Efficacy and safety of programmed cell death protein 1/programmed death-ligand 1 inhibitors combined with chemotherapy for breast cancer: a systematic review and meta-analysis

Introduction

Background

Breast cancer (BC) remains one of the most prevalent malignancies worldwide, posing a significant threat to women’s health (1-3). It is classified into distinct molecular subtypes, including hormone receptor-positive (HR⁺), human epidermal growth factor receptor 2-positive (HER2⁺), and triple-negative BC (TNBC), each characterized by unique biological behaviors and clinical outcomes (4-6). Despite advancements in early detection and multimodal therapies—including surgery, chemotherapy (CT), radiotherapy, and targeted treatments—BC remains a leading cause of cancer-related mortality worldwide. This is primarily attributed to its inherent high heterogeneity, strong metastatic potential, and notable recurrence rates (7). Conventional therapies often face limitations, including drug resistance, severe toxicity, and insufficient efficacy in aggressive subtypes like TNBC. Furthermore, the absence of reliable biomarkers for personalized treatment complicates clinical decision-making, underscoring the urgent need for innovative therapeutic strategies (8).

Immunotherapy has emerged as a transformative approach in BC management, particularly through immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis (9-11). This pathway facilitates tumor immune evasion by suppressing T-cell activity, and its blockade can restore anti-tumor immunity (12,13). Recent clinical trials have demonstrated that combining ICIs such as atezolizumab (Ate) or pembrolizumab (Pem) with CT significantly improves overall survival (OS) and progression-free survival (PFS) in advanced BC, leading to regulatory approvals by the U.S. Food and Drug Administration (FDA) (14-16). However, critical controversies persist that hinder precise clinical decision-making: first, the comparative efficacy of ICI-CT combinations varies substantially based on CT backbone selection [e.g., nab-paclitaxel (nP) vs. solvent-based taxanes], with unresolved debates about whether nP’s avoidance of steroid premedication (and subsequent preservation of ICI activity) translates to superior outcomes compared to conventional taxanes (17,18); second, PD-L1’s validity as a predictive biomarker remains inconsistent across different detection assays and threshold definitions, creating uncertainty about which patients truly benefit from ICI-based therapies; third, while ICIs improve survival, they introduce unique immune-related adverse events (irAEs) that may offset therapeutic gains, yet few studies have systematically compared toxicity profiles across different ICI-CT regimens to inform risk-benefit trade-offs. These controversies are not merely gaps in “unclear” efficacy data but actionable clinical dilemmas that require synthesis of existing evidence—an essential role of meta-analysis, as primary randomised controlled trials (RCTs) are often underpowered to resolve subgroup differences or cross-regimen safety comparisons (19).

Rationale and knowledge gap

Existing meta-analyses are constrained by small sample sizes, high heterogeneity, and insufficient direct comparisons between key regimens. Notably, the differential effects of CT backbone choices (e.g., nP vs. conventional taxanes) and biomarker-driven stratification (e.g., PD-L1 expression thresholds) remain underexplored. Addressing these gaps is critical to advancing precision medicine in BC.

Objective

This study presents the first low-heterogeneity meta-analysis directly comparing Ate- and Pem-based combinations in BC, with a focus on TNBC and PD-L1-positive populations. By synthesizing data from randomized controlled trials (RCTs), we systematically evaluate the survival benefits of distinct regimens and elucidate the impact of CT backbone selection and biomarker stratification. Our work advances the field through expanded evidence from high-quality trials, head-to-head comparisons of Ate and Pem, precision subgroup analyses for TNBC and PD-L1-positive cohorts, and insights into CT optimization. The findings provide high-level evidence to guide clinical decision-making, refine biomarker-driven approaches, and challenge traditional therapeutic paradigms.

Future research should prioritize validating PD-L1 expression thresholds, optimizing CT sequencing, and exploring novel synergistic regimens to maximize therapeutic benefits. This study lays a robust foundation for reshaping the BC treatment landscape and improving patient outcomes. We present this article in accordance with the PRISMA reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1949/rc).

Methods

Study design

To ensure transparency and minimize selection bias, the study protocol was prospectively registered on PROSPERO (CRD420251051736) prior to data collection and analysis.

Eligibility criteria

RCTs were eligible if they evaluated immunotherapy-CT combinations (e.g., Ate with CT, Ate with nP, or Pem with CT) against control regimens (placebo plus CT or taxane-based therapy) in patients with BC. Exclusion criteria encompassed non-randomized studies, conference abstracts, trials with incomplete outcome data, studies lacking hazard ratios (HRs) with 95% confidence intervals (CIs) for OS or PFS, trials with fewer than 10 patients per treatment arm, and duplicate publications (only the most recent and comprehensive data were retained).

Data sources and search strategy

A comprehensive search of PubMed, Embase, and the Cochrane Central Register of Controlled Trials was conducted for English-language studies published before November 29, 2025. Key search terms included “PD-1 inhibitor”, “PD-L1 inhibitor”, “atezolizumab”, “pembrolizumab”, “breast cancer”, and “randomized controlled trial”. Manual screening of reference lists from relevant reviews and registered trials on ClinicalTrials.gov ensured thorough coverage of available evidence.

Study selection and data extraction

Two independent reviewers (C.B. and Z.C.) screened titles, abstracts, and full texts to assess eligibility. Discrepancies were resolved through discussion with a third reviewer. Extracted data included study characteristics (author, publication year, trial phase, NCT identifier), patient demographics (sample size, median age, BC subtype), intervention details (treatment regimen, dosing, duration), and outcomes (HRs for OS/PFS, PD-L1 expression thresholds, subgroup analyses).

Risk of bias assessment

Study quality was evaluated using the Cochrane Risk of Bias Tool 2.0, which assessed randomization processes, allocation concealment, blinding, outcome reporting completeness, and attrition bias. Each domain was classified as low, high, or unclear risk.

Statistical analysis

Primary outcomes (OS and PFS) were analyzed using random-effects models weighted by inverse variance to account for clinical and methodological heterogeneity. Heterogeneity was quantified via Cochran’s Q test and I² statistics (I²>50% indicating substantial heterogeneity). Sensitivity analyses excluded trials with high risk of bias. Subgroup analyses focused on TNBC, PD-L1-positive populations, and CT backbone differences (nP vs. conventional taxanes). All analyses were performed using STATA 12.0 (StataCorp), with P<0.05 considered statistically significant.

Subgroup analyses

Predefined subgroup analyses were conducted to evaluate the differential efficacy of immunotherapy-CT combinations across clinically relevant populations and treatment variables. These included comparisons between TNBC and non-TNBC cohorts, stratification by PD-L1 expression status (positive vs. negative), and variations in CT backbone (e.g., nP vs. conventional taxane-based regimens). Effect estimates for each subgroup were calculated using random-effects models, with heterogeneity within subgroups assessed via Cochran’s Q test and I² statistics. Sensitivity analyses were performed to validate findings in subgroups with limited data or high heterogeneity.

Results

Study selection and characteristics

The literature search identified 826 records, of which 12 RCTs involving 6,691 patients met the eligibility criteria (Figure 1, Table 1). Key characteristics of the included trials are summarized in Table 1 (15,17,18,20-28). The analysis encompassed diverse immunotherapy-CT combinations, including Ate with nP, CT, or bevacizumab (Bev), and Pem with CT or paraplatin (P). Patient cohorts varied across trials, with sample sizes ranging from 104 to 2,244 per treatment arm.

Figure 1 PRISMA flowchart.

Survival outcomes in the overall population

OS

Ate-based regimens demonstrated significant OS benefits compared to controls (HR =0.83; 95% CI: 0.75–0.93; I²=52.8%), with the most pronounced effect observed in the Ate + nP subgroup (HR =0.75; 95% CI: 0.65–0.86; I²=49.2%) (Figure 2A). Similarly, Pem + CT showed a robust OS advantage (HR =0.70; 95% CI: 0.57–0.86; I²=4.9%) (Figure 2B).

Figure 2 Forest plots for OS comparisons. (A) Ate-based regimens vs. controls. (B) Pem-based regimens vs. controls. Ate, atezolizumab; CI, confidence interval; HR, hazard ratio; OS, overall survival; Pem, pembrolizumab.

PFS

Ate-based combinations significantly improved PFS (HR =0.77; 95% CI: 0.71–0.83; I²=53.5%), particularly in the Ate + nP subgroup (HR =0.69; 95% CI: 0.62–0.78; I²=65.4%). Pem + CT also enhanced PFS (HR =0.75; 95% CI: 0.65–0.87; I²=44.6%), though heterogeneity was moderate (Figure 3A,3B).

Figure 3 Forest plots for PFS comparisons. (A) Ate-based regimens vs. controls. (B) Pem-based regimens vs. controls. Ate, atezolizumab; CI, confidence interval; HR, hazard ratio; Pem, pembrolizumab; PFS, progression-free survival.

Subgroup analyses in TNBC

In TNBC patients, Ate-based regimens were associated with improved OS (HR =0.90; 95% CI: 0.78–1.04; I²=24.2%) and PFS (HR =0.83; 95% CI: 0.75–0.91; I²=49.0%), though statistical significance for OS was marginal. Pem + CT exhibited stronger OS benefits in this subgroup (HR =0.70; 95% CI: 0.57–0.86; I²=4.9%) (Figure 4A,4B).

Figure 4 Subgroup analysis of OS (A,C,E) and PFS (B,D,F) by treatment regimen. (A,B) Ate or Pem vs. control group in TNBC. (C,D) Ate + nP or CT vs. controls: (C) Ate + nP vs. controls; (D) Ate + CT vs. controls. (E,F) Ate or Pem + CT vs. controls. Ate, atezolizumab; CI, confidence interval; CT, chemotherapy; HR, hazard ratio; nP, nab-paclitaxel; OS, overall survival; Pem, pembrolizumab; PFS, progression-free survival; TNBC, triple-negative breast cancer.

Impact of CT backbone

Comparative analysis of CT partners revealed superior efficacy of Ate + nP over Ate + CT in OS (HR =0.75 vs. 1.18) and PFS (HR =0.69 vs. 0.81). However, limited data for Ate + CT (1 trial for OS; 2 trials for PFS) precluded definitive conclusions (Figure 4C,4D).

Head-to-head comparisons: Ate vs. Pem with CT

Direct comparison of Ate + CT and Pem + CT regimens showed comparable OS benefits (Ate + CT: HR =0.74; 95% CI: 0.65–0.85; Pem + CT: HR =0.81; 95% CI: 0.69–0.95). For PFS, Pem + CT marginally outperformed Ate + CT (HR =0.69 vs. 0.71), though heterogeneity was higher in the Pem subgroup (I²=51.6%) (Figure 4E,4F).

Safety profile analysis of adverse events

Overall unacceptable adverse events (UAEs)

A comprehensive evaluation of clinical interventions necessitates a balanced assessment of efficacy and safety. Table S1 summarizes the data on overall UAEs and serious adverse events (SAEs) from 10 included RCTs, providing critical insights into the safety profile of PD-1/PD-L1 inhibitor-CT combinations.

In the experimental groups (PD-1/PD-L1 inhibitor + CT), the incidence of overall UAEs ranged from 70.59% (12/17) to 89.57% (438/562), with a median incidence of 82.14% (26,28). In contrast, the control groups (placebo + CT) showed a relatively lower UAE incidence, ranging from 48.15% (22/26) to 82.11% (223/451), with a median incidence of 73.91% (24,27). Quantitative synthesis using random-effects models (accounting for moderate heterogeneity, I²=42.3%) revealed that the experimental groups had a significantly higher risk of UAEs compared to controls [relative risk (RR) =1.12; 95% CI: 1.05–1.19; P=0.001]. The absolute risk difference (ARD) was 8.23% (95% CI: 3.17–13.29%), indicating that PD-1/PD-L1 inhibitor combination therapy was associated with an additional 8.23% risk of clinically UAEs relative to CT alone. Subgroup analysis by intervention type showed that the risk elevation was more pronounced in Pem-based combinations (RR=1.18; 95% CI: 1.07–1.30) compared to Ate-based regimens (RR=1.09; 95% CI: 1.02–1.17), which may be attributed to the distinct pharmacodynamic profiles of the two ICIs or differences in CT backbones.

SAEs

SAEs, which reflect clinically significant, potentially life-threatening toxicities, are critical for risk-benefit assessment. In the experimental groups, SAE incidence varied from 29.41% (5/17) to 43.20% (267/783), with a median incidence of 38.60%. The control groups had a lower median SAE incidence of 27.54%, ranging from 15.38% (4/26) to 38.29% (82/451) (22,25,27,28). Meta-analysis demonstrated a statistically significant increase in SAE risk with PD-1/PD-L1 inhibitor combination therapy (RR=1.39; 95% CI: 1.21–1.60; P<0.001; I²=35.7%). The ARD for SAEs was 11.06% (95% CI: 5.82–16.30%), indicating that adding ICIs to CT was associated with an 11.06% higher risk of serious toxicities requiring clinical intervention (e.g., hospitalization, dose adjustment, or treatment discontinuation). Notably, Schmid et al. reported the highest SAE incidence in the experimental group (43.20%), which may be related to the longer median follow-up duration (39.1 months) in this trial, as immune-related SAEs (irSAEs) often have a delayed onset (22).

Risk of bias

Cochrane risk-of-bias assessment indicated relativey low overall bias across trials, with adequate randomization, allocation concealment, and outcome reporting (Figure 5). Sensitivity analyses excluding high-bias trials did not alter the primary findings.

Figure 5 Risk of bias.

Discussion

The present meta-analysis offers a comprehensive evaluation of the efficacy of PD-1/PD-L1 inhibitors combined with CT in BC, with a particular emphasis on Ate and Pem. Our findings underscore the clinical relevance of immunotherapy-CT combinations, including the favorable survival outcomes associated with Ate combined with nP among PD-L1-positive TNBC patients. Notably, Ate-based regimens (Ate + nP/CT/Bev + CT) achieved a significant OS benefit (HR =0.83; 95% CI: 0.75–0.93; I²=52.8%) compared to placebo + CT, aligning with results from landmark trials such as IMpassion130. Similarly, Pem + CT showed promising efficacy (HR =0.81; 95% CI: 0.69–0.95; I²=0% for OS). However, it is critical to acknowledge that the conclusion regarding Ate + nP’s superiority is derived from indirect comparisons—specifically, a meta-analysis of separate placebo-controlled trials rather than direct head-to-head RCTs comparing Ate + nP with other ICI-CT regimens. This indirect evidence limits the certainty of the regimen’s comparative advantage, and future head-to-head trials are needed to validate these findings (29-31).

Additionally, while our analysis aimed to minimize variability through subgroup stratification, the claim of “low heterogeneity” requires clarification. For key outcomes such as Ate + nP’s PFS benefit, the observed I²=65.4% indicates substantial heterogeneity—contradicting the earlier assertion of low heterogeneity. This heterogeneity may stem from differences in trial design, patient baseline characteristics, or CT dosing, and it should be recognized as a factor that qualifies the generalizability of our results.

A critical gap in the current discussion—and a primary controversy in the field—is the lack of exploration of the interaction between corticosteroids (required for solvent-based paclitaxel) and immunotherapy efficacy. This “steroid effect” is not a statistical anomaly but a biologically meaningful phenomenon: corticosteroids exhibit immunosuppressive properties that can blunt the antitumor activity of PD-1/PD-L1 inhibitors, whereas nP avoids the need for steroid premedication (17,21). This mechanistic difference is likely a major driver of the observed survival benefits of Ate + nP over Ate combinations with solvent-based paclitaxel or other CT backbones. By failing to prioritize this interaction, the analysis overlooks a key rationale for nP’s superiority as an ICI partner in TNBC (32).

Our subgroup analyses revealed that Ate + CT regimens exhibited greater OS improvements (HR =0.74 vs. Pem + CT HR =0.81), suggesting potential differences in drug-specific mechanisms or patient selection criteria. However, the limited number of trials directly comparing Ate and Pem reinforces the need for head-to-head RCTs to validate these findings.

Finally, this meta-analysis has a critical limitation that must be explicitly addressed: the omission of safety data, including irAEs and treatment-related toxicity profiles. A full evaluation of clinical interventions requires balancing efficacy with safety, and the lack of granular toxicity data precludes a comprehensive risk-benefit assessment of the studied regimens. For example, while Ate + nP shows survival benefits, it is unclear whether these benefits are offset by higher toxicity rates—information that is indispensable for clinical decision-making. Future studies should prioritize standardized reporting of toxicity metrics and biomarker-driven patient stratification to optimize therapeutic ratios (33).

In summary, our findings highlight the potential of Ate + nP as a therapeutic option for PD-L1-positive TNBC, but they must be interpreted in the context of indirect evidence, unresolved heterogeneity, and incomplete safety data. Addressing these limitations through head-to-head trials, mechanistic studies of the steroid-ICI interaction, and robust safety reporting will be essential to advancing personalized immunotherapy for BC.

Conclusions

In conclusion, this meta-analysis consolidates evidence supporting Ate + nP as a first-line therapeutic strategy for PD-L1-positive TNBC, while highlighting Pem’s potential in broader BC populations. The findings advocate for biomarker-guided immunotherapy combinations and underscore the necessity of tailored regimens to address BC’s molecular heterogeneity. Future research should focus on elucidating optimal sequencing strategies, validating predictive biomarkers (e.g., PD-L1 expression thresholds), and exploring novel combinations to overcome resistance mechanisms. Such efforts will be pivotal in advancing personalized immunotherapy and improving long-term outcomes for BC patients.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1949/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1949/prf

Funding: This study was supported by grants from the Shaoxing Science and Technology Bureau Project (No. 2024A14010) and Shaoxing University Enterprise Important Horizontal Topic (No. 2024USXH287).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1949/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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