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Original Investigation
December 26, 2019

Use of Immunotherapy With Programmed Cell Death 1 vs Programmed Cell Death Ligand 1 Inhibitors in Patients With Cancer: A Systematic Review and Meta-analysis

Author Affiliations
  • 1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
  • 2The Medical Department, 3D Medicines Inc, Shanghai, China
  • 3School of Public Health, Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Beijing, China
  • 4Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
JAMA Oncol. Published online December 26, 2019. doi:10.1001/jamaoncol.2019.5367
Key Points

Question  Do anti–programmed cell death 1 and anti–programmed cell death ligand 1 deliver different clinical outcomes?

Findings  In this systematic review and meta-analysis of 19 randomized clinical trials involving 11 379 patients, anti–programmed cell death 1 appears to exhibit significantly greater overall survival compared with anti–programmed cell death ligand 1 with a comparable safety profile in patients with solid tumors.

Meaning  Anti–programmed cell death 1 appears to exhibit favorable survival outcomes and a comparable safety profile with anti–programmed cell death ligand 1 in cancer therapy, which may provide valuable insight for future treatment strategy.


Importance  Immune checkpoint inhibitors of programmed cell death 1 (PD-1) and its ligand (PD-L1) have led to a paradigm shift in cancer treatment. Understanding the clinical efficacy and safety profile of these drugs is necessary for treatment strategy in clinical practice.

Objective  To assess the differences between anti–PD-1 and anti–PD-L1 regarding efficacy and safety shown in randomized clinical trials across various tumor types.

Data Sources  Systematic searches of PubMed, Cochrane CENTRAL, and Embase were conducted from January 1, 2000, to March 1, 2019. In addition, abstracts and presentations from all major conference proceedings were reviewed.

Study Selection  All randomized clinical trials that compared anti–PD-1 and anti–PD-L1 with standard treatment in patients with cancer were selected as candidates. Retrospective studies, single-arm phase 1/2 studies, and trials comparing anti–PD-1 and anti–PD-L1 with other immunotherapies were excluded. Studies of anti–PD-1 and anti–PD-L1 therapy were screened and paired by the matching of clinical characteristics as mirror groups.

Data Extraction and Synthesis  Three investigators independently extracted data from each study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guideline. Trial names, first author, year of publication, study design, National Clinical Trial identifier number, blinding status, study phase, pathologic characteristics, number of patients, patients’ age and sex distribution, Eastern Cooperative Oncology Group Performance Status, lines of treatment, study drugs, biomarker status, follow-up time, incidence of adverse events, and hazard ratios (HRs) with 95% CIs for overall survival and progression-free survival were extracted. A random-effects model was applied for data analysis.

Main Outcomes and Measures  Differences in OS between anti–PD-1 and anti–PD-L1 across different cancer types were assessed. An effect size was derived from each mirror group and then pooled across all groups using a random-effects model.

Results  Nineteen randomized clinical trials involving 11 379 patients were included in the meta-analysis. Overall, anti–PD-1 exhibited superior overall survival (HR, 0.75; 95% CI, 0.65-0.86; P < .001) and progression-free survival (HR, 0.73; 95% CI, 0.56-0.96; P = .02) compared with anti–PD-L1. No significant difference was observed in their safety profiles. Sensitivity analysis presented consistency in the overall estimates across these analyses. Consistent results were observed through frequentist and bayesian approaches with the same studies.

Conclusions and Relevance  Comprehensive analysis suggests that anti–PD-1 exhibited favorable survival outcomes and a safety profile comparable to that of anti–PD-L1, which may provide a useful guide for clinicians.

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    1 Comment for this article
    Inappropriate safety comparision based on different control arms in Mirror 3 for GC 3L
    Yiling Chen, MBA | Guosen Securities
    The authors illustrated indirect comparsions of efficacy and safety outcomes of anti-PD-1 vs anti-PD-L1 therapies across multiple settings with similar indications, biomarker subpopulations, treatment lines and regimens. Generally, we agree with the authors' conclusion of PFS and OS superiority and comparable safety profiles of anti-PD-1 vs anti-PD-L1, for multiple indications and for GC 3L as our focus. However, two randomized clinical trials compared in Mirror 3 had materially different control arms: placebo to nivolumab in ATTRACTION-2, and chemotherapy to avelumab in JAVELIN Gastric 300. Since the inclusion of Mirror 3 did not meet the mirror principle mentioned by the authors in Figure 2, the meta-analysis and intepretation of efficacy and safety outcomes should be more careful and cautious.
    The results of both trials had been published (Kang et al. Lancet. 2017; Bang et al. Ann Oncol. 2018). We have no idea to discuss about the possible efficacy variability due to different baseline characteristics (especially due to pathogenesis of Eastern and Western GC patients, implied by KEYNOTE-181), but we focus on the safety profiles in the GC 3L setting exhibited in this article. It might be inaccurate of the risk ratios for GC 3L listed in the Table (2.42 in any grade AEs, 7.28 in grade 3-5 AEs). We find that mispresentation possibly caused by the benchmark effect of different control arms.
    From Kang's article and Bang's article, the incidence of any grade TRAEs was 42.7% in the nivolumab arm vs 26.7% in the placebo arm, and 48.9% in the avelumab arm vs 74.0% in the chemotherapy arm. Grade 3-5 TRAEs was 10.3% in nivolumab vs 4.3% in placebo, and 9.8% in avelumab vs 39.0% in chemotherapy. Furthermore, TRAEs led to discontinuation was 2.7% in nivolumab vs 2.5% in placebo, and 3.8% in avelumab vs 5.1% in chemotherapy. Indeed, incidences of any grade TRAEs (40~50%) and grade 3-5 TRAEs (~10%) were numerically approximate between nivolumab arm and avelumab arm. But based on different control benchmarks, nivolumab seemed to incur more frequent and severe TRAEs compared to placebo control, while avelumab seemed to incur less TRAEs compared to chemotherapy control.
    We notice that the patients in the control arm of JAVELIN Gastric 300 were treated not by BSC but predominantly by chemotherapy (irenotecan n=120, paclitaxel n=54, BSC only n=3), which was materially different from placebo control in ATTRACTION-2. So it could be inappropriate and misleading to use relative risk ratio method (simplified (42.7/26.7)/(48.9/74.0)=2.42, similar to 2.41 in the Table with adjustment) to measure the safety profiles of two immunotherapies in the GC 3L setting based on two control regimens with materially distinct safety profiles.
    Since March 2019, more results and data of randomized clinical trials have been announced and published across various settings. We hope more detailed subgroup analyses and more extended meta-analyses could be applied, especially similar-setting cross-trial comparison like this article did, while baseline alignment and control arm calibration should be necessary for comparability. These efforts could reveal the hologram of immunotherapy landscape, and help to illustrate more responsive indications, more sensitive subpopulations, more effective therapeutics and more optimized paradigms, which are useful and welcome to clinical practitioners, research investigators and investment analysts.
    Additionally, there is a mistake or typo in Figure 4 (≥3 lines of treatment in urothelial carcinoma should be corrected as ≤3 lines).