Original Article

Volume 000, Number 000, April 2025, pages 000-000

Anti-Programmed Cell Death-1 Versus Anti-Programmed Death-Ligand 1 (PD-L1) in PD-L1-Negative Advanced Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Lung cancer is a leading cause of cancer-related mortality worldwide, accounting for a significant portion of cancer deaths among both men and women [1]. Non-small cell lung cancer (NSCLC) is the most common subtype, representing approximately 85% of all lung cancer diagnoses [2]. Unfortunately, many patients are diagnosed at an advanced or unresectable stage, limiting treatment options and contributing to its poor prognosis [3]. Despite this, recent advances in immunotherapy have led to a significant improvement in mortality rates over the past 3 years [4].

A key mechanism in the treatment of NSCLC has been the understanding of how these tumors evade immune surveillance. This process is in part, driven by the interaction between the programmed death-ligand 1 (PD-L1) protein which is expressed on the surface of tumor cells and the programmed cell death-1 (PD-1) receptor found on effector T cells. This interaction effectively suppresses the cytotoxic activity of T cells, allowing tumor cells to escape immune detection and destruction. By blocking this interaction, immune checkpoint inhibitors (ICIs) disrupt the immune-suppressive environment created by the tumor during the priming phase of the cancer-immunity cycle [5]. ICIs are divided into two main subclasses: those targeting PD-1 or PD-L1 and those targeting cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) [6, 7]. PD-1 is a receptor expressed on the surface of multiple immune cell types, including T cells, B cells, and natural killer (NK) cells. One of its ligands, PD-L1, is present in different cell types including tumor cells and participates in the inhibition of previously activated T cells. CTLA-4 is present on the surface of CD4-positive and CD8-positive lymphocytes and binds to T-cell-costimulatory factors on the surface of antigen-presenting cells (APCs). CTLA-4 binding reduces interleukin-2 (IL-2) production and T-cell proliferation [6]. Checkpoint blockade using ICIs overcomes this tumor-mediated immune inhibition, leading to a proinflammatory tumor microenvironment which potentially increases anti-cancer immune effect [5, 8-10]. Recent studies focused on their role in conversion of initially unresectable advanced NSCLC into respectable disease after chemoimmunotherapy [11, 12]. Approved ICIs include anti-PD-1 antibodies (pembrolizumab, nivolumab, and cemiplimab), anti-PD-L1 (atezolizumab, avelumab, and durvalumab) and anti-CTLA-4 (ipilimumab and tremelimumab) [7].

Immunotherapy was initially approved for the subset of patients in whom the PD-L1 expression was high. Clinical evidence has shown that ICIs significantly improve outcomes for patients with advanced NSCLC when compared to traditional platinum-based chemotherapy [13]. These findings have driven the use of PD-L1 expression as a biomarker to guide treatment decisions [10, 14]. However, the clinical landscape is more complex for patients whose tumors are classified as PD-L1-negative (PD-L1 expression < 1%). Subsequent studies have shown that anti-PD-1 and anti-PD-L1 therapies can still provide benefits in PD-L1-negative NSCLC, when added to chemotherapy, in terms of both overall survival (OS) and progression-free survival (PFS) [13]. The reported prevalence of PD-L1 expression below 1% in NSCLC patients varies across clinical trials, with estimates ranging from one-third to nearly half of all cases [10]. Moreover, recent studies have highlighted the potential for combining PD-L1 inhibitors with other treatments, such as bevacizumab and chemotherapy, to enhance efficacy without significantly increasing adverse events [8].

Despite these promising findings, questions remain regarding the differential efficacy of anti-PD-1 and anti-PD-L1 agents in PD-L1-negative NSCLC patients. While both classes of ICIs target the same immune pathway, they have distinct mechanisms of action and pharmacological properties [14].

It is still unclear whether one class of drugs offers superior outcomes in PD-L1-negative patients. Furthermore, while no significant differences in side effects have been observed between these therapies in small cell lung cancer [15], the impact of these therapies in PD-L1-negative NSCLC patients remains underexplored.

This meta-analysis aimed to study the relative efficacy of PD-L1 inhibitors and PD-1 inhibitors in PD-L1-negative advanced NSCLC patients, which could help inform treatment decisions and guide future research efforts in developing more effective, personalized treatment strategies for patients with advanced NSCLC.

The systematic review and meta-analysis study was performed following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 guidelines [16].

A systematic search of published randomized controlled trials (RCTs) was conducted in July 2024 using MEDLINE (host: PubMed, Scopus, and Google Scholar). Inclusion criteria comprised RCTs of any phase involving patients with advanced NSCLC in which participants received either anti-PD-1 (pembrolizumab, nivolumab, toripalimab, cemiplimab, tislelizumab, and camrelizumab) or anti-PD-L1 (atezolizumab, duravlumab, and avelumab) either alone or in combination with other systemic therapy against a respective standard of care therapy (SOC), availability of outcome data; namely progression-free survival (PFS) and/or overall survival (OS) reported based on PD-L1 expression status; specifically for the subset of patients with negative PD-L1 expression. Ongoing trials, trials including only patients with positive PD-L1 expressions, and trials which did not include the prespecified reported outcomes were excluded from this study. When several versions of the same RCTs were identified, we included the most recent version that included the predefined outcome data. Each study was screened separately by two independent investigators. Discrepancy in date was resolved by a third investigator. Institutional Review Board approval is not applicable for systematic review and meta-analysis.

After RCTs were identified, data extraction was performed by two independent investigators. Extracted data comprised the name and the date of publication of each included trial, the histological subtype (squamous vs. non-squamous), treatment line (first line vs. later line), drug subclass (anti-PD-1 vs. anti-PD-L1), experimental arm and control arm of each included trial, the sample size of the PD-L1-negative cohort, and the total sample size of each included trial. For outcome measures, we extracted the hazard ratio (HR) and related 95% confidence intervals (CIs) for PFS and/or OS for the subset of patients who had negative PD-L1 expression as defined by each individual trial.

The HRs for PFS and OS for the PD-L1-negative cohort of patients in each included study were pooled using the generic inverse variance. Random effect modeling was utilized due to both clinical and statistical heterogeneity amongst included trials. Comparisons between PD-1 and PD-L1 inhibitors were performed using subgroup analysis as described by Deeks [17]. Analyses were performed using Review Manager V.5.4.1 (The Cochrane Collaboration, Copenhagen, Denmark). Variation in effect size was examined using subgroup analyses; specifically, we assessed the association of effect size with treatment line (first line vs. later line), histological subtype (squamous vs. non-squamous), and according to the used anti-PD-1/PD-L1 agent (pembrolizumab, nivolumab, atezolizumab, and durvalumab). Pairwise comparisons of pooled data were then performed using WINBUGS within Microsoft Excel (Microsoft Corp., Redmond, WA, USA). Statistical significance was defined as P < 0.05. We did not apply corrections for multiple significance testing.

The study selection scheme is shown in Figure 1. Twenty-three trials were included in the meta-analysis. PD-L1 testing was performed in all participants, where a total of 4,548 PD-L1-negative patients were identified in this study, representing 33% of all participants in included clinical trials. The platforms used for PD-L1 testing and the expression used to describe the population of patients who showed no PD-L1 expression varied amongst the trials involving different agents; however, PD-L1-negative tumors were defined in all included trials as the tumors that do not explicit any inducible expression of PD-L1 by tumor or immune infiltrating cell.

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Figure 1. Study selection schema.

OS data were available from 21 out of the 23 included trials, while PFS data were available from 20 trials. Amongst the included trials, 18 trials were undertaken in the first-line sitting, of which 11 trials included anti-PD-1. Twelve trials included patients with non-discriminatory NSCLC histological subtypes. Out of the remaining 11 trials, seven were devoted to the non-squamous subtype. Characteristics of included studies are reported in Table 1 [18-40].

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Table 1. Characteristics of Included Clinical Trials

Funnel plot to assess publication bias is demonstrated in Figure 2a, b. Heterogeneity of the samples of the 14 studies that included anti-PD-1 was tested using Chi-square (Q test = 9.21, df = 11, P = 0.60), which means no significant heterogeneity as demonstrated in Figure 2c. On the other hand, heterogeneity of the nine trials studying PD-L1 testing (Chi-square (Q test) = 15.56, df = 8, P = 0.05) was significant as demonstrated in Figure 2d.

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Figure 2. Funnel plot comparing the precision of individual studies in (a) anti-PD-1 and (b) anti-PD-L1. The y-axis represents the standard error. The x-axis displays the study estimated effect size (hazard ratio). Forrest plot comparing the heterogeneity of the included trials for the two subclasses (c) anti-PD-1 and (d) anti-PD-L1.PD-1: programmed cell death-1; PD-L1: programmed death-ligand 1.

A summary of the main and subgroup data results is shown in Tables 2 and 3.

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Table 2. Results of the Differential Efficacy Between Anti-PD-1 Over Anti-PD-L1 in PD-L1-Negative Advanced NSCLC Patients

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Table 3. Association Between Histological Subtype and Outcomes

Overall, the addition of anti-PD-1 was associated with better OS in PD-L1-negative advanced NSCLC patients (HR: 0.75, 95% CI: 0.67 - 0.83, P < 0.01) as shown in Figure 2c, while the addition of anti-PD-L1 inhibitors showed neither a significant nor meaningful improvement in OS (HR: 0.90, 95% CI: 0.78 - 1.05, P = 0.18) as shown in Figure 2d. Compared to anti-PD-L1 agents, anti-PD-1 inhibitors showed better OS in PD-L1-negative patients (HR: 0.83, 95% CI: 0.67 - 0.99, P = 0.01).

For PFS, pooling of individual trials showed a higher magnitude of effect for PD-1 compared to PD-L1 inhibitors (HR: 0.69, 95% CI: 0.63 - 0.76, P < 0.01 versus HR: 0.83, 95% CI: 0.74 - 0.94, P < 0.01). Again, these differences were statistically significant in pairwise comparisons (HR: 0.83, 95% CI: 0.71 - 0.97, P = 0.02).

The differential benefit of anti-PD-1 over anti-PD-L1 inhibitors was found to be more pronounced if the agents were used in the first-line setting (pairwise comparison HR: 0.79, 95% CI: 0.66 - 0.93, P = 0.01). In contrast, there was no statistically significant difference in OS between the two subclasses if used during the later lines of therapy (pairwise comparison 1.13; 95% CI: 0.82 - 1.55, P = 0.45) as shown in Table 2.

Similar trends albeit with lower magnitude were observed for the PFS endpoint. There was a non-significant association with greater improvement in PFS with PD-1 inhibitors compared with PD-L1 inhibitors when used in the first line (pairwise comparison HR: 0.84, 95% CI: 0.68 - 1.03, P = 0.09). No effect was seen for later lines (pairwise HR: 1.06, 95% CI: 0.78 - 1.43, P = 0.70) as shown in Table 2.

Among trials that explored specific histological subtypes of NSCLC, the addition of anti-PD-1 agents was associated with a significant improvement in OS among the two histological subtypes, squamous (HR: 0.60, 95% CI: 0.47 - 0.78, P < 0.01) and non-squamous (HR: 0.79, 95% CI: 0.65 - 0.95, P = 0.01). Conversely, the utilization of anti-PD-L1 agents showed non-significant effects in the two histological subtypes (HR: 0.87, 95% CI: 0.67 - 1.13 in squamous and HR: 0.81, 95% CI: 0.61 - 1.07 in non-squamous) as shown in Table 3. Due to the small number of studies available for review, pairwise comparisons were not performed.

Based on the results of multiple landmark trials, ICIs were approved as monotherapy, in PD-L1 high NSCLC patients, or combined with chemotherapy for the remainder of patients [18]. Several trials were conducted to examine the benefit of adding anti-PD-1 or anti-PD-L1 into the treatment paradigm for PD-L1-negative NSCLC [13], a group which represents a considerable proportion of the whole patients’ spectrum. Both anti-PD-1 and anti-PD-L1 have different specific properties in terms of binding to different targets, where efficacy may vary based on the site of inhibition [7]. However, little is known about the differential efficacy of one class over the other.

In our meta-analysis comparing the efficacy of anti-PD-1 agents with that of anti-PD-L1 agents, we observed a significantly greater magnitude of improved OS with anti-PD-1 compared with anti-PD-L1. This effect appeared to apply only to treatment delivered in the first-line sitting. We also extended the comparison to cover the different histological subtypes (when reported), and this analysis proved a consistent differential benefit of anti-PD-1 over anti-PD-L1 independent of the histological subtype. Of note, while effect sizes were in a similar direction for PFS, differences were not statistically significant.

This study provides clinicians with valuable insights into which ICI class is more effective in first-line settings in PD-L1-negative NSCLC by observing a statistically significant OS benefit with anti-PD-1 therapies, which is an impactful endpoint even if PFS differences were not significant. Moreover, by examining the impact on various histological subtypes, generalizability of the findings is further enhanced.

This study has limitations. First, the relatively small number of included trials may have an impact on the accuracy of our analysis and will have reduced power to observe statistically significant results especially for some subgroup analyses. In addition, in all allocated trials, anti-PD-1/ PD-L1 therapies were used either alone or in combination with SOC systemic therapies comprising different forms of chemotherapeutic agents. Thus, a significant degree of heterogeneity between included interventions was noted. We did utilize methods to address this heterogeneity (e.g., random effects models), but residual uncertainty will likely remain. Third, a degree of selection bias is expected as we could not include all approved anti-PD-1/PD-L1 in this analysis. For example, the efficacy of avelumab (anti-PD-L1) was only studied in the PD-L1-positive patients and therefore, there were no available outcome data for the PD-L1-negative advanced NSCLC patients. Moreover, recent studies have increasingly emphasized the use of anti-PD-1 therapies rather than anti-PD-L1, which could potentially influence the outcomes of this metanalysis. However, despite these limitations, this study may identify future research in the same field studying the differences between anti-PD-1 and anti-PD-L1, not just in NSCLC, but in other disease sites where both PD-1 and PD-L1 inhibitors are in use.

The efficacy of both ICI subclasses targeting PDL pathway was previously studied regardless of PD-L1 expression in advanced NSCLC, particularly in squamous and low PD-L1 expression. Possible interclass differences favoring anti-PD-1 was highlighted [41]. Also, differences between the two subclasses were studied in the setting of head and neck squamous cell carcinoma (SCC) without the clarification of PDL receptor status and there was a significant difference between the two favoring anti-PD-1 in metastatic disease in which anti-PD-1 lowered mortality [42]. However, up until this meta-analysis, little was known about their relative effect in PD-L1-negative advanced NSCLC patients and their different subclasses.

The discordance between PFS and OS is observed occasionally with ICIs and other treatments that may affect tumor growth kinetics instead of imposing a direct cytotoxic effect on cancer cells, which may hinder the observed benefits in PFS while the differential benefit in OS is still significant [43]. This includes the potential observation of pseudo-progression which may impact on PFS data. The US Food and Drug Administration (FDA) has examined several trials in which an OS benefit was demonstrated without significant improvements in intermediate endpoints (PFS or response rate) after which several ICIs were granted approvals for NSCLC, head and neck SCC, and melanoma [43-47]. It is noteworthy that PD-1 receptor expressed on immune cells has two ligands (PD-L1/PD-L2). The precise role of PD-L2 in cancer immunity remains incompletely understood. However, unlike anti-PD-L1, anti-PD-1 neutralizes both PD-L1 and PD-L2 [19-21], and this might explain the improved differential efficacy in anti-PD-1 over anti-PD-L1. Among the 23 trials analyzed, the POPLAR trial was the only study to assess PD-L2 status and atezolizumab (an anti-PD-L1) was still effective in tumors with high expressions of PD-L2 [22].

Further studies with larger sample size might add a huge value to the generalizability of the conducted results, especially those studying the effect of ICIs in PD-L1-negative advanced NSCLC in the first line without chemoradiation that might provide some answers to the real effect without any confounders either by seroconversion to PD-L1-positive after chemoradiation [48], or the lack of difference in PFS which was partially justified by pseudoefficacy. Also, inclusion of emerging studies that highlights the previously non-studied ICIs of PD-L1-negative NSCLC will add further external validity to the results.

Finally, studying PD-L2 status and investigating other potential biomarkers that contribute to tumor microenvironment and immune escape, including tumor mutational burden (TMB) which correlates with the response to anti-PD-1/anti-PD-L1 [49, 50], interferon (IFN)-γ-related gene signatures in non-resectable melanoma although studies failed to correlate the level in NSCLC [51], and STK11/KEAP1 mutations which correlate with poor response to anti-PD-1 and anti-PD-L1 [52]. Decline in the level of circulating tumor DNA (ctDNA) in advanced solid tumors is associated with substantial improvement in outcome and response and might guide treatment plans [53], and finally, the concept of heterogeneity immune checkpoint signature (HIS) which might explain the difference in response to ICIs according to the size of the solid tumor [54].

In summary, among patients with PD-L1-negative advanced NSCLC, it appears that anti-PD-1 inhibitors are associated with greater magnitude improvement in OS compared to anti-PD-L1 inhibitors, especially if used as first-line treatment. There was no apparent influence of histological subtype. The lack of confirmatory effect on PFS means that these data need to be validated, preferably in large real-world studies.

Anti-PD-1 therapies are associated with better OS than anti-PD-L1 in PD-L1-negative advanced NSCLC, a finding influenced by the included trials which were performed in the first-line sitting.

This analysis proved a consistent differential benefit of anti-PD-1 over anti-PD-L1 independent of the histological subtype in advanced patients with PD-L1-negative NSCLC. Of note, while effect sizes were in a similar direction for PFS, differences were not statistically significant.

These results could help inform treatment decisions and guide future research efforts in developing more effective, personalized treatment strategies for patients with advanced NSCLC.

Acknowledgments

We would like to thank the reviewers for all the valuable comments and suggestions which helped us to improve the quality of the manuscript.

Financial Disclosure

None to declare.

Conflict of Interest

Laith Al-Showbaki: consulting from Novartis, AstraZeneca, and Janssen. Eitan Amir: consulting from Gilead and Novartis.

Informed Consent

Not applicable.

Author Contributions

Conceptualization: Laith Al-Showbaki. Data curation: Malak Al-Kasasbeh, Karem Jbarah, and Saif Yamin. Formal analysis: Laith Al-Showbaki. Methodology: Laith Al-Showbaki. Writing - original draft: all authors. Writing - review and editing: all authors.

Data Availability

The authors declare that data supporting the findings of this study are available within the article.

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