
==== Front
J Int Med Res
J Int Med Res
IMR
spimr
The Journal of International Medical Research
0300-0605
1473-2300
SAGE Publications Sage UK: London, England

39291412
10.1177/03000605241238689
10.1177_03000605241238689
Observational Study
Risk factors and nomograms for diagnosis and early death in patients with combined small cell lung cancer with distant metastasis: a population-based study
Yin Hui 12
Hu Zhi 2
https://orcid.org/0000-0003-3047-9051
Yang Jie 3
1 Department of Biochemistry and Molecular Biology, Basic Medical College, Qingdao University, Qingdao, China
2 Department of Thoracic Surgery, The First Affiliated Hospital Shaoyang University, Shaoyang, China
3 Department of Thoracic Surgery, 117970 The First Affiliated Hospital of Nanchang University , Nanchang, China
Jie Yang, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, China. Email: yangjie176@126.com
9 2024
18 9 2024
52 9 030006052412386898 11 2023
21 2 2024
© The Author(s) 2024
2024
SAGE Publications
https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Objective

Combined small cell lung cancer (CSCLC) with distant metastasis (DM) is an aggressive disease with a poor prognosis. Effective nomograms are needed to predict DM and early death in patients with CSCLC and DM.

Methods

This retrospective study included patients with CSCLC from the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Risk factors for DM and early death were analyzed by univariate and multivariate logistic regression. Nomograms were constructed based on the results in a training cohort and confirmed in a validation cohort, and their performances were assessed by concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

Results

A total of 788 patients with CSCLC were selected, including 364 patients with metastatic CSCLC. Sex, tumor site, T stage, and N stage were independent risk factors for DM, while age, surgery, chemotherapy, and liver metastasis were independent risk factors for early death. C-index, ROC, calibration, and DCA curve analyses all showed good predictive performances for both nomograms.

Conclusions

These nomograms could reliably predict DM risk in CSCLC patients and early death in CSCLC patients with DM, and may thus help clinicians to assess these risks and implement individualized therapies.

Combined small cell lung cancer
distant metastasis
risk factor
early death
nomogram
prediction
typesetterts2
==== Body
pmcIntroduction

According to the Global Cancer Statistics 2020, lung cancer was the leading cause of cancer mortality worldwide, with an estimated 2.2 million new cases and 1.8 million new deaths in 2020. 1 Small cell lung cancer (SCLC) is characterized as a highly lethal and aggressive type, accounting for around 15% of lung cancer cases, while non-small cell lung cancer (NSCLC) accounts for nearly 80%. The World Health Organization Histology Criteria 2015 defined CSCLC as a subset of SCLC diagnosed by pathological biopsy including components of both SCLC and any other subtype of NSCLC, such as adenocarcinoma, squamous cell carcinoma, or large cell carcinoma. 2 The incidence of CSCLC is variable, accounting for approximately 5% to 20% of all SCLC cases. 3 SCLC is a recalcitrant carcinoma with high propensities for metastasis and recurrence. Approximately one third of patients with SCLC are initially diagnosed with early-stage disease, while around 70% of cases are diagnosed at an advanced stage.4,5 In a retrospective study of 181 patients with CSCLC, 99 patients (54.7%) had recurrence after surgery, leading to poor survival. 6 Although standard chemotherapy and radiation plus immune checkpoint inhibitors have been recommended, survival is still limited, especially in patients with SCLC and distant metastasis (DM). It is therefore imperative to identify patients with CSCLC at high risk of metastasis.

In a study of 43,156 patients with T1-2 NSCLC, 6944 patients (16.09%) developed DM, and race, sex, histology, T and N stage, marital status, tumor size, grade, and laterality were all identified as independent risk factors for metastasis. 7 In another series of 18,187 patients with SCLC, 22.07% of patients were diagnosed with bone metastasis, with a median survival of 6 months, with age, sex, N stage, and tumor size all related to bone metastasis. 8 Zhao et al. reported that low expression levels of Cullin5 and SOCS3 promoted metastasis, drug-resistance, and a poor prognosis in SCLC [13]. Other research also revealed that high neuron-specific enolase, neutrophil-to-lymphocyte, Friend leukemia virus integration 1, and the long noncoding RNA CCAT2 were associated with SCLC metastasis.9–11 Risk factors for metastasis based on laboratory markers have been identified in patients with NSCLC and SCLC; however, the risk factors based on clinicopathological parameters correlated with metastatic CSCLC remain unclear.

The treatment response is currently transient in most patients with SCLC and DM, resulting in a median survival of 1 year. In a comprehensive analysis of 358 patients with extensive-stage disease, 43.8% of patients died within 12 months, 11 while another study in China also reported a median survival of just 11 months, and 58.4% of patients with extensive-stage SCLC died within 1 year. 12 Patients with CSCLC and DM are prone to early death, defined as an overall survival time of less than 3 months after diagnosis. Identification of the factors contributing to early death may help clinicians to develop individualized treatment strategies, which might in turn improve overall survival and alleviate the suffering caused by the disease. There are currently no published in-depth studies on mortality within 3 months of metastatic CSCLC. There is thus a need for a simple-to-use, predictive model to distinguish the potential risk factors for early death.

Nomograms are widely used to predict DM and early death in cancer patients; however, most existing nomograms are derived from patients with metastatic SCLC or CSCLC without DM, and there are no nomograms for diagnosis and early death in patients with CSCLC and DM.

We therefore aimed to construct novel nomograms to predict DM in patients with CSCLC and early death in patients with CSCLC and DM, based on demographic and clinicopathologic variables from the Surveillance, Epidemiology, and End Results (SEER) database. The resulting nomograms may facilitate individualized patient care and medical therapy.

Materials and methods

Patients and data collection

This retrospective study used data extracted from the SEER database between 2004 and 2015. The inclusion criteria were as follows: (a) malignant tumor located in the main bronchus and lung (site code: C340-C349); (b) patients diagnosed with primary CSCLC (histology code: 8045); (c) diagnostic confirmation based on positive histology, laboratory test/marker, or microscopic confirmation; and (d) complete T stage, N stage, and M stage according to the 6th edition American Joint Committee on Cancer staging system. We excluded patients with unknown overall survival time. Data on clinical variables including age at diagnosis, sex, race, grade, tumor site, surgery, chemotherapy, radiotherapy, lung metastasis, brain metastasis, bone metastasis, and liver metastasis were also obtained. We also excluded patients with missing data on race. Age at diagnosis was divided into under 60 years old, 60 to 70 years old, and over 70 years old. Tumor grade was divided into grade I to II, grade III to IV, and unknown.

Patients were divided randomly into training and validation cohorts at a ratio of 7:3, using R software (www.r-project.org). The selection processes for the two study cohorts are shown in Figure 1.

Figure 1. Study selection process. CSCLC, combined small cell lung cancer; DM, distant metastasis; SEER, Surveillance, Epidemiology, and End Results database.

This retrospective study was approved by the Institutional Review Board of The First Affiliated Hospital Shaoyang University and was exempt from the need for informed consent. All information from the SEER database has been de-identified and no personal identifying information was used in our analysis, and informed consent was therefore not required. The reporting of this study conforms to STROBE guidelines. 13

Statistical analysis

All statistical analyses were carried out using R software (version 4.0.3) and a P-value <0.05 (two-sided) was considered statistically significant. Numbers and percentages were used to summarize categorical variables. The training and validation cohorts were extracted randomly using R software at a ratio of 7:3, and the distribution and difference between the two cohorts were examined by χ2 or Fisher’s exact tests. Independent risk factors for DM in patients with CSCLC and for early death in patients with CSCLC and DM were analyzed by univariate and multivariate logistic regression analyses. Risk factors with a P-value <0.05 in univariate analysis were included in the multivariate analysis. A predictive nomogram was constructed based on the results of multivariate analysis in the training cohort and was validated in the validation cohort using the “rms” package. The discrimination abilities of the nomograms in both the training and validation cohorts were determined using receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC), and the C-index. Calibration curves were plotted to determine the consistency between the predicted and actual probabilities. Decision curve analysis (DCA) curves were generated to evaluate the clinical benefits and improved performance of the nomogram.

Results

Baseline characteristics

A total of 788 patients diagnosed with primary CSCLC met the inclusion criteria and were enrolled in the present study between 2004 and 2015, including 364 patients (46.2%) diagnosed with DM. The patients’ baseline characteristics are presented in Table 1. The DM rates were similar in the training and validation cohorts (46.5% and 45.6%, respectively).

Table 1. Baseline characteristics of patients with combined small cell lung cancer.

	Overall	Training cohort	Validation cohort	P	
(n = 788)	(n = 551)	(n = 237)	
Age, years					
 <60	179 (22.7%)	128 (23.2%)	51 (21.5%)	0.834	
 60–70	302 (38.3%)	208 (37.7%)	94 (39.7%)		
 >70	307 (39.0%)	215 (39.0%)	92 (38.8%)		
Sex					
 Female	349 (44.3%)	236 (42.8%)	113 (47.7%)	0.212	
 Male	439 (55.7%)	315 (57.2%)	124 (52.3%)		
Race					
 Black	100 (12.7%)	71 (12.9%)	29 (12.2%)	0.944	
 Other	32 (4.1%)	22 (4.0%)	10 (4.2%)		
 White	656 (83.2%)	458 (83.1%)	198 (83.5%)		
Grade					
 I–II	48 (6.1%)	39 (7.1%)	9 (3.8%)	0.0525	
 III–IV	407 (51.6%)	292 (53.0%)	115 (48.5%)		
 Unknown	333 (42.3%)	220 (39.9%)	113 (47.7%)		
Site					
 Left upper lobe	202 (25.6%)	146 (26.5%)	56 (23.6%)	0.905	
 Left lower lobe	90 (11.4%)	62 (11.3%)	28 (11.8%)		
 Right upper lobe	236 (29.9%)	164 (29.8%)	72 (30.4%)		
 Right middle lobe	33 (4.2%)	23 (4.2%)	10 (4.2%)		
 Right lower lobe	93 (11.8%)	66 (12.0%)	27 (11.4%)		
 Main bronchus	59 (7.5%)	37 (6.7%)	22 (9.3%)		
 Unspecific	75 (9.5%)	53 (9.6%)	22 (9.3%)		
T					
 T1	175 (22.2%)	119 (21.6%)	56 (23.6%)	0.819	
 T2	265 (33.6%)	188 (34.1%)	77 (32.5%)		
 T3	33 (4.2%)	25 (4.5%)	8 (3.4%)		
 T4	315 (40.0%)	219 (39.7%)	96 (40.5%)		
N					
 N0	260 (33.0%)	181 (32.8%)	79 (33.3%)	0.623	
 N1	79 (10.0%)	51 (9.3%)	28 (11.8%)		
 N2	336 (42.6%)	236 (42.8%)	100 (42.2%)		
 N3	113 (14.3%)	83 (15.1%)	30 (12.7%)		
M					
 M0	424 (53.8%)	295 (53.5%)	129 (54.4%)	0.876	
 M1	364 (46.2%)	256 (46.5%)	108 (45.6%)		

DM-related risk factors

We explored potential risk factors for DM by univariate logistic regression analysis. Sex, tumor site, T stage, and N stage were all correlated with DM (P < 0.05) and were further included in multivariate analysis, which identified male sex, main bronchus, T4 stage, and higher N stage as independent risk factors for DM in patients with CSCLC (Table 2).

Table 2. Univariate and multivariate logistic regression analyses of risk factors associated with distant metastasis in patients with combined small cell lung cancer.

	Univariate analysis	Multivariate analysis	
	HR	95%CI	P	HR	95%CI	P	
Age, years							
 <60	Reference						
 60–70	0.796	0.512–1.239	0.312	1.989	0.831–4.759	0.122	
 >70	1.016	0.656–1.574	0.943	3.224	1.345–7.724	0.009	
Sex							
 Female	Reference						
 Male	1.700	1.207–2.394	0.002	1.899	1.291–2.792	0.001	
Race							
 Black	Reference						
 Other	2.204	0.802–6.055	0.125				
 White	0.841	0.510–1.387	0.497				
Grade							
 I–II	Reference						
 III–IV	0.726	0.371–1.422	0.350				
 Unknown	1.564	0.789–3.099	0.200				
Tumor site							
 Left upper lobe	Reference						
 Left lower lobe	1.168	0.644–2.119	0.609	1.118	0.582–2.146	0.737	
 Right upper lobe	0.719	0.456–1.134	0.156	0.665	0.405–1.092	0.107	
 Right middle lobe	1.938	0.789–4.762	0.149	2.205	0.846–5.749	0.106	
 Right lower lobe	0.712	0.391–1.295	0.266	0.670	0.349–1.284	0.228	
 Main bronchus	3.365	1.518–7.455	0.003	2.391	1.016–5.626	0.046	
 Unspecific	2.639	1.360–5.120	0.004	1.377	0.674–2.813	0.380	
T							
 T1	Reference						
 T2	1.646	0.993–2.729	0.053	1.291	0.757–2.203	0.3489	
 T3	2.620	1.081–6.349	0.033	1.781	0.697–4.55	0.2281	
 T4	5.450	3.321–8.945	<0.001	3.536	2.067–6.048	<0.001	
N							
 N0	Reference						
 N1	1.600	0.837–3.059	0.155	1.397	0.693–2.819	0.350	
 N2	3.042	2.016–4.592	<0.001	2.242	1.428–3.519	<0.001	
 N3	4.619	2.654–8.041	<0.001	2.985	1.640–5.434	<0.001	
HR, hazard ratio; CI, confidence interval.

Nomogram construction and validation

We constructed a diagnostic risk nomogram based on the four independent risk factors in multivariate analysis (Figure 2). The C-indexes in the training and validation cohorts were 0.769 (95% confidence interval: 0.730–0.808) and 0.764 (0.704–0.823), respectively, and the AUCs of the ROC curves were 0.769 (0.729–0.808) and 0.769 (0.704–0.824), respectively, indicating that both these factors showed good discrimination (Figure 3a, b). Calibration curves showed good consistency for predicting DM between the predicted and actual results (Figure 3c, d). In addition, DCA showed that the nomogram provided excellent benefits. A larger net benefit was associated with a better predictive performance of the diagnostic risk model, implying that the nomogram could provide an effective and precise tool for DM prediction (Figure 3e, f).

Figure 2. Diagnostic nomogram for predicting distant metastasis in patients with combined small cell lung cancer. Tumor site code: 1: left upper lobe; 2: left lower lobe; 3: right upper lobe; 4: right middle lobe; 5: right lower lobe; 6: main bronchus; 7: unspecific. DM, distant metastasis.

Figure 3. Validation of the diagnostic nomogram. Receiver operating characteristic curve (a), calibration curve (c), and decision curve analysis (DCA) (e) in the training cohort, and receiver operating characteristic curve (b), calibration curve (d), and DCA (f) in the validation cohort. DM, distant metastasis; AUC, area under the curve.

Factors associated with early death

Patients lacking data on surgery, radiotherapy, and chemotherapy were excluded from the study on early death, and this cohort therefore included 363 patients with metastatic CSCLC, including 150 patients (41.3%) who experienced early death. The demographic characteristics of all patients with DM are summarized in Table 3. There were no significant differences between the training and validation cohorts. Univariate and multivariate logistic regression analyses identified four independent risk factors associated with early death in patients with DM, namely age, surgery, chemotherapy, and liver metastasis (Table 4).

Table 3. Baseline characteristics of patients with combined small cell lung cancer and distant metastasis.

	Overall	Training cohort	Validation cohort	P	
(n = 363)	(n = 254)	(n = 109)	
Age					
 <60	88 (24.2%)	62 (24.4%)	26 (23.9%)	0.239	
 60–70	131 (36.1%)	98 (38.6%)	33 (30.3%)		
 >70	144 (39.7%)	94 (37.0%)	50 (45.9%)		
Sex					
 Female	135 (37.2%)	92 (36.2%)	43 (39.4%)	0.556	
 Male	228 (62.8%)	162 (63.8%)	66 (60.6%)		
Race					
 Black	50 (13.8%)	31 (12.2%)	19 (17.4%)	0.080	
 Other	19 (5.2%)	17 (6.7%)	2 (1.8%)		
 White	294 (81.0%)	206 (81.1%)	88 (80.7%)		
Grade					
 I–II	20 (5.5%)	13 (5.1%)	7 (6.4%)	0.605	
 III–IV	153 (42.1%)	104 (40.9%)	49 (45.0%)		
 Unknown	190 (52.3%)	137 (53.9%)	53 (48.6%)		
T					
 T1	39 (10.7%)	28 (11.0%)	11 (10.1%)	0.215	
 T2	96 (26.4%)	60 (23.6%)	36 (33.0%)		
 T3	14 (3.9%)	12 (4.7%)	2 (1.8%)		
 T4	214 (59.0%)	154 (60.6%)	60 (55.0%)		
N					
 N0	71 (19.6%)	42 (16.5%)	29 (26.6%)	0.119	
 N1	29 (8.0%)	22 (8.7%)	7 (6.4%)		
 N2	190 (52.3%)	134 (52.8%)	56 (51.4%)		
 N3	73 (20.1%)	56 (22.0%)	17 (15.6%)		
Tumor site					
 Left upper lobe	82 (22.6%)	59 (23.2%)	23 (21.1%)	0.514	
 Left lower lobe	38 (10.5%)	26 (10.2%)	12 (11.0%)		
 Right upper lobe	98 (27.0%)	67 (26.4%)	31 (28.4%)		
 Right middle lobe	20 (5.5%)	14 (5.5%)	6 (5.5%)		
 Right lower lobe	32 (8.8%)	24 (9.4%)	8 (7.3%)		
 Main bronchus	44 (12.1%)	35 (13.8%)	9 (8.3%)		
 Unspecific	49 (13.5%)	29 (11.4%)	20 (18.3%)		
Surgery					
 No	333 (91.7%)	235 (92.5%)	98 (89.9%)	0.411	
 Yes	30 (8.3%)	19 (7.5%)	11 (10.1%)		
Radiation					
 No	197 (54.3%)	135 (53.1%)	62 (56.9%)	0.566	
 Yes	166 (45.7%)	119 (46.9%)	47 (43.1%)		
Chemotherapy					
 No	143 (39.4%)	99 (39.0%)	44 (40.4%)	0.816	
 Yes	220 (60.6%)	155 (61.0%)	65 (59.6%)		
Lung metastasis					
 No	124 (34.2%)	91 (35.8%)	33 (30.3%)	0.417	
 Yes	46 (12.7%)	29 (11.4%)	17 (15.6%)		
 Unknown	193 (53.2%)	134 (52.8%)	59 (54.1%)		
Brain metastasis					
 No	129 (35.5%)	93 (36.6%)	36 (33.0%)	0.668	
 Yes	43 (11.8%)	28 (11.0%)	15 (13.8%)		
 Unknown	191 (52.6%)	133 (52.4%)	58 (53.2%)		
Bone metastasis					
 No	117 (32.2%)	80 (31.5%)	37 (33.9%)	0.825	
 Yes	56 (15.4%)	41 (16.1%)	15 (13.8%)		
 Unknown	190 (52.3%)	133 (52.4%)	57 (52.3%)		
Liver metastasis					
 No	115 (31.7%)	79 (31.1%)	36 (33.0%)	0.784	
 Yes	57 (15.7%)	42 (16.5%)	15 (13.8%)		
 Unknown	191 (52.6%)	133 (52.4%)	58 (53.2%)		
Early death					
 No	213 (81.0%)	149 (58.7%)	64 (58.8%)	0.999	
 Yes	150 (19.0%)	105 (41.3%)	45 (41.2%)		

Table 4. Univariate and multivariate logistic regression analyses of risk factors associated with early death in patients with combined small cell lung cancer and distant metastasis.

	Univariate analysis		Multivariate analysis		
	HR	95%CI	P	HR	95%CI	P	
Age, years							
 <60	Reference						
 60–70	1.750	0.878–3.486	0.112	1.989	0.831–4.759	0.122	
 >70	2.882	1.447–5.742	0.003	3.224	1.345–7.724	0.009	
Sex							
 Female	Reference						
 Male	1.655	0.973–2.815	0.063				
Race							
 Black	Reference						
 Other	3.333	0.967–11.487	0.056				
 White	1.227	0.559–2.694	0.610				
Grade							
 I–II	Reference						
 III–IV	1.619	0.418–6.269	0.485				
 Unknown	3.285	0.866–12.458	0.080				
Tumor site							
 Left upper lobe	Reference						
 Left lower lobe	1.950	0.763–4.987	0.163	1.337	0.418–4.274	0.625	
 Right upper lobe	0.890	0.422–1.878	0.760	0.867	0.344–2.183	0.762	
 Right middle lobe	1.950	0.600–6.335	0.267	0.902	0.192–4.233	0.896	
 Right lower lobe	2.305	0.876–6.062	0.091	0.981	0.284–3.393	0.976	
 Main bronchus	1.300	0.547–3.087	0.552	1.062	0.363–3.109	0.912	
 Unspecific	2.762	1.107–6.895	0.029	2.696	0.872–8.339	0.085	
T							
 T1	Reference						
 T2	1.346	0.507–3.575	0.551				
 T3	0.227	0.025–2.060	0.188				
 T4	2.373	0.986–5.715	0.054				
N							
 N0	Reference						
 N1	1.275	0.430–3.782	0.662				
 N2	1.809	0.865–3.782	0.115				
 N3	1.673	0.721–3.881	0.231				
Surgery							
 No	Reference						
 Yes	0.070	0.009–0.533	0.010	0.060	0.006–0.563	0.014	
Radiotherapy							
 No	Reference						
 Yes	0.415	0.247–0.695	0.001	1.130	0.568–2.25	0.728	
Chemotherapy							
 No	Reference						
 Yes	0.084	0.046–0.154	<0.001	0.070	0.034–0.146	<0.001	
Lung							
 No	Reference						
 Yes	1.183	0.505–2.775	0.699				
 Unknown	1.319	0.765–2.274	0.319				
Brain metastasis							
 No	Reference						
 Yes	1.504	0.640–3.534	0.349				
 Unknown	1.342	0.779–2.311	0.289				
Bone metastasis							
 No	Reference						
 Yes	1.012	0.467–2.189	0.977				
 Unknown	1.222	0.694–2.152	0.486				
Liver metastasis							
 No	Reference						
 Yes	2.242	1.042–4.824	0.039	3.585	1.336–9.620	0.011	
 Unknown	1.529	0.855–2.735	0.152	1.495	0.701–3.192	0.298	
HR, hazard ratio; CI, confidence interval.

Nomogram construction and validation

We constructed a nomogram to predict early death in patients with CSCLC and DM based on the independent risk factors screened by multivariate analysis (Figure 4). The C-indexes in the training and validation cohorts were 0.840 (0.792–0.889) and 0.898 (0.833–0.963), respectively, and the AUCs were 0.840 (0.791–0.89) and 0.898 (0.833–0.964), respectively (Figure 5a, b). The calibration curves were good predictors and observers in terms of early death risk (Figure 5c, d). In addition, DCA showed a significant improvement in the net benefit of the nomogram with a wide range of threshold probabilities in both the training and validation sets, implying good clinical application value of this nomogram (Figure 5e, f).

Figure 4. Risk nomogram for predicting early death in patients with combined small cell lung cancer and distant metastasis. Tumor site code: 1: left upper lobe; 2: left lower lobe; 3: right upper lobe; 4: right middle lobe; 5: right lower lobe; 6: main bronchus; 7: unspecific.

Figure 5. Validation of the risk nomogram. Receiver operating characteristic curve (a), calibration curve (c), and decision curve analysis (DCA) (e) in the training cohort, and receiver operating characteristic curve (b), calibration curve (d), and DCA (f) in the validation cohort. EM, early death; AUC, area under the curve.

Discussion

To the best of our knowledge, this was the first study to identify independent risk factors for DM and early death in patients with CSCLC based on a large-scale, population-based, national cancer database. We also established two risk nomograms with reliable accuracy and discriminative ability and validated these by ROC, calibration, and DCA curves. The results suggested that these two nomograms may provide a practical tool to help clinicians identify patients at high risks of DM and early death, as well as to determine the optimal clinical interventions for patients diagnosed with metastatic CSCLC.

The incidence of DM at the time of initial diagnosis of SCLC is generally more than 60%, and patients with metastatic SCLC have poorer overall and median survival, 14 whereas the incidence of DM in the current cohort was only 46.3%. Accurately identifying patients at high risk of metastasis may facilitate the implementation of individualized therapeutic strategies; however, despite extensive research on extensive-stage SCLC, studies focusing on metastatic CSCLC are scarce. Cai et al. indicated that the liver was the most common metastatic site and the lung was the least common, 15 and Lu et al. established a diagnostic nomogram based on age, sex, N stage, and tumor size to predict liver metastasis with good accuracy in SCLC. 16 Other researchers exploring metastasis-related factors in SCLC validated some laboratory markers, such as interferon-induced transmembrane protein 1, KMT2C, and DLL3, as useful and efficient biomarkers to estimate the risk of metastasis in SCLC17–19; however, these are expensive, time-consuming, and invasive, thus limiting their clinical use, and their accuracy and efficiency have not been confirmed in large cohorts. Nomograms based on clinical variables have been used to predict DM efficiently in other tumors. Chao et al. combined age, sex, T stage, N stage, histology, tumor location, and pathological grade to predict metastasis in esophageal cancer, 20 while a nomogram based on race, age, primary site, tumor depth, size, and grade was established in patients with superficial gastric cancer without lymph node metastasis. 21 Nevertheless, no studies have concentrated on metastasis in CSCLC based on clinical characteristics.

In the current study, we identified four risk factors for DM in CSCLC using logistic regression analyses, namely sex, tumor site, T stage, and N stage. As for other tumors, T stage and N stage were confirmed to be associated with DM in CSCLC.19,22 Patients with centrally located primary tumors have visibly worse survival outcomes compared with patients with peripheral SCLC. 23 This may support the current finding that DM was more frequently associated with CSCLC located in the main bronchus, but further investigations are required to clarify this phenomenon. Males are predominant in both SCLC and CSCLC,12,24,25 and male sex was associated with a high probability of DM, as reported in previous studies.8,14,22

Similarly, a novel tool was established to predict early death in patients with uterine sarcoma, which provided a better prediction than the FIGO stage system. 26 Shi et al. also built a model to predict early death in patents with stage IV esophageal cancer based on histological grade, chemotherapy, liver metastasis, and bone metastasis. 27 These studies demonstrate the feasibility and significance of nomograms for predicting early mortality in patients with cancer. Notably however, recent studies have focused on the prognoses of patients with NSCLC and SCLC without metastases or with brain metastasis, and early death in patients with CSCLC and DM has not been explored. Shen et al. revealed that age and liver metastasis were risk factors for early death in patients with lung cancer with synchronous brain metastasis, 28 while another study demonstrated that age, surgery, and chemotherapy were independent risk factors for early death in patients with advanced epithelial ovarian cancer (both FIGO stage III–IV). 29 In line with these studies, we found that age was significantly correlated with early death in patients with metastatic CSCLC. Wang et al. reported that extensive disease, no surgery, elevated neuron-specific enolase, and elevated neutrophil/lymphocyte ratio were associated with worse prognosis in patients with CSCLC, 25 while surgical resection significantly improved overall and lung cancer-specific survival in a propensity score-matched analysis of stage III SCLC patients from America and China. 30 In the current study, surgery improved the risk of early death in patients with metastatic CSCLC; notably however, the limited number of patients with metastatic CSCLC undergoing surgery means that this result must be treated with caution, and more large prospective clinical trials are needed to clarify the benefits of surgery in patients with CSCLC and DM. In a study of 207 patients with metastatic SCLC, response to chemotherapy was the most important factor related to a better prognosis. 31 Although chemotherapy plus immune checkpoint inhibitors are recommended for patients with extensive-stage SCLC, platinum plus etoposide has also been recommended for many years and is a common treatment for advanced SCLC in clinical practice.32,33 Chemotherapy reduced the risk of early death in patients with metastatic CSCLC in our study, consistent with previous reports.34,35 The benefits of radiotherapy for metastatic CSCLC thus remain unknown and require further investigation.

Liver metastasis was usually an early event whereas bone and brain metastases tended to be late occurrences in a series of 1009 patients with SCLC. 23 In addition, patients with extensive-stage with liver metastasis alone or in combination with other organs have worse outcomes. The liver is the most common site of DM in solid tumors because of its anatomical location and vascular features. 36 Moreover, Wu et al. revealed that liver metastasis was an independent prognostic factor leading to shorter progression-free and overall survival in patients with stage IV lung adenocarcinoma (median progression-free survival, 6.7 vs 11.2 months, P < 0.001; median overall survival, 9.2 vs 17.5 months, P < 0.001). 37 As expected and in line with published data, our study showed that the liver was the most metastatic organ, associated with a significantly increased risk of early death.

This study had some limitations. First, this was a retrospective study with potential selection bias, and prospective randomized controlled studies are therefore required to confirm our results. Second, inherent bias could not be avoided because of the lack of external validation. Third, no detailed information on the CSCLC components was included because the data are not available in the SEER database. Finally, the data on tumor grade and metastatic organs were incomplete, and their impact on metastasis and early death may thus have been underestimated.

Conclusion

We comprehensively demonstrated that sex, tumor site, T stage, and N stage were independent risk factors for DM in patients with CSCLC, while age, liver metastasis, surgery, and chemotherapy were independent risk factors associated with early death in patients with CSCLC and DM. These simple-to-use nomograms will facilitate precise clinical decision-making and improve the prognosis for patients with metastatic CSCLC.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605241238689 - Supplemental material for Risk factors and nomograms for diagnosis and early death in patients with combined small cell lung cancer with distant metastasis: a population-based study

Supplemental material, sj-pdf-1-imr-10.1177_03000605241238689 for Risk factors and nomograms for diagnosis and early death in patients with combined small cell lung cancer with distant metastasis: a population-based study by Hui Yin, Zhi Hu and Jie Yang in Journal of International Medical Research

Acknowledgements

We thank the developers of the R package who shared their code freely. We also acknowledge the contribution of the SEER database for access to the data.

Author contributions: The study was conceptualized and designed by HY and ZH. The figures and tables were generated by HY. Statistical results were completed by HY. The initial manuscript was written by HY and ZH. This study was scrutinized in every aspect by JY who critically reviewed the original article.

None.

Funding: None.

ORCID iD: Jie Yang https://orcid.org/0000-0003-3047-9051
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