Prognostic role of pretreatment lung immune prognostic index in extensive-stage small-cell lung cancer treated with platinum plus etoposide chemotherapy

Abstract

BACKGROUND:

To investigate the prognostic role of lung immune prognostic index (LIPI) in extensive-stage small-cell lung cancer (ES-SCLC) patients treated with platinum plus etoposide chemotherapy.

METHODS:

Data were obtained from two randomized controlled trials (NCT00119613 and NCT00363415). Overall survival (OS) and progression-free survival (PFS) was assessed according to LIPI score through Kaplan-Meier analysis. Univariate and multivariate Cox-regression analysis were performed to investigate predictors for OS and PFS.

RESULTS:

A total of 911 patients with ES-SCLC treated with platinum plus etoposide chemotherapy (CT) were included for analysis. The median age at diagnosis was 62 years, and 760 (83.4%) had performance status of 1 or less. 1-year OS for ES-SCLC with poor, intermediate, and good LIPI was 20%, 30% and 31%, respectively, and 1-year PFS was 7%, 15% and 21%, respectively. Cox-regression analysis showed that the PFS and OS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores (HR 1.81, 95% CI: 1.38–2.36; $p<$ 0.001 and HR 1.35, 95% CI: 1.07–1.72, $p=$ 0.012), while no significant difference was observed between intermediate and poor LIPI groups in terms of OS (HR 1.01, 95% CI: 0.82–1.23, $p=$ 0.82), but not for PFS (HR 1.27, 95% CI: 1.00–1.61, $p=$ 0.048). In addition, LIPI score was significantly associated with disease control rate and objective response rate (both $p<$ 0.0001).

CONCLUSION:

Prognosis of patients with pretreatment LIPI score of 2 is poorer than those with LIPI score of 0–1 among ES-SCLC who received first-line platinum plus etoposide chemotherapy; Further studies are still recommended to confirm our findings in prospective studies.

Keywords

Small-cell lung cancer biomarker LIPI score prognostic index

1. Introduction

According to the GLOBOCAN estimates of cancer incidence and mortality, lung cancer remains the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths) in 2018 [1]. Small-cell lung cancer (SCLC) accounts for approximately 15% of all new lung cancers, with an annual incidence of overall 300,000 new cases worldwide. Generally, SCLC is a highly aggressive disease, which is characterized by rapid tumor growth and early distant metastasis [2, 3]. In the past decades, although major improvements have been achieved in the treatment of solid tumors including non-small-cell lung cancer, the current standard first-line treatment for extensive-stage(ES)-SCLC remains platinum-based doublet chemotherapy [4, 5]. Despite the initial response rate to first-line chemotherapy is approximately 70%, nearly all of ES-SCLC patients would inevitably develop chemotherapy resistance and disease progression, and the prognosis of ES-SCLC remains poor, with 5-year survival less than 10% [2]. Therefore, a better understanding of prognostic factors for survival would be of particular importance to assist physicians to identify SCLC patients who are considered at risk for unfavorable outcomes and perform an individualized therapy for such patients in advanced.

Cancer-associated inflammation leads to poor survival [6, 7]. Recently, the associations between inflammatory markers and the prognosis of lung cancer have been extensively investigated [8, 9, 10]. In 2018, Prof. Mezquita [11] developed a lung immune prognostic index (LIPI) based on dNLR greater than 3 and LDH greater than ULN, and characterized into 3 groups (good, 0 factors; intermediate, 1 factor; poor, 2 factors). The authors found that pretreatment LIPI was correlated with worse outcomes for non-small-cell lung cancer (NSCLC) treated with immune checkpoint inhibitor (ICI), but not for chemotherapy. However, the sample size of NSCLC treated with chemotherapy was relative small ( $n=$ 162). Subsequently, an exploratory pooled analysis was performed based on data from eleven randomized clinical trials and found that LIPI was an important prognostic biomarkers for metastatic NSCLC independent of treatment modalities [12]. However, the prognostic role of pretreatment LIPI in ES-SCLC treated with platinum plus etoposide chemotherapy remains undetermined. As a result, in the present study, we aim to investigate the prognostic role of LIPI in ES-SCLC patients who treated with first-line chemotherapy by using an individual data analysis from two prospective clinical trials.

2. Materials and methods

2.1 About PDS and study cohorts

Project data sphere was an independent, not-for-profit data-sharing platform, which provided individual patient-level data from prospective clinical trial in order to advance future cancer research (https://www. projectdatasphere.org/). In the present study, we used the raw individual data from two phase III trials evaluating efficacy and toxicities of platinum plus etoposide chemotherapy for ES-SCLC patients (NCT00119613 and NCT00363415). The primary results of these trials were analyzed and published previously [13, 14]. For chemotherapy-naïve patients with ES-SCLC treated with etoposide-carboplatin in the NCT 00363415 trial, the median progression free survival and overall survival was 5.4 and 10.6 months, respectively. In the Pirker R.’s study, the median progression-free survival and overall survival ES-SCLC patients treated with etoposide-platinum was 5.6 and 9.3 months. Therefore, survival outcomes of ES-SCLC patients treated with etoposide-platinum were comparable for the two patient cohorts. As our study was a second-analysis of previously published trials, informed consent was waved in the present study. Finally, a total of 911 patients with ES-SCLC treated with platinum plus etoposide chemotherapy were included for analysis.

2.2 Data collection

The available data of the phase III trial contains data about age at diagnosis, baseline ECOG performance status, sex, race, baseline neutrophil and white blood cell, baseline lactate dehydrogenase (LDH) and alkaline phosphatase (ALP), baseline weight and height. Moreover, data about disease response rate, progression-free survival status and overall survival status were recorded. Based on the inclusion criteria for clinical trials, all included patients in the present study should have adequate organ function and acceptable performance status.

2.3 Statistical consideration

The baseline characteristics of included patients was simply described by using frequencies and percentages. The LIPI composite scores were calculated based on the dNLR (absolute neutrophil count/[white blood cell count – absolute neutrophil count]) and the baseline LDH level according to Mezquita et al. report [11]. In addition, we also investigated the prognostic role of dNLR and baseline LDH level for ES-SCLC in this patient population. Disease control rate (DCR) and objective response rate (ORR), Overall survival (OS) and progression-free survival (PFS) was assessed according to LIPI scores through Kaplan-Meier analysis. Multiple comparisons of survival times between LIPI score are compared by Log-rank tests. Univariate and multivariate Cox-regression analysis were performed to investigate predictors for overall survival and progression-free survival. Factors significantly associated with risk of OS and PFS in the univariate analysis ( $p<$ 0.05) were then included for analysis in the multivariate cox-regression analysis. A two-tailed $P$ -value $<$ 0.05 was considered statistically significant. Statistical analyses were conducted through NCSS version 11.0 statistical software.

3. Results

3.1 Patients characteristics

A total of 934 patients from two phase III trials were identified (NCT00363415481: 455 patients and NCT00119613: 479 patients, Supplemental Table 1), 23 patients were excluded for the present analysis due to lack baseline data of albumin or LDH. Finally, 911 patients were included for analysis and the baseline characteristics were shown in Table 1. All of the chemotherapy-naïve ES-SCLC patients received platinum plus etoposide therapy. The median age at diagnosis was 62 years. 568 (62.3%) patients aged less than 65, while 343 (37.7%) patients older than 65; Among these patients, and 760 (83.4%) had performance status of 1 or less. 632 were male and 279 were female patients; In addition, a dNLR greater than 3 were observed 263 patients, while the other 648 patients less than 3. As for baseline LDH value, 674 patients were greater than upper limits of normal (ULN), and 237 patients were less than UNL (Table 1).

Table 1
Baseline characteristics of 911 included patients

Characteristic	LIPI score
	0	1	2
Age
$<$ 65 years	117	334	128
$\geqslant$ 65 years	57	202	73
Sex
Male	48	164	67
Female	126	372	134
Race
Caucasian	148	499	190
Others	26	36	11
Baseline ECOG PS
0–1	15	85	51
2	159	450	150
dNLR
$<$ 3	174	473	0
$\geqslant$ 3	0	62	201
ALP, IU/L
$\leqslant$ ULN	16	321	85
$>$ ULN	158	214	116
LDH, IU/L
$\leqslant$ ULN	174	62	0
$>$ ULN	0	473	201
Albumin (continuous	37 (26–59)	38 (24.3–49)	36 (23–48)
variable), g/L
BMI (kg/m ${}^{2}$ )
$<$ 25	84	259	113
$\geqslant$ 25, $\leqslant$ 30	56	183	69
$>$ 30	33	93	19

Abbreviation: ECOG PS, Eastern Cooperative Oncology Group Performance Score; dNLR, derived neutrophil to lymphocyte ratio (leukocytes minus neutrophils); ULN, upper limits of normal; BMI, Body Mass Index; ALP, Alkaline phosphatase; LDH, lactate dehydrogenase.

3.2 Association of LIPI scores with PFS

The LIPI was evaluable for 911 patients, giving 174 patients (19.1%) in the poor group, 536 (58.8%) in the intermediate group, and 201 (22%) in the good LIPI group. Median PFS was 5.16 months (95% CI, 4.90–5.30 months). According to LIPI scores, median PFS was 5.50, 6.13, and 6.57 months, respectively. And 1-year PFS was 7%, 15% and 21%, respectively, and there was significant difference of PFS among LIPI groups ( $p<$ 0.001, Fig. 1). Moreover, we evaluated the PFS difference according to dNLR value and baseline LDH level. Our results showed that the PFS of patients with dNLR $<$ 3 was significantly better than patients with dNLR $\geqslant$ 3 ( $p=$ 0.023, Supplemental Fig. 1A). In addition, the prognosis of ES-SCLC presented with increased baseline LDH level was poorer than patients with baseline normal LDH level group ( $p=$ 0.006, Supplemental Fig. 1C).

Cox-regression analysis showed that the PFS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores (HR 1.81, 95% CI: 1.38–2.36; $p<$ 0.001) and intermediate group (HR 1.27, 95% CI: 1.00–1.61; $p=$ 0.048). Multivariable analysis showed that Eastern Cooperative Oncology Group performance score, the baseline ALP and LDH level, LIPI score and dNLR were associated with longer PFS (Table 2).

Table 2
Univariate and multivariate cox regression analysis for factors predicting PFS

Characteristic	Progression-free survival
	Univariate		Multivariate
	HR (95% CI)	$p$	HR (95% CI)	$p$
Age (continuous)	1.00 (0.99–1.01)	0.60	–
Sex
Male	1		–
Female	0.91 (0.76–1.08)	0.27	–	–
Race
Caucasian	1		–
Others	0.67 (0.43–1.02)	0.064	–	–
Baseline ECOG PS
0–1	1		1
2	1.48 (1.20–1.84)	0.0003	1.39 (1.12–1.74)	0.0029
dNLR
$<$ 3	1		1
$\geqslant$ 3	1.27 (1.07–1.52)	0.0074	1.20 (1.00–1.45)	0.0068
ALP, IU/L
$\leqslant$ ULN	1		1
$>$ ULN	1.33 (1.13–1.58)	0.0007	1.21 (1.01–1.44)	0.035
LDH. IU/L
$\leqslant$ ULN	1		1
$>$ ULN	1.42 (1.16–1.74)	0.0006	1.32 (1.06–1.64)	0.014
BMI (kg/m ${}^{2}$ )
$<$ 25	1		1
$\geqslant$ 25, $\leqslant$ 30	0.97 (0.81–1.16)	0.71	0.93 (0.77–1.11)	0.77
$>$ 30	0.78 (0.61–1.00)	0.049	0.81 (0.63–1.04)	0.097
LIPI score
0	1		1
1	1.27 (1.00–1.61)	0.048	1.18 (0.92–1.51)	0.19
2	1.81 (1.38–2.36)	$<$ 0.001	1.55 (1.16–2.07)	0.032

Figure 1.

Progression-free survival according to LIPI scores.

3.3 Association of LIPI scores with OS

The LIPI was evaluable for 911 patients, giving 174 patients (19.1%) in the poor group, 536 (58.8%) in the intermediate group, and 201 (22%) in the good LIPI group. Median OS was 7.52 months (95% CI, 7.16–7.83 months). According to LIPI scores, median OS for ES-SCLC with poor, intermediate, and good LIPI was 7.6 months, 9.07 months, and 8.81 months, respectively. And 1-year OS for ES-SCLC with poor, intermediate, and good LIPI was 31%, 30% and 20%, respectively, and there was significant difference of OS among LIPI groups ( $p=$ 0.0056, Fig. 2). In addition, we also investigated the survival difference according to dNLR value and baseline LDH level. Our results showed that the OS of patients with dNLR $<$ 3 was significantly better than patients with dNLR $\geqslant$ 3 ( $p=$ 0.023, Supplemental Fig. 1B), while no significant difference between LDH increase and LDH normal group ( $p=$ 0.20, Supplemental Fig. 1D).

Figure 2.

Overall survival according to LIPI scores.

Cox-regression analysis showed that the OS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores (HR 1.35, 95% CI: 1.07–1.72, $p=$ 0.012), while no significant difference was observed between intermediate and poor LIPI groups in terms of OS (HR 1.01, 95% CI: 0.82–1.23, $p=$ 0.82). Multivariable analysis showed that, when controlling for the covariates of sex, race, and baseline BMI, Eastern Cooperative Oncology Group performance score, the baseline ECOG status, LIPI score and sex were two independent risk factors for OS (Table 3).

Table 3

Univariate and multivariate cox regression analysis for factors predicting OS

Characteristic	Overall survival
	Univariate		Multivariate
	HR (95% CI)	$p$	HR (95% CI)	$p$
Age (continuous)	1.01 (0.99–1.014)	0.22	–
Sex
Male	1		1
Female	0.76 (0.65–0.90)	0.0014	0.76 (0.64–0.90)	0.0015
Race
Caucasian	1		1
Others	1.39 (1.03–1.88)	0.03	1.35 (1.00–1.84)	0.053
Baseline ECOG PS
0–1	1		1
2	1.46 (1.19–1.78)	0.0002	1.50 (1.22–1.84)	0.0001
dNLR
$<$ 3	1		1
$\geqslant$ 3	1.20 (1.02–1.43)	0.03	0.84 (0.62–1.17)	0.32
ALP, IU/L
$\leqslant$ ULN	1		–
$>$ ULN	1.01 (0.86–1.18)	0.95	–	–
LDH, IU/L
$\leqslant$ ULN	1		–
$>$ ULN	1.12 (0.94–1.33)	0.20	–	–
BMI (kg/m ${}^{2}$ )
$<$ 25	1		1
$\geqslant$ 25, $\leqslant$ 30	0.89 (0.76–1.06)	0.20	0.88 (0.74–1.04)	0.13
$>$ 30	0.77 (0.62–0.96)	0.022	0.82 (0.66–1.03)	0.084
LIPI score
0	1		1
1	1.01 (0.82–1.23)	0.95	1.04 (0.85–1.28)	0.71
2	1.35 (1.07–1.72)	0.012	1.55 (1.04–2.32)	0.031

3.4 Association of LIPI scores with ORR/DCR

A total of 693 ES-SCLC patients were available for ORR and DCR analysis, the ORR was observed in 58 patients (426%) in the poor group, 193 (46.7%) in the intermediate group, and 81 (563%) in the good LIPI group. Similarly, the DCR in the poor group (551%) was significantly lower than that in the intermediate group (62.0%), and (771%) in the good LIPI group. And significant correlation was observed between LIPI scores and ORR or DCR (both $p<$ 0.0001, Table 4). In addition, logistic regression analysis showed that LIPI score was an independent risk factor for DCR (OR 1.59, 95% CI: 1.00–2.52, $p=$ 0.047; OR 1.96, 95% CI: 1.12–3.41, $p=$ 0.018, Supplement Table 2).

Table 4
Response rate and disease control rate according to LIPI groups

Assessment	All patients ( $n=$ 911)	LIPI0-good ( $n=$ 174)	LIPI1-moderate ( $n=$ 536)	LIPI2-poor ( $n=$ 201)	$P$ value
Objective response rate
CR+PR	332 (36.4%)	81 (46.6%)	193 (36%)	58 (28.5%)	$P<$ 0.0001
SD	110 (12.1%)	30 (17.2%)	63 (11.8%)	17 (8.5%)
PD	251 (27.6%)	33 (19.0%)	157 (29.3%)	61 (30.3%)
NA	218 (23.9%)	30 (17.2%)	123 (22.9%)	65 (32.3%)
Disease control rate
CR, PR or SD	442 (48.5%)	111 (64.8%)	256 (47.8%)	75 (37.3%)	$p<$ 0.0001
PD	251 (27.6%)	33 (19.0%)	157 (29.3%)	61 (30.3%)
NA	218 (23.9%)	30 (17.2%)	123 (22.9%)	65 (32.3%)

Abbreviations: CR, complete response; PR, partial response; SD, stable disease; PD, progression disease; NA, not available.

4. Discussion

Emerging evidence indicates that the mediators and cellular effectors of cancer-related inflammation play an important role in cancer development and disease progression [15]. However, the specific mechanism of inflammation involves this procedure remains unclear. Possible mechanism is that the inflammatory cells and cytokines found in tumors are more likely to contribute to tumor growth, progression, and immunosuppression than they are to initiate an effective host anti-tumor response [16, 17]. As a result, the prognostic value of multiple peripheral hematological markers has been extensively investigated in various tumors. Indeed, more and more evidence have showed that biomarkers of inflammation, which derived from peripheral blood, such as neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR) and lymphocyte-to-monocyte ratio (LMR) is significantly associated with survival for various tumors including lung cancer [18, 19, 20, 21, 22, 23, 24].

Interesting, baseline LDH level has been associated with poor prognosis in solid tumors including SCLC [25]. It has been well known that hypoxic microenvironments frequently exist in many solid tumors with oxygen levels fluctuating temporally, and the hypoxic microenvironment of a tumor can increase the conversion of pyruvic acid to lactic acid [26]. While LDH is an important enzyme that catalyzes the hydrogen transfer reaction between lactic acid and pyruvic acid [27]. Therefore, unregulated LDH levels ensure proficient anaerobic glycolytic metabolism in the tumor environment, leading to reduced oxygen dependence. Numerical studies indicated that LDH expression increased with tumor progression, and the prognostic role of LDH in cancers has been reported in respectable studies, including SCLC [25, 28, 29, 30, 31, 32], although most of these studies are retrospective analysis with relative small sample size. However, the LDH level in the present study seemed to be prognostic only for PFS, but not for OS. One possible explanation for this findings is that all patients were included in clinical trials with adequate hematological and liver function, and there might be potential biases.

The LIPI composite scores are calculated based on the dNLR and the baseline LDH level, both of which can be conveniently obtained in clinical practice. This LIPI scoring system was initially established to reflect immune status and identify patients who would benefit from treatment with ICI, but the sample size is relative small. Mezquita et al. found that Pretreatment LIPI was correlated with worse outcomes for ICI, but not for chemotherapy [11]. Subsequently, Kazandjian et al. [12] perform a larger sample size retrospective studies of 11 clinical trials and find that LIPI scores are important prognostic biomarkers not only for metastatic NSCLC patients treated with ICI, but also for targeted therapy or cytotoxic chemotherapy, although the prognostic value of LIPI seems greater for patients treated with immunotherapy. However, the prognostic role of LIPI scores in SCLC remains undetermined. As a result, we conduct the present study to investigate role of LIPI in ES-SCLC patients who treated with platinum plus etoposide chemotherapy.

To our best knowledge, the present study is the first to demonstrate prognostic role of pre-treatment LIPI for survival of ES-SCLC patients with a large sample size ( $n=$ 911). In consistent with Kazandjian et al’s report, the OS and PFS for ES-SCLC after first-line platinum-based chemotherapy is significantly associated with LIPI scores by Kaplan-Meier method using log-rank test. Cox-regression analysis showed that the PFS and OS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores ( $p<$ 0.001 and $p=$ 0.012), while no significant difference was observed between intermediate and poor LIPI groups in terms of OS ( $p=$ 0.82), but not for PFS ( $p=$ 0.048). In addition, significant correlation was observed between LIPI scores and ORR or DCR. As an integrated indicator based on dNLR and LDH, the mechanisms underlying potentially prognostic value of pre-treatment LIPI in ES-SCLC may be elucidated by a combination of the two mechanisms which we stated in previously.

We acknowledge that there are several potential limitations of our study. First of all, despite of the randomized, prospective nature of the included studies, our study is a retrospective analysis of the pooled dataset of these included studies. Thus there might be potential biases due to missing trials and laboratory values. Second, the present study is lack of external validation for SCLC, although the score system has been validated in mNSCLC. However, our study has several strong points: 1) this is a secondary analysis of two prospective phase III trial, detailed information about clinical characteristics, performance status and disease progression of the present analysis is reliable; 2) this is the first and largest individual analysis to validate the prognostic role of LIPI in ES-SCLC treated with first-line platinum plus etoposide chemotherapy. Thirdly, none of the included patients received immunotherapy, thus the prognostic role of LIPI score in SCLC who receiving immunotherapy remains undetermined, which needed to be investigated in further studies. Finally, the present study uses the bivariable selection (BVS) for selecting variables to be used in multivariable analysis, this type of variable selection is inappropriate according to previous publication if the relationship between an outcome and a risk factor is confounded by any confounder and when this confounder is not properly controlled. However, no obviously confounder between risk factors were observed in the present study.

5. Conclusion

In conclusion, the preset study confirm that prognosis of patients with pretreatment LIPI score of 2 is poorer than those with LIPI score of 0–1 among ES-SCLC who received first-line platinum plus etoposide chemotherapy. However, further studies are still recommended to confirm our findings in prospective studies.

Ethical approval

All procedures performed were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

As our study was a second-analysis of previously published trials, informed consent was waved in the present study.

Funding

None.

Supplementary data

The supplementary files are available to download from https://dx-doi-org.web.bisu.edu.cn/10.3233/CBM-201502.

sj-docx-1-cbm-10.3233_CBM-201502.docx - Supplemental material

Supplemental material, sj-docx-1-cbm-10.3233_CBM-201502.docx

Footnotes

Acknowledgments

This publication was based on research using information obtained from www.projectdatasphere.org, which was maintained by Project Data Sphere, LLC. Neither Project Data Sphere, LLC nor the owner(s) of any information from the website had contributed to, approved or were in any way responsible for the contents of this publication.

Conflict of interest

None.

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Prognostic role of pretreatment lung immune prognostic index in extensive-stage small-cell lung cancer treated with platinum plus etoposide chemotherapy

Abstract

BACKGROUND:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 About PDS and study cohorts

2.2 Data collection

2.3 Statistical consideration

3. Results

3.1 Patients characteristics

Table 1 Baseline characteristics of 911 included patients

Table 2 Univariate and multivariate cox regression analysis for factors predicting PFS

Table 4 Response rate and disease control rate according to LIPI groups

5. Conclusion

Ethical approval

Informed consent

Funding

Supplementary data

sj-docx-1-cbm-10.3233_CBM-201502.docx - Supplemental material

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Baseline characteristics of 911 included patients

Table 2
Univariate and multivariate cox regression analysis for factors predicting PFS

Table 4
Response rate and disease control rate according to LIPI groups