Efficacy of chemotherapy combined with local therapy in patients with oligometastatic non-small cell lung cancer: a SEER-based study (2024)

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Background & Aims: Localized therapy (LCT) is becoming increasingly important in the treatment of patients with oligometastatic non-small cell lung cancer (OM-NSCLC). However, the optimal timing of LCTin relation to systemic treatment remains unclear. This study aimed to develop a novel predictive nomogram to identify specific OM-NSCLC populations who could benefit from LCT.

Methods: 14,920 OM-NSCLC patients between 2010 and 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. Propensity score matching (PSM) and Kaplan-Meier Survival Curve were conducted to evaluate the influence of chemotherapy combined with local therapy(CCLCT) on the prognosis. Univariate and multivariate Cox regression models were utilized to determine potential risk factors, and a nomogram of overall survival (OS) at different times was formulated. The area under the receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA) and a risk stratification system were used to validate the nomograms.

Results: The most favorable prognostic survival was observed in patients receiving a combination of chemotherapy and surgery, followed by those undergoing chemotherapy, surgery and radiotherapy. Conversely, patients receiving only chemotherapy or a combination of chemotherapy and radiotherapy had the lowest and comparably similar prognostic survival outcomes. Specifically, chemotherapy combined with surgery is an effective treatment option to improve prognostic survival among OM-NSCLC patients, with a 19-month prolongation of median survival compared to chemotherapy alone. Independent prognostic risk factors utilized in the nomogram for predicting overall survival (OS) include therapy type, age, sex, race, primary tumor site, tumor size, presence of metastases (in the bone, brain, and liver), N stage, and tumor grade. The AUC demonstrated the good performance of the nomogram. A favorable consistency between the predicted and actual survival probabilities was demonstrated by adopting calibration curves. Finally, The DCA and the risk classification system further supported that the prediction model was clinically effective.

Conclusions: Chemotherapy combined with surgery is a highly effective treatment strategy for OM-NSCLC patients, significantly enhancing their prognostic survival. We constructed a novel nomogram to predict OS in OM-NSCLC patients, aiding both patients and healthcare professionals in assessing prognosis and facilitating informed clinical decisions.

oligometastatic non-small cell lung cancer

chemotherapy combined with surgery

propensity score matching

nomogram

SEER

According to Global Cancer Statistics 2020 (1), lung cancer was the second most frequent cancer and the leading cause of cancer death worldwide in terms of incidence and mortality, with up to 1.8 million deaths (18% of total cancer deaths). From the perspective of pathology and treatment, lung cancer can be roughly divided into two categories: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Notably, non-small cell lung cancer comprises approximately 80%-85% of cases. Roughly 66% of individuals diagnosed with non-small cell lung cancer (NSCLC) present with either local or distant metastases, which is linked to an unfavorable prognosis (2). Merely 15% of patients manage to survive beyond five years following their diagnosis. The most frequent sites of local metastasis are the lymph nodes (LNS) and the lungs on the opposite side, while distant metastases commonly manifest in the liver, brain, and bones (3).

Oligometastases are defined as no more than 3 limited distant metastatic organs. These patients seem to have a more indolent cancer compared to those with diffuse metastasis. Oligometastatic non-small cell lung cancer (OM-NSCLC) is a metastatic disease with a limited number of metastatic sites. It resembles an intermediate stage of NSCLC, between limited and extensive metastatic disease, even though there are no staging criteria to determine this distinction.

Patients with OM-NSCLC may benefit from chemotherapy in combination with aggressive local therapy, such as surgery and/or radiotherapy (4). What is the best way to combine chemotherapy with local treatment remains controversial (5), and a number of studies have concluded that tailoring treatment modalities to the individual has shown promising benefits (6, 7).

Therefore, capitalizing on the comprehensive data of the SEER database, this study aimed to explore the prognostic impact of chemotherapy combined with various local treatments on OM-NSCLC patients, and to develop a validated prognostic nomogram model to better understand the risk factors and accurately determine the prognosis. This model may assist clinicians in reaching a more appropriate clinical decision.

2.1 Data source

All patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database (8, 9), which covers approximately 35% of the US population across 17 states (10). We completed the registration form to obtain SEER*Stat (version 8.4.2) after reading and signing the Terms of Use Agreement. The SEER registry has granted us permission to access the data (authorization number: 24603-Nov2021).

2.2 Patients

In the present study, SEER*Stat was used to collect all the relevant data, including patients’ clinical information. The inclusion criteria were as follows: (1) patients with oligometastatic non-small cell lung cancer (OM-NSCLC) registered between 2010 and 2015; (2) primary site: C34.0-C34.3, C34.8-C34.9; (3) histological codes: squamous cell carcinoma (8051-8052, 8070-8078, 8083-8084, 8090, 8094, 8123), adenocarcinoma: (8015, 8050, 8140-8141, 8143-8145, 8147, 8190, 8201, 8211, 8250-8255, 8260, 8290, 8310, 8320, 8323, 8333, 8401, 8440, 8470-8471, 8480-8481, 8490, 8503, 8507, 8550, 8570-8572, 8574, 8576), large cell carcinoma (8012-8014, 8021, 8034, 8082), not otherwise specified (8046, 8003-8004, 8022, 8030-8033, 8035, 8120, 8200, 8240-8241, 8243-8246, 8249, 8430, 8525, 8560, 8562, 8575) [in the light of the International Classification of Tumor Diseases Third Edition (ICD-O-3)]; (4) tumor metastases.

The exclusion criteria were as follows: (1) unknown cause-specific death classification and survival months; (2) unknown race and marital status; (3) unknown AJCC and TNM stage; (4) unknown metastases (lung, bone, brain and lymph node); (5) unknown tumor size and lymph nodes involvement; (6) unknown laterality and grade recode. Given that the SEER database was publicly accessible, Institutional Review Board approval was not required for the present study(Figure 1).

2.3 Clinical variables

Information on demographic factors (age, sex, race and marital status), tumor-related factors (primary site, histological codes (ICD-O-3), tumor metastases [lung, bone, brain and lymph node], tumor size, lymph nodes involvement, laterality, grade recode, 7th edition AJCC and TNM stage), therapeutic factors (surgery, chemotherapy and radiotherapy), and follow-up (11 years) were extracted from the SEER database.

The clinical characteristics of the patients included age (<62, 62-71 and >71; segmentation using x-tile software), sex (male, female), race (white, black, Asian or Pacific Islander and American Indian/Alaska Native), marital status (married (including common law), single (never married), divorced, separated, widowed and unmarried or domestic partner), primary site (main bronchus; upper lobe, lung; middle lobe, lung; lower lobe, lung; overlapping lesion of lung and lung, nos), histological codes (squamous cell carcinoma, adenocarcinoma, large cell carcinoma and not otherwise specified (other)), tumor metastases (yes, no), tumor size (<=5 cm, 5-10 cm, >10cm), lymph nodes involvement (no regional lymph node involvement or isolated tumor cells (itcs) detected; axillary lymph node(s), ipsilateral; movable axillary lymph node(s), ipsilateral; fixed/matted ipsilateral axillary nodes; axillary/regional lymph node(s) and supraclavicular node(s), ipsilateral), laterality (left and right), grade recode (I, II, III and IV), T stage (T0, T1, T2, T3, T4 and TX), N stage (N0, N1, N2 and N3), M stage (M1a, M1b and M1nos), and therapy (chemotherapy and chemotherapy+local therapy (surgery, radiotherapy and surgery+radiotherapy)). All patients had AJCC stage IV.

2.4 Endpoint definition

The primary outcome for this analysis was overall survival (OS), which was defined as the time interval between the day of diagnosis and the day of death for any reason.

2.5 Statistical analysis

The PSM method was adopted to reduce the confounding effect caused by other factors and evaluate the survival benefits of chemotherapy and chemotherapy combined with local treatment patterns, matching at a ratio of 1:1 was performed using the nearest neighbor method, with a caliper value of 0.01 (11). Meanwhile, survival curves were plotted by the Kaplan-Meier (K-M) method and compared by the log-rank test.

All eligible cases were randomized in a 7:3 ratio into training cohort and test cohort. Descriptive statistics were used to compare the baseline characteristics between the training cohort and test cohort through a Chi-squared test. The training cohort was used to create nomograms and filter factors for nomograms, while the validation cohort was used to validate the results of the training cohort. Univariate Cox regression was used to identify factors associated with OS, and multivariate Cox regression to identify associated independent risk factors. Variables with P values < 0.05 in univariate Cox regression analysis were included in multivariate Cox regression analysis, and associated hazard ratios (HR) and 95% confidence intervals (CI) were calculated. Based on these identified prognostic factors, we developed a nomogram to predict OS rates at 1-, 2- and 3-years in OM-NSCLC patients (12). In addition, the areas under the receiver operating characteristic (ROC) curves (AUCs) were plotted to evaluate the discriminative performance of the nomogram (13). Calibration curves were generated to assess the accuracy and reliability of the nomogram (14). Decision curves analysis (DCA) was conducted to determine the applicability of the nomogram in clinical practice (15, 16). According to the median risk score, all patients with OM-NSCLC who received CCLCT were divided into high-risk and low-risk groups. Kaplan-Meier (K-M) survival curves with the log-rank test were performed to show the difference OS status between the two groups.

All statistical analyses were conducted using SPSS (version 26.0) and R software (version 4.0.2) and Stata (version 17.0). Two-side P-value < 0.05 was considered statistically significant.

3.1 Characteristics of patients

A total of 155,341 patients with OM-NSCLC in the SEER database were included in this study. In accordance with the exclusion criteria, 14,920 patients were enrolled and 21 variables were selected. The sociodemographic and clinicopathologic characteristics of all patients were summarized in Table 1. Among them, 66.81% of patients with OM-NSCLC were older than 62 years and 55% of patients were male patients. In addition, 78.92% of patients were white. More than half of the patients were married. The primary location was the upper lobe of the lung in more than half of the patients. Histologic type of the patient was predominantly adenocarcinoma (60.26%). 99.96% of patients had lymph node metastasis and 34.14% of patients had bone metastasis, but only 12.76% of patients had liver metastasis and 24.95% of patients had brain metastasis. The most frequent T, N and M stages were T4, N2 and M1b staging respectively. The vast majority of patients have tumors that are less than 10 cm in size. In terms of laterality, the right side is more common than the left side. Grade recode was primarily focused on stage III. Few patients received chemotherapy combined with surgery and radiotherapy (3.92%) and Chemotherapy combined with surgery (4.41%), while more than 90% received chemotherapy and chemotherapy combined with radiotherapy treatment modalities.

3.2 Propensity score matching (PSM)

To explore the impact of CCLCT on survival, we employed PSM to eliminate between-group differences chemotherapy and CCLCT, resulting in more reliable results.To evaluate the prognostic value of CCLCT in OM-NSCLC patients, we confirmed 6,294 patients who only received chemotherapy and 8,626 patients who received CCLCT. In the absence of PSM, there was significant imbalance in baseline demographic and clinical characteristics between the two groups. However, after 1:1 PSM, the covariates between groups were well balanced with a caliper width of 0.01, suggesting that PSM successfully reduced potential confounding.

We contrasted the OS of OM-NSCLC patients using Kaplan-Meier analysis and found no significant difference in survival between patients who received only chemotherapy and those who received CCLCT (OS: log-rank=2.06, p=0.15; Figure 2). The median survival was 10 months for both groups. A further comparison of the different localized treatment modalities revealed significant differences in survival outcomes (OS: log-rank=124.18, p<0.001; Figure 3). The best prognostic survival was observed in patients who received chemotherapy combined with surgery, followed by those who underwent chemotherapy, surgery and radiotherapy. In contrast, patients who received only chemotherapy or chemotherapy combined with radiotherapy had the lowest and similar prognostic survival outcomes. The median survival for patients receiving chemotherapy combined with surgery was 29 months, which was the best prognostic survival outcome. This was followed by chemotherapy, surgery and radiotherapy with a median survival of 16 months. In comparison, the worst treatment modalities were chemotherapy alone and chemotherapy combined with radiotherapy, which had median survivals of 10 and 9 months, respectively.

3.3 Univariate and multivariate analysis

Since chemotherapy combined with various local treatment modalities yields distinct prognostic outcomes, further analyses were conducted using data from 1,636 patients who received chemotherapy with local therapy. We divided the data into a training cohort (1,145 patients) and a test cohort (491 patients) in a 7:3 ratio. A comparison of clinical characteristics was operated between patients in the training and internal validation cohorts showed comparability, as there were no significant differences (P > 0.05) in the distribution of clinical characteristics (Table 2).

The univariate and multivariate Cox regression analysis of OS and CSS rates in the training cohort was carried out for screening independent prognostic variables. In the univariate Cox analysis, the following features were significantly related to OS: age, sex, race, primary site, histological codes, bone metastasis, brain metastasis, liver metastasis, N stage, M stage, tumor size, lymph nodes involvement, grade recode and therapy. Histological codes, M stage and lymph nodes involvement were then excluded by multivariate analysis, leaving eleven recognized risk factors: age, sex, race, primary site, bone metastasis, brain metastasis, liver metastasis, N stage, tumor size, grade recode and therapy.

By analyzing the results of multifactorial COX regression, the risk of survival increased with age. Male patients exhibited a higher risk compared to females. American Indian/Alaska Native patients displayed more favorable survival outcomes. Patients with primary tumors in part of a lobe have better prognostic outcomes than those with tumors spanning multiple lobes or located in the main bronchus. Lymph node metastases occurred in all patients. For either metastasis, the occurrence of metastases significantly reduced survival outcomes. Additionally, a higher risk was associated with more advanced stages in terms of N stage and grade recode. Using tumor size < 5 cm as a reference, with the increase of tumor size, the survival risk gradually increased. Patients who received chemotherapy combined with surgery had the best prognosis and survival, followed by patients who received chemotherapy combined with surgery combined with radiotherapy. Patients who received chemotherapy alone or chemotherapy combined with radiotherapy had the lowest survival rate.

Subsequently, a total of 11 predictors: age, sex, race, primary site, bone metastasis, brain metastasis, liver metastasis, N stage, tumor size, grade recode and therapy were utilized to construct the nomogram. Confidence intervals (CI) and corresponding p-values for specific variables in the univariate and multivariate analyses of OS were summarized in Tables 3 respectively.

3.4 Nomogram development and validation

According to the independent and significant risk factors identified by the multivariable Cox regression analysis, a nomogram was utilized for predicting 1-, 2- and 3-years OS in OM-NSCLC patients (Figure 4). The nomogram shows that race has the greatest impact on prognosis, followed by therapy, primary site, grade recode and tumor size, while sex contributes the least to survival outcomes. Each level of these variable was assigned a score on the points scale. The total score, obtained by summing the scores for each selected variable, was used to predict the 1-, 2- and 3- year OS for OM-NSCLC patients.

We contrasted the Area Under the Curve (AUC) of each cohort (Figure 5). In the training cohort, the AUC of predicting the 1-, 2- and 3-years OS were 0.701, 0.762 and 0.802, respectively. In the validation cohort, the AUC for 1-, 2- and 3-years OS were 0.729, 0.756 and 0.801, respectively. These values demonstrate a satisfactory discriminatory ability of the model. Furthermore, calibration curves of the training and validation cohorts were described for 1-, 2- and 3-years OS (Figure 6). In this study, all calibration curves closely resembled the diagonal line, indicating a strong agreement between the observed outcomes and the predictions. Finally, the decision curve analysis (DCA) indicated that using the nomograms for risk management could present positive clinical benefit within a threshold probability ranged of approximately 30% to 90%. This encompassed the mortality probability of the patients, indicating a favorable clinical utility the nomogram (Figure 7). Therefore, our nomogram exhibited an excellent predictive ability for OM-NSCLS patients. The K–M curves indicated that the patients in the high-risk group had significantly worse OS than the patients in the low-risk group (Figures 8A, 8B).

Lung cancer plays a major fatal role in cancer-related deaths worldwide. Utilizing a large population using SEER data, the present study revealed that approximately 21% of all NSCLC patients had oligometastases. This represents the largest cohort of OM-NSCLC patients undergoing a CCLCT described to date. At present, multimodal comprehensive therapy represents the optimal treatment management strategy for OM-NSCLC based on the results discussed within a multidisciplinary tumor board (4). Thus, the utilization of the SEER database enables an accurate exploration the prognostic impacts of chemotherapy combined with various local therapies in OM-NSCLC patients, thereby identifying the population where the most effective treatment modality is applicable.

Based on the data obtained from the SEER database and following a 1:1 propensity score matching, the OS of OM-NSCLC patients treated with chemotherapy and CCLCT was contrasted using the Kaplan-Meier analysis. We revealed that the most favorable prognostic survival was found for chemotherapy combined with surgery, followed by the chemotherapy, surgery, and radiotherapy treatment regimen. In contrast, chemotherapy alone and the combination of chemotherapy and radiotherapy yielded the lowest and comparable prognostic survival rates. Therefore, chemotherapy combined with surgery is an effective treatment option to improve prognostic survival in patients with OM-NSCLC, with a 19-month prolongation of median survival compared to chemotherapy alone.

Deboever et al. (17) proposed that pulmonary resection as a means of maximum locoregional control in OM-NSCLC is feasible and safe, and may be associated with durable long-term survival benefits, which was similar to our research. Therefore, the treatment modality of chemotherapy combined with surgery can better achieve comprehensive control of OM-NSCLC patients both overall and locally (18). In addition to conventional surgical resection, local ablative treatment is considered as an important tool to prolong the survival of OM-NSCLC patients, which can significantly reduce the burden of tumor compared with radiochemotherapy (19, 20). Guerrero et al. (21) discovered that ablative treatments, including surgery, may provide longer survival and better local control times among OM-NSCLC patients. There is a rationale for the use of ablative local treatments, as most failures after chemotherapy occur at sites initially affected by disease, and these sites could be a source of further dissemination. However, radiotherapy, as an important tool of local treatment, cannot contribute to the prolongation of survival. This may be because radiotherapy has historically served as a palliative modality in OM-NSCLC (22, 23). While this approach has the potential to alleviate symptom burdens and enhance performance status, it has little to no effect on prolonging prognostic survival.

For OM-NSCLC patients treated with CCLCT, we identified a total of 11 independent risk factors associated with prognosis by univariate and multivariate analyses: race, therapy, primary site, grade recode, tumor size, N stage, liver metastasis, bone metastasis, age, brain metastasis and sex were included. In addition, we constructed a nomogram using the multivariable Cox regression to predict overall survival of those patients. Internal validation cohorts verified its accuracy, which was expected to provide more evidence for individualized treatment.

In this study, we found that the following factors were associated with predicting OS in patients with OM-NSCLC: chemotherapy combined with surgery, age < 62, female, american indian/alaska native, upper lobe of lung, no metastases (liver, bone and brain), tumor size < 5cm, N0 stage and grade IV. Our results also yielded several other insights that align with previous literature. Most patients tend to be elderly, male, and the most common histologic finding is adenocarcinoma (24). Caucasian and African-American patients have decreased OS relative to those with other ethnicities (25). In particular, a primary tumor located in the upper lobes of the lungs has a better prognosis.

With respect to pathological stage and tumor characteristics, tumor size, N stage and grade were associated with the prognosis of OM-NSCLC patients. Chao et al. (26) discovered that these may be used as the independent risk predictors associated with survival in OM-NSCLC. In general, large tumors grow in the body for a longer time and are prone to vascular invasion and metastasis. Ischemic necrosis is likely to occur within large tumors. This was consistent with the results of our study. The larger the tumor, the higher the prognostic risk for patients with OM-NSCLC. N stage and grade incorporate the status of regional lymph node involvement and the degree of difference between tumor and normal cells. Previous studies have indeed confirmed that these factors are significantly associated with survival time (27).

However, our study has limitations. First of all, the nomogram was established according to the SEER database. It neither necessarily represents the rest of the world nor includes important factors such as therapy criteria for chemotherapy (drug class, dose, duration and frequency), surgery (timing, parts, pre- and post-operative physical indicators) and radiotherapy (timing, volumes, dose, and fractionation schedules), tumor markers (carcinoembryonic antigen, neuron-specific enolase and squamous cell carcinoma antigen, etc.), smoking status. We cannot control these potential modifier effects due to the lack of these data in the SEER database. These will be the main part of our future research. Besides, our study was performed retrospectively, which inevitably has a selection bias that is difficult to adjust. Moreover, our prediction model has only been validated internally, and external validation or further prospective studies are necessary. It is suggested that a multicenter study including more therapeutic combination modalities and lung function variables of OM-NSCLC should be conducted.

Data availability statement

Existing datasets are available in a publicly accessible repository:

Publicly available datasets were analyzed in this study. This data can be found here: [https://seer.cancer.gov//authorization number: 24603-Nov2021].

Ethics statement

Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and the institutional requirements.

Author contributions

Conceptualization, Supervision and Validation: MH. Methodology, formal analysis and draft: XY and WL. Final draft approval: JY. Revision and literature research: KL. All authors contributed to the article and approved the submitted version.

Funding

Sichuan Province Major Development Program of 2022 (No.22ZDYF0376) and 2024 Sichuan Guiding Plan for the Transfer and Transformation of Scientific and Technological Achievements (No.24ZHSF0072)

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Thank you for the support of the Surveillance, Epidemiology and End Results (SEER) database.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Table 1Demographic and clinical characteristics before and after PSM

PSM, propensity score matching;

Table2 Clinical characteristics of OM-NSCLC patients receiving CCLCT after PSM

Table3Univariate and multivariate analyses of prognostic factors for OS