved the highest PFS benefit (lifeyears, LYs) in 2 years (1.323), with camrelizumab (1.320), sintilimab (1.243), tislelizumab (1.189), pembrolizumab (0.990) and atezolizumab (0.947) ranking in order; Camrelizumab achieved the highest OS benefit (LYs) in 10 years (2.723), with atezolizumab (2.445) and pembrolizumab (2.397) ranking in order. RMST model showed similar results. In terms of safety, PD-(L)1 inhibitors increased the incidence of SAEs when combined with chemotherapy, sugemalimab and camrelizumab was the safest drugs.

Conclusion: Sugemalimab is superior both in HR and long-term survival benefit for Chinese patients with advanced sq-NSCLC.

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.

Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network

BACKGROUND

Synthesis of clinical effectiveness from multiple trials is a well-established component of decision-making. Time-to-event outcomes are often synthesised using the Cox proportional hazards model assuming a constant hazard ratio over time. However, with an increasing proportion of trials reporting treatment effects where hazard ratios vary over time and with differing lengths of follow-up across trials, alternative synthesis methods are needed.

OBJECTIVES

To compare and contrast five modelling approaches for synthesis of time-to-event outcomes and provide guidance on key considerations for choosing between the modelling approaches.

METHODS

The Cox proportional hazards model and five other methods of estimating treatment effects from time-to-event outcomes, which relax the proportional hazards assumption, were applied to a network of melanoma trials reporting overall survival: restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models.

RESULTS

All models fitted the melanoma network acceptably well. However, there were important differences in extrapolations of the survival curve and interpretability of the modelling constraints demonstrating the potential for different conclusions from different modelling approaches.

CONCLUSION

The restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models can accommodate non-proportional hazards and differing lengths of trial follow-up within a network meta-analysis of time-to-event outcomes. We recommend that model choice is informed using available and relevant prior knowledge, model transparency, graphically comparing survival curves alongside observed data to aid consideration of the reliability of the survival estimates, and consideration of how the treatment effect estimates can be incorporated within a decision model.

Bayesian multivariate network meta-analysis model for the difference in restricted mean survival times

Network meta-analysis (NMA) is essential for clinical decision-making. NMA enables inference for all pair-wise comparisons between interventions available for the same indication, by using both direct evidence and indirect evidence. In randomized trials with time-to event outcome data, such as lung cancer data, conventional NMA methods rely on the hazard ratio and the proportional hazards assumption, and ignore the varying follow-up durations across trials. We introduce a novel multivariate NMA model for the difference in restricted mean survival times (RMST). Our model synthesizes all the available evidence from multiple time points simultaneously and borrows information across time points through within-study covariance and between-study covariance for the differences in RMST. We propose an estimator of the within-study covariance and we then assume it to be known. We estimate the model under the Bayesian framework. We evaluated our model by conducting a simulation study. Our multiple-time-point model yields lower mean squared error over the conventional single-time-point model at all time points, especially when the availability of evidence decreases. We illustrated the model on a network of randomized trials of second-line treatments of advanced non-small-cell lung cancer. Our multiple-time-point model yielded increased precision and detected evidence of benefit at earlier time points as compared to the single-time-point model. Our model has the advantage of providing clinically interpretable measures of treatment effects.

Progress and challenges of network meta-analysis

In the past years, network meta-analysis (NMA) has been widely used among clinicians, guideline makers, and health technology assessment agencies and has played an important role in clinical decision-making and guideline development. To inform further development of NMAs, we conducted a bibliometric analysis to assess the current status of published NMA methodological studies, summarized the methodological progress of seven types of NMAs, and discussed the current challenges of NMAs.

Statistical fundamentals on cancer research for clinicians: Working with your statisticians

PURPOSE

To facilitate understanding statistical principles and methods for clinicians involved in cancer research.

METHODS

An overview of study design is provided on cancer research for both observational and clinical trials addressing study objectives and endpoints, superiority tests, non-inferiority and equivalence design, and sample size calculation. The principles of statistical models and tests including contemporary standard methods of analysis and evaluation are discussed. Finally, some statistical pitfalls frequently evident in clinical and translational studies in cancer are discussed.

RESULTS

We emphasize the practical aspects of study design (superiority vs non-inferiority vs equivalence study) and assumptions underpinning power calculations and sample size estimation. The differences between relative risk, odds ratio, and hazard ratio, understanding outcome endpoints, purposes of interim analysis, and statistical modeling to minimize confounding effects and bias are also discussed.

CONCLUSION

Proper design and correctly constructed statistical models are critical for the success of cancer research studies. Most statistical inaccuracies can be minimized by following essential statistical principles and guidelines to improve quality in research studies.

The Current Role of Adjuvant Chemotherapy in Locally Advanced Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck, and it originates from the mucous epithelium of the nasopharynx. Because it is "hidden", the symptoms of NPC can easily be missed, and more than 70% of patients present with locally advanced disease at diagnosis. Concurrent radiation therapy with chemotherapy can significantly improve regional control of NPC. At present, distant metastasis is the main cause of treatment failure. At the end of the 20th century, clinical trial No. IG0099 in the United States confirmed the effectiveness of adjuvant chemotherapy (AC) for the first time. However, in the past 20 years, various clinical trials and meta-analyses conducted globally have yielded contradictory results regarding the effect of AC on locally advanced NPC. AC has changed from category 1 to the current category 2A in the National Comprehensive Cancer Network (NCCN) guidelines, and it remains controversial whether AC can significantly improve the survival of NPC patients. Here, we comprehensively analyzed the role of AC in locally advanced NPC by comparing some treatment methods. We conclude the role of AC in treating locally advanced NPC, based on the studies presented, remains undefined but is associated with increased toxicity.