Traditionally, the standard first-line treatment for metastatic small-cell lung cancer has been platinum-based chemotherapy (carboplatin or cisplatin) in combination with etoposide.1–3 Since the introduction of immune checkpoint inhibitors, chemoimmunotherapy regimens combining platinum–etoposide with PD-L1 inhibitors such as atezolizumab have become part of the standard of care in this setting. Despite response rates of 60% to 65%, limited progress has been achieved in over two decades; outcomes remain poor, with a median overall survival of approximately 10 months.3,4

Small-cell lung cancer is characterized by a high mutation rate, suggesting that these tumors may be immunogenic and could respond to immune checkpoint inhibitors.5–7 The addition of immunotherapy to chemotherapy may enhance antitumor immunity and improve outcomes beyond those achieved with current treatment options. Indeed, clinical activity of immunotherapy has been observed in patients with relapsed or metastatic small-cell lung cancer in early-phase trials.8–12 However, a phase 2 single-arm study of pembrolizumab maintenance therapy and a phase 3 study of ipilimumab plus chemotherapy did not demonstrate improved efficacy over chemotherapy alone as first-line treatment for extensive-stage small-cell lung cancer.12,13 These setbacks underscored the challenge of translating immunotherapy benefits to the frontline setting, but further investigation continued.

Atezolizumab (Tecentriq, F. Hoffmann–La Roche/Genentech) is a humanized monoclonal antibody targeting programmed death-ligand 1 (PD-L1), which inhibits PD-L1–PD-1 and PD-L1–B7–1 signaling, thereby restoring tumor-specific T-cell immunity.14,15 In a phase 1 trial, atezolizumab monotherapy showed an acceptable safety profile and promising durable responses in patients with relapsed or refractory small-cell lung cancer.10 Subsequently, the phase III IMpower133 trial provided a breakthrough: atezolizumab plus chemotherapy significantly improved survival as first-line therapy. In IMpower133, atezolizumab in combination with platinum–etoposide achieved a median overall survival of 12.3 months versus 10.3 months with chemotherapy alone (HR = 0.70; 95% CI 0.54–0.91; p = 0.007), and a median progression-free survival of 5.2 months versus 4.3 months, respectively (HR = 0.77; 95% CI 0.62–0.96; p = 0.02).14 This was the first regimen in decades to show a survival benefit in extensive-stage SCLC,15 leading to regulatory approval of atezolizumab in the first-line setting and establishing a new standard of care.

However, real-world studies are needed to evaluate the effectiveness of chemo-immunotherapy under routine clinical conditions and to determine whether outcomes are comparable to those observed in clinical trials.16 Initial findings are encouraging. For example, a large retrospective study reported that survival outcomes with first-line atezolizumab plus chemotherapy in routine practice were reproducible and similar to those from IMpower13317 – but further large-scale, long-term data will confirm the generalizability of these benefits.16

The primary objective of this study was to assess the effectiveness and safety of atezolizumab in combination with platinum–etoposide chemotherapy in real-world clinical practice, by evaluating median OS and PFS and comparing the results with those obtained in the IMpower133 clinical trial. The secondary objective was to analyze clinical factors associated with survival. These analyses will be exploratory and descriptive in nature.

This was a retrospective, observational, multicenter study of patients with metastatic small-cell lung cancer (SCLC) who received first-line atezolizumab plus platinum–etoposide chemotherapy between November 2021 and March 2025.

To minimize immortal time bias in the comparison of patients who completed induction, we prespecified a landmark analysis. The landmark time (t) was set at 2.8 months (∼12 weeks) from treatment initiation, corresponding to the intended completion of four induction cycles (q3w). All landmark analyses reset time zero at t*.

Eligible patients were adults (≥18 years) with histologically confirmed stage IV or metastatic SCLC, no prior systemic therapy for metastatic disease, and complete clinical records. Patients with incomplete data or a concurrent active malignancy were excluded.

Collected variables included demographics (age, sex), clinical data (ECOG performance status, smoking history, comorbidities, metastatic sites), and treatment details (start and end dates, cycles completed, duration, reason for discontinuation, adverse event [AE] type and severity). Treatment regimens, including the atezolizumab dose, were recorded.

Baseline characteristics were summarized using descriptive statistics: categorical variables as frequencies and percentages, continuous variables as medians (interquartile range, IQR) or means (standard deviation, SD).

This study was designed and reported in accordance with the STROBE statement (Strengthening the Reporting of Observational Studies in Epidemiology).

In our study, the median OS was 9.4 months (95% CI: 7.0–13.1), somewhat shorter than the 12.3 months (95% CI: 10.8–15.9) reported in IMpower133.14 This difference may reflect distinct baseline profiles, particularly the inclusion of patients with poorer performance status—17.1% had ECOG ≥ 2, a group excluded from IMpower133, which enrolled only ECOG 0–1. Other real-world factors, such as higher comorbidity burden and less frequent imaging, may also have contributed.

Conversely, median PFS was longer in our series (7.2 months; 95% CI: 6.5–8.6) vs 5.2 months (95% CI: 4.4–5.6) in IMpower133,14 possibly due to practices like continuing immunotherapy beyond radiologic progression in selected patients or differences in imaging schedules outside trial settings.

Our findings align with other observational studies. Falchero et al. reported median OS and PFS of 11.3 and 5.2 months, respectively; only 11% of their cohort had ECOG ≥ 2 vs 17.1% in ours, which may partly explain their superior OS.17 The Italian MAURIS study, on a broadly similar population, showed median OS of 10.7 months (95% CI: 9.9–13.7) and PFS of 5.5 months (95% CI: 5.3–5.8).18

In contrast, Shiono et al. documented longer OS (15.9 months; 95% CI: 11.8–18.3) and PFS (5.4 months; 95% CI: 4.6–5.9), likely related to patient selection, age distribution, and follow-up methods.19 Similarly, Lee et al. reported OS and PFS of 12.0 and 4.6 months, respectively, underscoring the heterogeneity of real-world populations.20

Our ORR was also notably higher (81.7%; 95% CI: 70.1–89.4) than in IMpower133 (60.2%). This difference may be influenced by more heterogeneous response evaluation criteria in real-world settings and the absence of mandatory radiologic confirmation, unlike the strict protocol-driven approach of clinical trials. Despite these variations, the median treatment duration in our study (4.4 months) was comparable to that observed in IMpower133, suggesting similar exposure to the therapeutic regimen.14

These findings highlight the value of observational studies in complementing clinical trial data, offering a more pragmatic view of treatment performance in routine oncology practice.

Baseline functional status, as measured by ECOG, was associated with survival. Patients with ECOG ≥ 2 had significantly shorter PFS and OS than those with ECOG 0–1. Since IMpower133 excluded ECOG ≥ 2 patients, our findings add real-world context for this regimen in frailer groups. In the IMpower-133-like population (PS 0–1), median OS and PFS were 11.9 and 5.3 months, respectively.14 Similar results from other studies confirm ECOG ≥ 2 is linked to higher risks of progression and death.21,22,17 Masubuchi et al. also found that good PS at relapse predicts longer survival, reinforcing ECOG ≥ 2 as a marker of poor outcomes and the need for selective treatment in vulnerable SCLC patients.23

Age also appeared to impact OS, with significantly poorer outcomes in patients ≥ 65 years in our analysis. No statistically significant differences in PFS were found between age groups. Age-related survival effects vary. Shiono et al. reported similar survival for patients ≥ 70 vs < 70 years and no differences within elderly subgroups.19 Noivo et al. found no association between age and survival or response rate,21 while Choi et al. found no prognostic value of age for PFS or OS.22 Chen et al. showed similar benefit from atezolizumab in those > 65.24 Wang et al. associated increasing age with better PFS, but not OS.25 In contrast, Falchero et al. identified age as a significant OS predictor, with patients > 65 showing shorter survival (median OS 9.8 vs 13.2 months; HR = 1.26, p = 0.03).17 Overall, most studies do not show a consistent negative effect of age.

In adjusted models, sex was not estimable due to the absence of women among complete cases; unadjusted summaries showed no clear differences. A recent Portuguese study found no significant differences in PFS (p = 0.828) or OS (p = 0.782) by sex.21 Similarly, several studies did not associate sex with survival.19,22,25

In multivariable models, hepatic metastases were an independent predictor of shorter PFS, but showed no significant association with OS. This aligns with univariable analyses, which also showed worse PFS—and, at the unadjusted level, worse OS—in patients with hepatic metastases. In the IMpower133 trial, patients with liver metastases had lower OS (9.3 vs 16.8 months) and PFS (4.3 vs 5.6 months).14 Musicco et al. found significant OS differences between patients with and without liver metastases (6.6 vs 15.9 months; p < 0.001).26 In contrast, Masubuchi et al. and Wang et al. reported no association with PFS, likely due to small samples.23,25

In our cohort, baseline brain metastases did not significantly influence survival. This may relate to the small subgroup or confounders such as prior radiotherapy or selection bias. Falchero et al. similarly found no OS difference (9.9 vs 11.6 months; p = NS), though their multivariate analysis identified brain metastases as a predictor of shorter PFS (HR 1.3; 95% CI: 1.0–1.6; p = 0.02). Brain metastases were more frequent in their cohort (27%) than in ours (10.5%). Likewise, an exploratory IMpower133 analysis (∼8% with brain metastases) found no OS or PFS differences (HR 1.07; 95% CI: 0.47–2.43).14

Treatment duration did not independently influence survival in our analysis. Completion of ≥4 cycles (full induction) was not associated with differences in post-landmark outcomes. In contrast, Musicco et al. and Wang et al. observed longer OS (14.1 vs 4.7 months, p < 0.001) and improved PFS and OS, respectively, in patients completing all induction cycles.25,26 However, both studies analyzed treatment duration without accounting for immortal time bias, which may overestimate the survival benefit in patients able to receive more cycles. By contrast, our landmark approach suggests that longer treatment duration likely reflects better baseline prognosis or better treatment tolerance rather than a causal effect of additional cycles.

Both univariate and multivariate analyses identified baseline ECOG performance status as the strongest prognostic factor in patients with extensive-stage small-cell lung cancer treated with chemoimmunotherapy. In univariate analysis, ECOG ≥2, age ≥ 65 years, and hepatic metastases were all significantly associated with increased mortality. After multivariate adjustment, ECOG ≥2 and age ≥ 65 years remained independently associated with worse overall survival, underscoring the impact of baseline functional and physiological status on outcomes.

For progression-free survival, ECOG ≥2 was consistently associated with a higher risk of progression or death in both univariate and multivariate models, while age ≥ 65 years was not significantly associated with survival after adjustment. The presence of brain metastases did not show a meaningful association with either outcome. Hepatic metastases emerged as a relevant prognostic factor, being significantly associated with shorter PFS, consistent with their established negative prognostic impact in SCLC.

Taken together, these results highlight the prognostic value of baseline functional status and the adverse impact of hepatic involvement, while suggesting that chronological age alone has a more pronounced influence on overall rather than progression-free survival.

Our sensitivity analyses (IPTW-adjusted and landmark models) supported the robustness of these associations but do not allow the definition of formal selection criteria or specific patient subgroups expected to obtain “optimal” health outcomes with atezolizumab-based chemoimmunotherapy.

In terms of safety, the profile of the most frequent adverse events in the IMpower133 trial was similar to that of our cohort, with hematologic toxicity being the most common, followed by gastrointestinal toxicity.14 In the clinical trial, the incidence of adverse events was slightly higher than in our cohort (94.9% vs. 80.3%), as was the incidence of immune-mediated adverse events (39.9% vs. 7.9%), and the proportion of treatment-related deaths (1.5% vs. 0%). This could be related to the smaller sample size, which limits the detection of rare events. In addition, differences in study design, patient selection, and duration of follow-up may have influenced the identification and recording of toxicity. In actual clinical practice, adverse events are often less systematized and reported than in clinical trials.

This study has several limitations. Its retrospective observational nature and the absence of a control group preclude formal causal inference and leave room for residual confounding and selection bias, despite the use of multivariable Cox models, IPTW and a prespecified landmark time. The relatively small sample size, particularly in subgroups such as patients with ECOG ≥2 or brain metastases, reduces the statistical power to detect meaningful differences. Subgroup and multivariable analyses were not adjusted for multiplicity and should be interpreted descriptively and as hypothesis-generating. Radiological assessments were performed in routine clinical practice, which may introduce variability in response evaluation. Finally, no prospectively specified, registered protocol or statistical analysis plan was available; although the main endpoints and key covariates were predefined, some analyses were necessarily data-driven, and the results should be viewed as exploratory.

This real-world study describes the effectiveness and safety of atezolizumab plus platinum–etoposide in extensive-stage SCLC, showing high response rates and acceptable survival in a heterogeneous routine-practice population. Median PFS was similar to that reported in IMpower133, whereas median OS was numerically shorter, which is consistent with the inclusion of patients with poorer performance status (ECOG ≥2) and other real-world complexities. Baseline ECOG performance status and older age were independently associated with worse overall survival, while hepatic metastases were an independent predictor of shorter progression-free survival. Sex showed no clear effect (not estimable in adjusted models), and brain metastases were not significantly associated with outcomes. In a prespecified landmark analysis, completing ≥4 induction cycles was not independently associated with post-landmark PFS or OS, suggesting that longer treatment duration may primarily reflect better baseline prognosis or treatment tolerance.

These findings add pragmatic evidence on the use of atezolizumab-based chemoimmunotherapy in everyday oncology practice and help to refine clinical prognostic factors in extensive-stage SCLC. However, the absence of a randomized control group and the lack of formal trial emulation mean that our results should be interpreted as complementary to, rather than validating, the IMpower133 trial.

This study provides real-world evidence on the effectiveness and safety of atezolizumab in combination with platinum and etoposide for patients with metastatic small-cell lung cancer. It complements clinical trial data by confirming its applicability in routine practice and identifying baseline clinical variables associated with treatment outcomes. These findings enhance the understanding of patient profiles that may benefit most, contributing to the advancement of personalized oncology and more accurate therapeutic decision-making.

The findings have relevant implications for clinical practice, supporting the integration of atezolizumab-based regimens as a standard option in real-world settings. They also highlight the importance of identifying predictive factors to refine patient selection and improve outcomes. For research, the study opens avenues for further exploration of biomarkers and treatment optimization strategies. From a healthcare policy and hospital pharmacy perspective, the data support informed resource allocation and the rational use of immune-oncology therapies, aligning with efficiency and sustainability goals.

Laura Moñino Domínguez: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Laura Amaro Álvarez: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation. Alicia Aguado Paredes: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation. Isabel María Carrión Madroñal: Visualization, Validation, Supervision, Methodology, Conceptualization.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.