Abstract
Backgrounds
Little is known about whether prior chemoimmunotherapy (CTI) affects the efficacy of sequential treatment in patients with extensive-stage (ES) small-cell lung cancer (SCLC). Our preliminary study explored what kinds of biomarkers are associated with the outcomes of CTI followed by amrubicin (AMR) as a second-line treatment.
Methods
We retrospectively evaluated 45 patients with relapsed SCLC who underwent CTI followed by AMR monotherapy from December 2019 to December 2023. Clinical data and inflammatory and nutritional factors, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, systemic immune-inflammation index, prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), and Glasgow prognostic score before initial treatment of AMR, were analyzed to determine prognostic predictors. Survival analyses of variables were performed using the COX proportional hazards model.
Results
The objective responses for prior CTI and AMR were 40.5% and 60.0%, respectively. Progression-free survival (PFS) and overall survival (OS) after AMR were closely related to the NLR and ALI (or PNI). However, there were no significant factors associated with AMR response. Univariate analysis identified NLR and ALI as significant predictors of PFS, and the presence of prior immune checkpoint inhibitor (ICI) maintenance, NLR, ALI, and duration from ICI to progressive disease as significant predictors of OS. Multivariate analysis demonstrated that the NLR was an independent prognostic factor for predicting worse PFS and OS after AMR administration.
Conclusions
NLR was identified as a significant biomarker for predicting AMR outcomes after prior CTI in patients with ES-SCLC.
Keywords: Extensive-stage small-cell lung cancer (ES-SCLC), chemoimmunotherapy (CTI), amrubicin (AMR), neutrophil-to-lymphocyte ratio (NLR), predictive marker
Highlight box.
Key findings
• Neutrophil-to-lymphocyte ratio (NLR) was a significant predictor for chemotherapeutic resistance to amrubicin (AMR) after prior chemoimmunotherapy (CTI) in patients with extensive-stage small-cell lung cancer (ES-SCLC).
What is known and what is new?
• Inflammatory and nutritional markers were closely associated with predictors after AMR after initial CTI for patients with ES-SCLC.
• The presence of prior immune checkpoint inhibitor (ICI) and the duration from ICI administration to disease progression may influence the outcome after AMR treatment.
• NLR affected the therapeutic outcomes after not only ICI treatment but also sequential chemotherapy.
What is the implication, and what should change now?
• The continuation or sensitivity of ICI treatment can improve the therapeutic efficacy of AMR, although it remains unclear about the reasonable mechanism. Further investigation is needed to discover a promising biomarker for predicting the outcome of AMR followed by tarlatamab, a bispecific T-cell-engager immunotherapy.
Introduction
Extensive-stage (ES) small-cell lung cancer (SCLC) is identified as a progressive and dismal disease among patients with lung cancer. After the failure of initial chemoimmunotherapy (CTI), most patients experience a life-threatening situation. Amrubicin (AMR) is widely administered in Japan as sequential treatment after platinum-based chemotherapy with a programmed death ligand-1 (PD-L1) antibody. AMR inhibits DNA topoisomerase II. However, the therapeutic efficacy of AMR displays a median progression-free survival (PFS) of 4.1 months and an objective response rate (ORR) of 31.1%, providing only a limited survival benefit (1). Several studies have reported that the efficacy of docetaxel plus ramucirumab or docetaxel after immune checkpoint inhibitors (ICIs) is significantly higher than that of regimens without prior ICIs (2,3). Although it remains unclear why prior immunotherapy improves the efficacy of sequential cytotoxic agents, immunotherapy may lead to a chemotherapy-sensitive response in the tumor immune environment (4). Several reports have described that prior CTI does not enhance the therapeutic effect of AMR on ES-SCLC, and the ORR and median PFS for AMR range from 29.2% to 46.0% and from 2.9 to 3.8 months, respectively (5-7). However, these reports did not explore predictive markers of AMR after ICIs (5-7). Further studies are needed to identify meaningful biomarkers to predict the clinical benefits of AMR after prior CTI.
As clinical markers to predict the outcome of ICI treatment, inflammatory and nutritional markers, such as the neutrophil-to-lymphocyte ratio (NLR) and prognostic nutritional index (PNI), have already been described by clinical researchers (8,9). The prognostic role of topotecan as a topoisomerase inhibitor as well as AMR was investigated in SCLC patients, and the inflammatory and nutritional index was identified as biomarker to predict response and treatment efficacy (10). In their study, approximately 70% of the patients received chemotherapy or CTI as a first-line setting (10). The biological activity of SCLC is progressive and expanding to many organs, thus, most patients of SCLC easily get worse conditions after failure of initial treatment. As these inflammatory and nutritional factors are associated with the general condition of the patients, these biomarkers, including performance status (PS) may be investigated as prognostic markers after any treatment.
Based on this background, we conducted a retrospective study to identify useful markers for predicting the outcome of AMR treatment after prior CTI in patients with relapsed ES-SCLC. We present this article in accordance with the REMARK and STROBE reporting checklists (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-214/rc).
Methods
Patients
From December 2019 to December 2023, 110 patients with ES-SCLC were treated with platinum-based chemotherapy, including etoposide and PD-L1 antibodies, at our institution. The inclusion criteria of this study were as follows: (I) pathologically confirmed SCLC; (II) having recurrent sites after failure of prior CTI; (III) PS of 0–2; (IV) receiving AMR as second-line treatment after prior CTI; and (V) receiving blood testing just before initial administration of AMR. The exclusion criteria were not suitable for the administration of AMR, not available for adequate clinical data, and having severe comorbidities. Of the 110 patients, 4 patients continue to receive first-line CTI without any recurrence or death event, and 56 patients did not receive any chemotherapy because of best supportive care. Therefore, 60 patients received any chemotherapy as subsequent therapy. Of 60 patients, 15 patients were treated with platinum-based chemotherapy or any chemotherapy aside from AMR. Finally, 45 received AMR as a second-line treatment after failure of CTI. Some of these cases have been previously reported (11,12). The patient’s consort diagram was presented in Figure 1. Clinical data were extracted from medical records. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Institutional Ethics Committee of the International Medical Center at Saitama Medical University (approved No. 20-125, 2023-033). The requirement for written informed consent was waived by the Ethics Committee of Saitama Medical University owing to the retrospective nature of the study (13).
Figure 1.
Patient’s consort diagram in this study. CTI, chemoimmunotherapy; SCLC, small-cell lung cancer.
Therapeutic schedule and evaluation
AMR was intravenously administered at a dose of 25–40 mg/m2 on days 1–3 every 22 or 29 days. Granulocyte colony-stimulating factor was administered as a prophylaxis for neutropenia at the direction of the attending physician; however, its administration was not mandatory. Complete blood counts, biochemical testing, physical examinations, and adverse effects were evaluated according to the chief physician’s determination. Toxicity was graded based on the Common Terminology Criteria for Adverse Events, version 5.0. Tumor response was assessed based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (14).
Assessment of the inflammatory and nutritional indices
Clinical and biological data [total protein, albumin, and C-reactive protein (CRP) levels; white blood cell, neutrophil, platelet, and lymphocyte count; and height and weight] were extracted from medical records for further analyses. Six systemic inflammatory and nutritional status based on previous studies (15) were calculated at baseline within 1 week of the initial cycle of AMR treatment. The inflammatory indices were as follows: (I) NLR (16); (II) platelet count/lymphocyte count [platelet-to-lymphocyte ratio (PLR)] (15); and (III) systemic immune-inflammation index (SII) = platelet count × neutrophil count/lymphocyte count (16). The nutritional indices were as follows: (I) PNI =10 × albumin (g/dL) +0.005× lymphocyte count (15); (II) advanced lung cancer inflammation index (ALI) = body mass index (BMI) + albumin level (g/dL)/NLR (17); and (III) Glasgow prognostic score (GPS). The GPS was tabulated as follows: 0= no abnormal values (good); 1= one abnormal value (intermediate); and 3= two abnormal values (poor) (14). The respective abnormal values for CRP and albumin were >10 mg/mL and <3.5 g/dL. A GPS of 0 was defined as low, and a GPS of 1 or 2 was defined as high (14,15). The optimal cutoff values for NLR, PLR, SII, PNI, and ALI were determined using the median values (8,9).
Statistical analysis
Statistical significance was defined as P<0.05. Fisher’s exact test was utilized to evaluate the association between two categorical variables. PFS was defined as the time from the initial treatment of AMR monotherapy to disease progression or death. Overall survival (OS) was defined as the time from the initial treatment of AMR monotherapy to death from any cause. The primary endpoint was to assess the prognostic relationship between AMR monotherapy and inflammatory and nutritional indices.
The optimal cutoff values for the NLR, PLR, SII, PNI, and ALI were determined using receiver operating characteristic (ROC) curve analysis to calculate sensitivity and specificity; the cutoff values differentiate responders from non-responders. Responders were defined as those with a PFS time of >6 months after AMR administration. Factors with a value greater than the cut-off value were defined as highly expressed. Kaplan-Meier analysis was used to estimate survival as a function of time, and differences in survival were analyzed using the log-rank test. Univariate and multivariate analyses of variables were performed using the COX proportional hazards model. All statistical analyses were performed using GraphPad Prism (v.7.0e; GraphPad Software, San Diego, CA, USA) and JMP Pro 16.0 (SAS Institute Inc., Cary, NC, USA).
Results
Patient demographics
Patient characteristics are listed in Table 1. The median patient age was 71 years (range, 50–85 years). Thirty-eight (84.4%) patients were male, 35 (77.8%) had a PS of 0 or 1, and 30 (66.7%) had received carboplatin and etoposide with atezolizumab as a prior regimen.
Table 1. Patient characteristics.
| Characteristics | Number (n=45) |
|---|---|
| Median age (range), years | |
| ≤70/>70 | 22/23 |
| Sex | |
| Male/female | 38/7 |
| ECOG performance status | |
| 0–1/2 | 35/10 |
| Prior regimens | |
| CBDCA/VP-16/atezolizumab | 30 |
| CBDCA/VP-16/durvalumab | 11 |
| CDDP/VP-16/durvalumab | 4 |
| PD-L1 maintenance by prior regimen | |
| Median cycle by maintenance (range) | 2 (0–18 cycles) |
| Yes/no | 36/9 |
| IrAEs by prior chemoimmunotherapy | |
| Present/absent | 4/41 |
| Response by AMR | |
| CR/PR/SD/PD/NE | 0/15/16/6/8 |
| Response by prior chemoimmunotherapy | |
| CR/PR/SD/PD/NE | 0/27/10/8/0 |
| Metastatic sites | |
| Liver/brain/bone/adrenal/LN/PM/pleura | 14/24/10/11/33/11/11 |
Adrenal, adrenal gland; AMR, amrubicin; CBDCA, carboplatin; CDDP, cisplatin; CR, complete response; ECOG, Eastern Cooperative Oncology Group; irAEs, immune-related adverse events; LN, lymph nodes; NE, not evaluable; PD, progressive disease; PD-L1, programmed death ligand-1; Pleura, pleural metastases; PM, pulmonary metastases; PR, partial response; SD, stable disease; VP-16, etoposide.
Among 45 patients with lesions evaluable for response to AMR [a partial response (PR) in 15 patients, stable disease in 16, progressive disease (PD) in 6, and not evaluable in 8], the ORR was 40.5% (15/37), whereas the disease control rate was 83.8% (31/37). The ORR after the prior CTI was 60.0%.
The median values for the NLR, PLR, SII, PNI, and ALI just before AMR were 3.8 (range: 1.5–16.9), 5.6 (range: 1.8–13.3), 8,651.4 (range: 2,050.2–42,147.8), 59.7 (range: 40.8–91.2), and 20.9 (range: 4.3–62.5), respectively. A GPS of 0 and 1 was seen in 30 and 15 patients, respectively.
Efficacy by AMR and survival analysis
Patient demographics based on the efficacy of CTI and AMR are shown in Table 2. The median PFS and OS were 169 and 267 days, respectively. Forty (88.9%) patients experienced recurrence and 34 (75.6%) died owing to disease progression. The exploratory analysis was performed based on the OS after prior CTI (≥12 vs. <12 months), PFS after AMR administration (≥6 vs. <6 months), and OS after AMR initiation (≥12 vs. <12 months), and therapeutic response by AMR (PR vs. non-PR) (Table 2). OS after prior CTI was significantly associated with PS, NLR, ALI, and the duration from ICI to PD. PFS and OS after AMR were closely related to the NLR and ALI (or PNI). However, there were no significant factors associated with AMR response.
Table 2. Comparison of patient’s demographics according to the efficacy by CTI and AMR administration.
| Different variables | Total (n=45) | OS after prior CTI | PFS after AMR | OS after AMR | Response by AMR | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ≥12 M (n=23) | <12 M (n=22) | P | ≥6 M (n=20) | <6 M (n=25) | P | ≥12 M (n=8) | <12 M (n=37) | P | PR (n=15) | Non-PR (n=30) | P | |||||
| Age (years) | ||||||||||||||||
| <70/≥70 | 22/23 | 13/10 | 9/13 | 0.38 | 10/10 | 12/13 | >0.99 | 5/3 | 17/20 | 0.46 | 6/9 | 7/23 | 0.30 | |||
| Sex | ||||||||||||||||
| Male/female | 38/7 | 19/4 | 19/3 | >0.99 | 18/2 | 20/5 | 0.44 | 8/0 | 30/7 | 0.32 | 14/1 | 24/6 | 0.40 | |||
| PS | ||||||||||||||||
| 0–1/2 | 35/10 | 21/2 | 14/8 | 0.04* | 18/2 | 17/8 | 0.15 | 7/1 | 28/9 | 0.66 | 13/2 | 22/8 | 0.46 | |||
| Prior ICI maintenance | ||||||||||||||||
| Yes/no | 36/9 | 19/4 | 17/5 | 0.72 | 16/4 | 20/5 | >0.99 | 8/0 | 28/9 | 0.18 | 13/2 | 23/7 | 0.70 | |||
| Response to CTI | ||||||||||||||||
| PR/non-PR | 27/18 | 11/12 | 16/6 | 0.13 | 10/10 | 17/8 | 0.24 | 3/5 | 24/13 | 0.24 | 10/5 | 17/13 | 0.75 | |||
| Liver metastasis at initial presentation | ||||||||||||||||
| Yes/no | 13/32 | 5/18 | 8/14 | 0.34 | 5/15 | 8/17 | 0.74 | 2/6 | 11/26 | >0.99 | 2/13 | 11/19 | 0.16 | |||
| NLR | ||||||||||||||||
| High/low | 22/23 | 7/16 | 15/7 | 0.02* | 5/15 | 17/8 | 0.006** | 1/7 | 21/16 | 0.047* | 6/9 | 16/14 | 0.53 | |||
| PLR | ||||||||||||||||
| High/low | 16/29 | 10/13 | 6/16 | 0.35 | 9/11 | 7/18 | 0.35 | 3/5 | 13/24 | >0.99 | 4/11 | 12/16 | 0.34 | |||
| SII | ||||||||||||||||
| High/low | 24/21 | 9/14 | 15/7 | 0.07 | 8/12 | 16/9 | 0.08 | 2/6 | 22/15 | 0.12 | 8/7 | 16/14 | >0.99 | |||
| PNI | ||||||||||||||||
| High/low | 24/21 | 9/14 | 15/7 | 0.07 | 9/11 | 15/10 | 0.36 | 1/7 | 23/14 | 0.02* | 9/6 | 15/15 | 0.75 | |||
| ALI | ||||||||||||||||
| High/low | 23/22 | 17/6 | 6/16 | 0.002** | 15/5 | 8/17 | 0.006** | 7/0 | 16/21 | 0.009** | 8/7 | 15/15 | >0.99 | |||
| GPS | ||||||||||||||||
| High/low | 15/30 | 6/17 | 9/13 | 0.35 | 5/15 | 10/15 | 0.35 | 1/7 | 14/23 | 0.24 | 6/9 | 9/21 | 0.52 | |||
| Duration from ICI to PD (days) | ||||||||||||||||
| <138/≥138 | 23/22 | 6/17 | 17/5 | <0.001*** | 13/7 | 10/15 | 0.14 | 4/4 | 19/18 | >0.99 | 7/8 | 16/14 | 0.76 | |||
*, P<0.05; **, P<0.01; ***, P<0.001. The measurements of NLR, PLR, SII, PNI, ALI, and GPS were calculated just before AMR initiation. ALI, advanced lung cancer inflammation index; AMR, amrubicin; CTI, chemo-immunotherapy; GPS, Glasgow prognostic score; ICI, immune checkpoint inhibitor; M, months; NLR, neutrophil to lymphocyte ratio; OS, overall survival; PD, progressive disease; PFS, progression-free survival; PLR, platelet to lymphocyte ratio; PNI, prognostic nutrition index; PR, partial response; PS, performance status; SII, systemic immune inflammation index.
The univariate and multivariate analyses after AMR initiation are presented in Table 3. The Kaplan-Meier survival curves for PFS and OS are shown in Figure 2. Univariate analysis identified NLR and ALI as significant predictors of PFS, and the presence of prior ICI maintenance, NLR, ALI, and duration from ICI to PD as significant predictors of OS (Table 3). The application of a univariate log-rank test enabled the screening of variables with a cutoff of P<0.05 for subsequent multivariable analysis. As the strongest confounder between the NLR and ALI was recognized, ALI was not considered in further multivariate analyses. Multivariable analysis demonstrated that the NLR was an independent prognostic factor for predicting worse PFS and OS after AMR administration (Table 3).
Table 3. Univariate and multivariate survival analysis after AMR administration based on cut-off calculated by median values.
| Different variables | PFS | OS | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Univariate | Multivariate | Univariate | Multivariate | ||||||
| MST | P | P (HR, 95% CI) | MST | P | P (HR, 95% CI) | ||||
| Age | |||||||||
| ≤70/>70 | 159/166 | 0.61 | 231/211 | 0.35 | |||||
| Sex | |||||||||
| Male/female | 169/123 | 0.053 | 270/188 | 0.19 | |||||
| PS | |||||||||
| 0–1/2 | 182/67 | 0.39 | 270/67 | 0.07 | |||||
| Prior ICI maintenance | |||||||||
| Yes/No | 166/67 | 0.20 | 0.45 (0.69, 0.26–1.74) | 231/197 | 0.048* | 0.97 (0.98, 0.37–2.44) | |||
| Response by CTI | |||||||||
| PR/non-PR | 130/197 | 0.22 | 188/296 | 0.34 | |||||
| Response by AMR | |||||||||
| PR/non-PR | 195/124 | 0.052 | 296/197 | 0.12 | |||||
| Liver metastasis at initial presentation | |||||||||
| Yes/no | 130/166 | 0.63 | 169/267 | 0.19 | |||||
| NLR | |||||||||
| High/low | 116/231 | <0.001*** | 0.004** (3.27, 1.43–7.54) | 126/294 | <0.001*** | 0.007** (3.03, 1.35–6.92) | |||
| PLR | |||||||||
| High/low | 188/150 | 0.32 | 197/231 | 0.54 | |||||
| SII | |||||||||
| High/low | 124/188 | 0.32 | 130/294 | 0.06 | |||||
| PNI | |||||||||
| High/low | 127/188 | 0.39 | 211/267 | 0.29 | |||||
| ALI | |||||||||
| High/low | 231/124 | 0.001*** | 300/126 | <0.001*** | |||||
| GPS | |||||||||
| High/low | 150/174 | 0.55 | 169/237 | 0.20 | |||||
| Duration from ICI to PD (days) | |||||||||
| <138/≥138 | 195/127 | 0.07 | 0.502 (0.77, 0.37–1.63) | 294/130 | 0.02* | 0.11 (0.52, 0.23–1.15) | |||
*, P<0.05; **, P<0.01; ***, P<0.001. ALI, advanced lung cancer inflammation index; AMR, amurubicin; CI, confidence interval; GPS, Glasgow prognostic score; CTI, chemoimmunotherapy; HR, hazard ratio; ICI, immune checkpoint inhibitor; meta, metastases; MST, median survival time; multivariate, multivariate survival analysis; NLR, neutrophil to lymphocyte ratio; OS, overall survival; PD, progressive disease; PFS, progression-free survival; PLR, platelet to lymphocyte ratio; PNI, prognostic nutrition index; PR, partial response; PS, performance status; SII, systemic immune inflammation index; univariate, univariate survival analysis.
Figure 2.
The Kaplan-Meier curves for PFS and OS after AMR administration based on the OS after prior CTI (≥12 vs. <12 months), PD-L1 maintenance, NLR, and ALI. The patients with OS ≥12 months after prior CTI had a significantly longer PFS (A) and OS (B) than those with OS <12 months. There was no statistically significant difference in the PFS (C) between those with and without PD-L1 maintenance, but the patients with PD-L1 maintenance exhibited a significantly longer OS (D) than those without PD-L1 maintenance. High NLR was significantly associated with shorter PFS (E) and OS (F). Low ALI was significantly linked to poor PSF (G) and OS (H). ALI, advanced lung cancer inflammation index; AMR, amrubicin; CTI, chemoimmunotherapy; NLR, neutrophil-to-lymphocyte ratio; OS, overall survival; PD-L1, programmed death ligand-1; PFS, progression-free survival.
Next, we investigated the survival analysis using the cut-off values of NLR, PLR, SII, PNI, and ALI calculated by the ROC curve analysis. The optimal cutoff values for the NLR, PLR, SII, PNI, and ALI as determined by ROC curve analyses were 3.3 (sensitivity: 70.0%, specificity: 84.0%), 5.3 (sensitivity: 70.0%, specificity: 72.0%), 6,408.0 (sensitivity: 50.0%, specificity: 80.0%), 68.2 (sensitivity: 90.0%, specificity: 36.0%), and 29.9 (sensitivity: 65.0%, specificity: 88.0%), respectively. The areas under the curve in the ROC analysis were 0.747 (NLR), 0.680 (PLR), 0.650 (SII), 0.565 (PNI), and 0.724 (ALI). High values for the NLR, PLR, SII, PNI, and ALI were observed in 62.2, 46.6, 73.3, 28.8, and 35.5% of patients, respectively. Table 4 shows the survival analysis calculated by cut-off values of NLR, PLR, SII, PNI, and ALI calculated by ROC curve. The results of the other variables corresponded to those of Table 3. Univariate analysis identified NLR and ALI as significant predictors for PFS and ALI for OS (Table 4). Although there was a stronger confounder between NLR and ALI, the results of this analysis indicated ALI as a promising predictor rather than NLR. Therefore, ALI was chosen as the subsequent multivariable analysis in addition to prior ICI maintenance and duration from ICI to PD. Multivariable analysis demonstrated that the ALI was an independent prognostic factor for predicting worse PFS and OS after AMR administration (Table 4).
Table 4. Univariate and multivariate survival analysis after AMR administration based on cut-off value calculated by ROC curve.
| Different variables | PFS | OS | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Univariate | Multivariate | Univariate | Multivariate | ||||||
| MST | P | P (HR, 95% CI) | MST | P | P (HR, 95% CI) | ||||
| Age | |||||||||
| ≤70/>70 | 159/166 | 0.61 | 231/211 | 0.35 | |||||
| Sex | |||||||||
| Male/female | 169/123 | 0.053 | 270/188 | 0.19 | |||||
| PS | |||||||||
| 0–1/2 | 182/67 | 0.39 | 270/67 | 0.07 | |||||
| Prior ICI maintenance | |||||||||
| Yes/no | 166/67 | 0.20 | 0.80 (0.88, 0.32–2.18) | 231/197 | 0.048* | 0.74 (1.16, 0.45–2.76) | |||
| Response by CTI | |||||||||
| PR/non-PR | 130/197 | 0.22 | 188/296 | 0.34 | |||||
| Response by AMR | |||||||||
| PR/non-PR | 195/124 | 0.052 | 296/197 | 0.12 | |||||
| Liver metastasis at initial presentation | |||||||||
| Yes/no | 130/166 | 0.63 | 169/267 | 0.19 | |||||
| NLR | |||||||||
| High/low | 124/274 | 0.03* | 169/294 | 0.10 | |||||
| PLR | |||||||||
| High/low | 211/127 | 0.20 | 231/182 | 0.43 | |||||
| SII | |||||||||
| High/low | 127/214 | 0.28 | 195/333 | 0.26 | |||||
| PNI | |||||||||
| High/low | 123/182 | 0.83 | 123/267 | 0.47 | |||||
| ALI | |||||||||
| High/low | 280/123 | <0.001*** | 0.04* (0.95, 0.90–0.99) | 333/169 | 0.009** | 0.04* (0.42, 0.17–2.35) | |||
| GPS | |||||||||
| High/low | 150/174 | 0.55 | 169/237 | 0.20 | |||||
| Duration from ICI to PD (days) | |||||||||
| <138/≥138 | 195/127 | 0.07 | 0.315 (0.68, 0.33–1.44) | 294/130 | 0.01* | 0.060 (0.48, 0.22–1.03) | |||
*, P<0.05; **, P<0.01; ***, P<0.001. ALI, advanced lung cancer inflammation index; AMR, amrubicin; CI, confidence interval; CTI, chemoimmunotherapy; GPS, Glasgow prognostic score; HR, hazard ratio; ICI, immune checkpoint inhibitor; MST, median survival time; multivariate, multivariate survival analysis; NLR, neutrophil to lymphocyte ratio; OS, overall survival; PD, progressive disease; PFS, progression-free survival; PLR, platelet to lymphocyte ratio; PNI, prognostic nutrition index; PR, partial response; PS, performance status; SII, systemic immune inflammation index; univariate, univariate survival analysis.
Clinical feature of therapeutic duration in 45 patients
Figure 3 shows the duration of ICI administration, AMR monotherapy, and sequential therapy after AMR failure. In two patients with >1 year of continuous ICI administration (cases 40 and 42), the duration of AMR monotherapy was >300 days, with the ORR of PR. Eight (80.0%) of the 10 surviving patients exhibited a low NLR, and a high NLR was observed in four (66.7%) of the six patients with PD by AMR.
Figure 3.
Continuous period of ICI after CTI, therapeutic period of AMR, and sequential therapy after failure of AMR in 45 patients. AMR, amrubicin; CTI, chemoimmunotherapy; ICI, immune checkpoint inhibitor; NLR, neutrophil to leukocyte ratio; PD, progressive disease; PR, partial response.
Adverse events for AMR
In our study, 44 (97.8%) of 45 patients who received AMR were treated with prophylactic pegfilgrastim (PEG) treatment. Grade 1 or 2 appetite loss, fatigue, nausea, liver dysfunction, diarrhea, neuropathy, and pneumonia were observed in 12 (26.6%), 4 (8.8%), 5 (1.1%), 1 (0.2%), 1 (0.2%), 1 (0.2%), and, 1 (0.2%) patients, respectively. As hematological toxicities, grade 1 or 2 leukopenia, anemia, and thrombocytopenia were recognized in 4 (8.8%), 2 (0.4%), and 4 (8.8%) patients, respectively, whereas grade 3 or 4 leukocytopenia and thrombocytopenia were observed in 3 (6.6%) and 2 (0.4%) patients, respectively. Grade 3 febrile neutropenia was observed in 3 (6.6%) patients. There was no serious toxicity related to death after AMR administration.
Discussion
Our exploratory study identified the NLR as a significant predictor of AMR after prior CTI in patients with previously treated ES-SCLC. A recent meta-analysis of 11 studies with 3,664 patients with SCLC reported that a high NLR was associated with worse outcomes in patients receiving first-line chemotherapy (18). To the best of our knowledge, the relationship between the prognostic significance of the NLR and sequential treatment after prior CTI in patients with ES-SCLC remains unclear. In our study, the presence of prior anti-PD-L1 antibody maintenance after CTI and the duration from the initiation of anti-PD-L1 antibody therapy to disease progression may have affected the therapeutic efficacy of AMR monotherapy, as well as the NLR or ALI. We hypothesized that prior immunotherapy would prevent therapeutic resistance of the tumor immune microenvironment to sequential treatment.
Lambrecht et al. examined the prognostic potential of inflammatory and nutritional markers in 44 patients with SCLC receiving topotecan as second-line treatment (10). Although PS, active brain metastases, NLR, GPS, PNI, and SII significantly influenced PFS and OS in the univariate analysis, PS, brain metastases, and SII were identified as independent prognostic factors in the multivariate analysis. In their study, 70.5% of all patients received first-line CTI, and 29.5% were treated with chemoradiotherapy. None of the patients received prior immunotherapy, which may have biased the results of their study (10). The SII is an inflammatory index closely associated with the NLR. Therefore, inflammatory markers may predict the outcome of sequential treatment after prior ICI treatment. In the present study, we found that the NLR or ALI could predict outcomes after prior CTI followed by AMR. Moreover, sensitivity to ICI treatment appeared to improve the therapeutic efficacy of AMR monotherapy.
AMR monotherapy for relapsed SCLC has been previously described (5). The ORR and PFS for AMR without prior ICIs therapy range from 31.1% to 53.1% and from 3.2 to 4.5 months, respectively (5). Although the efficacy of AMR with and without prior ICIs has not been statistically compared, previous evidence suggests that prior anti-PD-L1 antibody may not improve the therapeutic efficacy of AMR (5-7,18). However, a high NLR or low ALI was closely associated with survival after AMR administration. To our knowledge, little is known about the predictive markers of AMR monotherapy, and it remains unclear whether the NLR or ALI can predict the outcome of AMR without prior immunotherapy. Lambrecht et al. reported that NLI, SII, and PNI significantly influenced the outcome after treatment with topotecan as a topoisomerase inhibitor (10). In their study, a multivariate COX regression model identified PS and SII as significant independent prognostic markers for PFS and PS and PNI for OS (10). Although PS is the most promising factor for predicting the outcome of any treatment in patients with SCLC, systemic inflammatory and nutritional markers also may be closely associated with prognostic predictors for systemic chemotherapy aside from immunotherapy. In particular, the resistance of prior immunotherapy could affect the tumor immune microenvironment of subsequent therapy; thus, inflammatory markers such as NLR may influence the therapeutic efficacy of AMR following ICI failure.
Although the genomic profiling of SCLC is related to functional inactivation of TO53 and RB1 genes, four distinct molecular subtypes of SCLC were defined by the dominant expression of transcription factors ASCL1, NEUROD1, YAP1, and POU2F3 (19). SCLC tumor immune microenvironment is highly heterogeneous, and immune hot tumors were related to OS. However, these molecular subtypes (ASCL1, NEUROD1, YAP1, and POU2F3) were not associated with immune environments or survival (19). Nowadays, it remains unclear about the prognostic significance of inflammatory and nutritional markers according to these molecular subtypes of SCLC.
As further sequential therapy after AMR treatment, tarlatamab, a bispecific T-cell engager immunotherapy, was approved in Japan and exhibited promising clinical benefits with an ORR of 55% and a median PFS of 4.9 months (20). Thus, further investigation is warranted to determine the most suitable biomarkers for the outcome of AMR, followed by tarlatamab.
Our study had some limitations. First, the sample size was small, which may have biased our results. The impact of the small sample size in terms of limited statistical power may increase the risk of type II error. Moreover, there was the potential for residual confounding due to the retrospective design, the inability to infer causality, and limited generalizability due to the single-center, Japanese cohort. Second, our study did not compare the efficacy of AMR after platinum-based chemotherapy with or without prior ICIs. Finally, there were no data on the relationship between inflammatory markers, including the NLR, and the tumor immune environment before AMR administration. Although it remains unclear whether prior immunotherapy could determine the chemosensitivity of the tumor environment, the assessment of tumor-infiltrating lymphocytes and PD-L1 expression just before AMR initiation is helpful for determining the mechanism of predictive biomarkers.
Conclusions
NLR was identified as a significant biomarker for predicting AMR outcomes after prior CTI in patients with ES-SCLC. The continuation or sensitivity of ICI treatment can improve the efficacy of AMR without an optimal mechanism. Further investigation is warranted to discover an optimal biomarker for predicting the outcome of AMR followed by tarlatamab, a bispecific T-cell-engager immunotherapy.
Supplementary
The article’s supplementary files as
Acknowledgments
The authors thank Editage (www.editage.jp) for English language editing.
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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of the International Medical Center at Saitama Medical University (approved No. 20-125, 2023-033), and the requirement for written informed consent was waived by the Ethics Committee of Saitama Medical University owing to the retrospective nature of the study.
Footnotes
Reporting Checklist: The authors have completed the REMARK and STROBE reporting checklists. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-214/rc
Funding: This work was supported by the JSPS Grant-in-Aid for Scientific Research C (No. 24K10292 to K.K.).
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-214/coif). K.K. received a speaker honorarium from Ono Pharmaceutical Company, Chugai Pharmaceutical, and AstraZeneca; research grants from AstraZenec; JSPS Grant-in-Aid for Scientific Research C (No. 24K10292). O.Y. and A.M. received speaker honoraria from Chugai Pharmaceutical and AstraZeneca, respectively. H.K. received research grants from Ono Pharmaceutical Company, Boehringer Ingelheim, and Chugai Pharmaceutical; speaker honoraria from Ono Pharmaceutical Company, Bristol-Myers Company, MSD, Chugai Pharmaceutical, and AstraZeneca. The other authors have no conflicts of interest to declare.
Data Sharing Statement
Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-214/dss
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