Prognostic factors affecting mortality in elderly, low body mass index, and poor performance status groups with lung cancer: analysis of the 2016 Korean Association of Lung Cancer Registry (KALC-R) database

Introduction

Lung cancer remains a leading cause of cancer-related mortality worldwide, posing challenges in its management and treatment, particularly among patients with compromised health profiles. Traditionally, individuals of advanced age, those with poor performance status (PS) as measured by the Eastern Cooperative Oncology Group (ECOG) score, or those in an overly cachexic condition, indicated by a low body mass index (BMI), have been considered ineligible for aggressive treatment modalities due to an increased risk of treatment related morbidity (1-3). This subset of the patient population, often described as “frail” or “vulnerable”, has been marginalized in comprehensive lung cancer care. As cancer incidence is expected to increase in older adults, improvements in cancer management are needed for this population. However, studies of treatment outcome in older patients or patients with diminished performance status are relatively scarce, as these patients are usually excluded from clinical trials. The patients with old age or poor performance are frequently undertreated due to concomitant comorbidities, which could affect functional status and drug pharmacokinetics (4).

Recent advancements in lung cancer treatment, however, have brought a paradigm shift in treatment raising the possibility of treatment for populations who were previously not considered for lung cancer therapy. The advent of targeted therapies for driver mutations and the integration of immunotherapy into treatment regimens have redefined the therapeutic landscape. Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) has been used for elderly populations (5). For advanced non-small cell lung cancer (NSCLC) patients without targetable mutations, efficacy of the pembrolizumab single regimen has been studied in older populations. One meta-analysis showed that immune checkpoint inhibitor (ICI) monotherapy or combined therapy was associated with improved survival regardless of ECOG PS 0 or 1 (6). Also, in an international multicenter study, there was no significant association between baseline BMI and clinical outcome in patients with advanced NSCLC treated with first-line chemoimmunotherapy combinations (7).

In light of these developments, it is necessary to reassess the treatment outcomes and feasibility of such advanced therapies in vulnerable populations. The present study aims to evaluate the Korean Association of Lung Cancer Registry (KALC-R) database, which is representative of the nationwide population. This study aims to provide real-world evidence on treatment outcomes across varying clinical conditions, with a focus on patients with frail conditions such as old age, low BMI, or reduced performance status, who are often underrepresented. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-423/rc).

Methods

Study design and participants

This study analyzed data from the third nationwide KALC-R survey, a multi-center cancer registry from 13 regional cancer centers and 38 hospitals from which significant number of registrations were made (8). In 2016, the KALC-R registered 2,808 patients who were newly diagnosed with lung cancer with approximately 80 data fields including patient age, gender, BMI, symptoms, smoking history, performance status, histopathologic type, clinical stage [according to the eighth edition of the Tumor, Node, Metastasis (TNM) International Staging System], initial treatment modality, mutation status [i.e., EGFR mutation and anaplastic lymphoma kinase (ALK) translocation] and survival status. For patients with small cell lung cancer (SCLC), clinical stage was classified as limited or extensive stage (ES).

Based on the annual number of patients registered in each hospital, the sample size allocated to each hospital was decided after taking selection probability into account. After sorting patients by age, gender, date of the initial diagnosis, and the Surveillance, Epidemiology, and End Results (SEER) program summary stage (9). Information such as BMI, symptoms, and smoking history was obtained on the initial date of visit at the time of diagnosis. Patients were followed up until December 2019. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board at the Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea (No. UC23ZISE0213) and individual consent for this retrospective analysis was waived.

Statistical analysis

Data are expressed as the mean ± standard deviation or median [interquartile range (IQR)]. The Mann-Whitney U test was used to compare continuous variables, and the chi square or Fisher’s exact test was used to compare categorical variables. Cox proportional hazards models were implemented to investigate mortality risk factors. Variables with a P value <0.20 on univariate analysis were used in multivariate analysis. Survival was analyzed by the Kaplan-Meier method. All P values <0.05 were considered statistically significant. All statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) software ver. 27.0 (IBM Corp., Armonk, NY, USA).

Survivor definition

Survivors were defined as patients who survived until the last follow-up date (December, 2019). Patients were followed for a minimum of 3 years to ensure adequate observation time to allow meaningful survival analysis. And the data collection cutoff was January 2024.

Non-survivors were defined as patients who died during the follow-up period due to any cause. Duration of follow-up was defined as dates between first diagnosis date and last follow-up date or date of death. The mortality data of study participants was verified by linking it with the Statistics Korea mortality data using resident registration numbers.

Categorization

In this study, age stratification was applied to categorize patients into two cohorts: younger than 65 years and 65 years or older. Age stratification was performed following previous studies (10,11). Additionally, we classified patients into three groups: age <65 years, ≥65 to <80 years, ≥80 years. ECOG performance was chosen to discriminate ‘good performance’ (ECOG 0–1) from ‘poor performance’ (ECOG 2–4) (12). BMI categories were determined based on cut-offs suggested by previous Asian studies (13,14): underweight (BMI <20 kg/m²), normal to pre-obese (BMI 20 to <25 kg/m²), and obese (BMI ≥25 kg/m²).

Results

Overall patient analyses

Baseline characteristics of NSCLC patients

The baseline characteristics and survival outcomes of 2,449 patients diagnosed with NSCLC in 2016 were shown in Table 1. The cohort was primarily male (69.7%) and the median age was 69 years. Compared to non-survivors, survivors were younger (median age: survivors 64 years vs. non-survivors 72 years; P<0.001) and had a smaller percentage of ever-smokers (48.3% vs. 67.8% in non-survivors; P<0.001).

BMI was significantly different between the groups (median BMI: survivors 23.9 kg/m² vs. non-survivors 22.4 kg/m²; P<0.001). Symptom presentation was also different between survivors and non-survivors; specifically, 36.5% of survivors were asymptomatic versus 10.8% of non-survivors (P<0.001), and the presence of symptoms like cough (19.7% vs. 37.5%; P<0.001), sputum (12.4% vs. 22.6%; P<0.001), and dyspnea (8.1% vs. 24.9%; P<0.001) was less common in survivors.

Histopathological types of NSCLC showed significant differences between the groups, with a larger percentage of survivors having adenocarcinoma (74.2% vs. 50.5% in non-survivors; P<0.001) and a smaller percentage having squamous cell carcinoma (20.6% vs. 31.2%; P<0.001). Regarding performance status, an ECOG score of 0–1 was more common in survivors (76.5% vs. 58.2% in non-survivors; P<0.001). Pulmonary function test results were superior in survivors, demonstrated by higher mean forced vital capacity (FVC) (survivors 3.2 L vs. non-survivors 3.0 L; P<0.001) and forced expiratory volume in one second (FEV₁) (survivors 2.4 L vs. non-survivors 2.0 L; P<0.001). The diffusing capacity of the lungs for carbon monoxide (DLco) was also higher in survivors (91% predicted vs. 73% predicted in non-survivors; P<0.001). Survivors exhibited a significantly larger proportion of early-stage NSCLC, with 63.4% at stage I and 11.2% at stage II, compared to non-survivors where only 10.7% were stage I and 7.4% were stage II (P<0.001 for both). Stages III and IV NSCLC were more prevalent among non-survivors, with 19.0% at stage III and 60.2% at stage IV, versus survivors at 11.1% and 9.0%, respectively (P<0.001 for both stages).

Regarding initial treatments, survivors showed significantly larger proportions of those receiving surgery only (72.6% of survivors vs. 11.6% of non-survivors; P<0.001) or surgery with perioperative treatment (6.6% of survivors vs. 3.6% of non-survivors; P<0.001). Radiotherapy alone and concurrent chemoradiotherapy were less common among survivors (3.2% and 5.0%, respectively) compared to non-survivors (11.1% and 11.5%; P<0.001 for both).

Baseline characteristics of SCLC patients

The comparative results of baseline characteristics between survivors and non-survivors among 359 patients with SCLC were shown in Table 2. Survivors showed a significantly younger median age of 64 years vs. 71 years in non-survivors (P<0.001). Asymptomatic presentation was more prevalent in survivors (20.0% vs. 7.7% in non-survivors; P=0.03). In terms of pulmonary function, survivors had higher median values for both FVC (3.4 vs. 3.1 L; P=0.03) and FEV1 (2.2 vs. 1.9 L; P=0.004).

Regarding clinical stage of SCLC, a significantly larger proportion of survivors was diagnosed with limited stage (LS) (85.7% of survivors vs. 32.7% of non-survivors; P<0.001). There was no significant difference in initial treatment approaches between the two groups (P=0.06).

Subgroup analyses stratified by age group, ECOG score, and BMI

Comparison between age groups in NSCLC patients

In the cohort of NSCLC patients stratified by age (cutoffs of 65 and 80 years), those in the oldest group had significantly smaller percentages of males (68.1%) and ever-smokers (57.3%) (P<0.001). The median BMI for patients in this age group was 21.6 kg/m², which was significantly lower than that of younger patients (P<0.001). Symptomatic presentation in the oldest cohort showed larger percentages for dyspnea (31.7%, P<0.001) and sputum (23.3%, P<0.001), whereas asymptomatic cases were less prevalent (10.0%, P<0.001) compared to younger age groups. Instances of hemoptysis were also more frequent (7.3%, P=0.02).

Histopathological analysis revealed that the prevalence of adenocarcinoma was significantly lower in the oldest group (40.8%, P<0.001), whereas squamous cell carcinoma was more common (29.6%, P<0.001). Furthermore, regarding performance status, ECOG score of 2–4 was more common in the oldest group (22.8%, P<0.001). Stage IV cancer was most prevalent in the oldest group (≥80 years), found 54.5% of patients in this age group, which was significantly higher than in younger cohorts (P<0.001). Similarly, the distribution of initial treatment varied significantly, with 58.9% of the oldest group receiving best supportive care, contrasting with smaller percentages in younger groups (P<0.001) (Table S1).

Comparison between age groups in SCLC patients

In the patient group aged ≥80 years with SCLC, the median BMI was significantly lower at 21 (P=0.005). Symptomatically, the largest proportion of patients in this age group reported a cough (55.8%, P=0.04) and weight loss (16.3%, P=0.03). Regarding performance status, the oldest age group showed a higher proportion of patients with ECOG score 2–4 compared to the younger age groups (P<0.001).

Pulmonary function test results showed significantly lower median values for FVC at 2.2 L (P<0.001) and FEV₁ at 1.6 L (P<0.001). The DLco was also decreased in the oldest cohort, with a median value of 63 (P=0.04).

Considering the clinical stage, the oldest group had a significantly larger proportion of ES at 72.1% compared to LS at 27.9% (P=0.02) (Table S2).

Comparison between ECOG groups in NSCLC patients

The comparison of NSCLC patients’ baseline characteristics between those with ECOG 0–1 and those with ECOG 2–4 were summarized in Table S3. The better performance group showed a higher median BMI (23.3 kg/m²) and a lower median age (67 years) compared to those with a worse performance status (P<0.001 for both). A significant difference was noted in symptomatic presentation; 23.8% of ECOG 0–1 patients were asymptomatic compared to 7.6% of ECOG 2–4 patients (P<0.001). Histopathologic analysis revealed a larger proportion of adenocarcinoma in the ECOG 0–1 group (64.8% vs. 38.6% in ECOG 2–4; P<0.001). Pulmonary function tests showed that ECOG 0–1 patients had better median values for FVC (3.2 vs. 2.6 L in ECOG 2–4; P<0.001) and FEV₁ (2.2 vs. 1.7 L in ECOG 2–4; P<0.001). The DLco was also higher in the ECOG 0–1 group (84 vs. 66 per in ECOG 2–4; P<0.001).

In terms of clinical stage, the ECOG 2–4 group had a notably larger proportion of stage IV disease (59.2% vs. 38.2% in ECOG 0–1; P<0.001). Initial treatment approaches differed substantially, with ECOG 0–1 patients more often receiving surgery only (38.5% vs. 7.2% in ECOG 2–4; P<0.001) and ECOG 2–4 patients more frequently provided with best supportive care (39.0% vs. 12.5% in ECOG 0–1; P<0.001).

Comparison between ECOG groups in SCLC patients

The comparison of two groups stratified by performance status was summarized in Table S4. Those with an ECOG performance status of 0–1 had a significantly higher median BMI of 23 kg/m² (P=0.02) compared to the ECOG 2–4 group. A marked age difference was also observed (P<0.001). The ECOG 2–4 group showed a larger proportion of ES at 68.8%, compared to 55.2% in the ECOG 0–1 group (P<0.001). The choice of initial treatment differed, with 56.2% of ECOG 0–1 patients receiving chemotherapy compared to 29.2% of ECOG 2–4 patients. Moreover, a significantly larger percentage of ECOG 2–4 patients received best supportive care (43.8% vs. 9.4% in ECOG 0–1; P<0.001).

Comparison between BMI groups in NSCLC patients

The comparison of three groups stratified by BMI was shown in Table S5. Those with a BMI ≥25 kg/m² had a smaller proportion of males (64.9%, P<0.001), lower prevalence of ever-smokers (56.5%, P<0.001) and presented more frequently as asymptomatic (25.8%, P<0.001) compared to those with lower BMI categories. The median age of those with a BMI ≥25 kg/m² was lower (66 years, P<0.001), compared to those of the other BMI groups. Higher BMI was associated with a greater incidence of adenocarcinoma (66.4% in BMI ≥25 kg/m² vs. 45.5% in BMI <20 kg/m², P<0.001) and a lower incidence of squamous cell carcinoma (24.0% in BMI ≥25 kg/m² vs. 36.6% in BMI <20 kg/m², P<0.001). Performance status also varied with BMI, with a larger proportion of patients with BMI ≥25 kg/m² in the 0–1 category (70.9%, P<0.001).

In terms of initial treatment, the higher BMI group was more likely to receive surgical treatment (44.0% surgery only in BMI ≥25 kg/m² vs. 19.2% in BMI <20 kg/m², P<0.001). The median overall survival (OS) was longest in the BMI group of 25 kg/m² or more (39.7 months for BMI ≥25 kg/m² vs. 8.2 months for BMI <20 kg/m², P<0.001).

Comparison between BMI groups in SCLC

The comparison between SCLC groups stratified by BMI was summarized in Table S6. A significant difference in median age was noted among BMI groups (BMI <20 kg/m²: 74 years, BMI 20 to <25 kg/m²: 70 years, BMI ≥25 kg/m²: 69 years; P=0.041). The proportion of asymptomatic patients varied significantly, with the smallest percentage in the underweight group (BMI <20 kg/m²: 3.7%; P=0.048). FEV₁ differed across groups (BMI <20 kg/m²: 1.8 L, BMI 20 to <25 kg/m²: 1.8 L, BMI ≥25 kg/m²: 2.2 L; P=0.002), as did the median OS (BMI <20 kg/m²: 4.3 months, BMI 20 to <25 kg/m²: 8.2 months, BMI ≥25 kg/m²: 11.7 months; P<0.001). However, no significant difference was seen among the groups regarding initial treatment modalities.

Survival analyses

Risk factors for mortality in overall patients with NSCLC

Multivariate Cox analysis showed that older age [hazard ratio (HR) 1.02; 95% confidence interval (CI): 1.01 to 1.03; P<0.001], male sex (HR 2.05; 95% CI: 1.58 to 2.64; P<0.001), lower BMI (HR 0.97; 95% CI: 0.95 to 0.99, P=0.02), squamous cell carcinoma histopathology compared to adenocarcinoma (HR 1.29; 95% CI: 1.05 to 1.57; P=0.01), poor performance status (HR 1.64, 95% CI: 1.25 to 2.15; P<0.001), lower FVC (HR 0.83, 95% CI: 0.73 to 0.95, P=0.007) or DLco (HR 0.99, 95% CI: 0.98 to 0.99, P=0.001), higher clinical stage (HR 4.23, 95% CI: 3.13 to 5.73, P<0.001, stage IV compared to stage I), and non-surgical treatment (HR 1.69; 95% CI: 1.31 to 2.18, P<0.001) or best supportive care (HR 3.48; 95% CI: 2.52 to 4.79, P<0.001) compared to surgery were significant prognostic factors for mortality in NSCLC patients (Table 3).

Risk factors for mortality in overall patients with SCLC

Multivariate Cox analysis showed that older age (HR 1.03; 95% CI: 1.01 to 1.04; P=0.001), lower BMI (HR 0.94; 95% CI: 0.89 to 0.98; P=0.007), poor performance status (HR 1.89; 95% CI: 1.27 to 2.81, P=0.002), higher clinical stage (HR 2.71; 95% CI: 2.02 to 3.64, P<0.001), and best supportive care (HR 2.95; 95% CI: 1.92 to 4.54, P<0.001, compared to anti-cancer treatment) were significant prognostic factors for mortality in SCLC (Table 4).

Risk factors for mortality in NSCLC patients with old age (≥65 years)

Multivariate Cox analysis showed that male sex (HR 2.12; 95% CI: 1.63 to 2.97; P<0.001), lower BMI (HR 0.96, 95% CI: 0.93 to 0.99; P=0.02), poor performance status (HR 1.90; 95% CI: 1.42 to 2.53; P<0.001), lower FVC (HR 0.77; 95% CI: 0.65 to 0.90; P=0.001) or DLco (HR 0.99; 95% CI: 0.98 to 0.99, P<0.001), higher clinical stage (HR 3.69; 95% CI: 2.69 to 5.06; P<0.001, stage IV compared to stage I), and non-surgical treatment (HR 1.63; 95% CI: 1.22 to 2.17; P=0.001) or best supportive care (HR 3.55; 95% CI: 2.55 to 4.93; P<0.001) compared to surgery were significant predictive factors for mortality in older NSCLC patients (Table 5).

Risk factors for mortality in SCLC patients with old age (≥65 years)

Multivariate Cox analysis showed that lower BMI (HR 0.91; 95% CI: 0.86 to 0.97; P=0.002), poor performance status (HR 1.97; 95% CI: 1.24 to 3.14; P=0.004), higher clinical stage (HR 2.93; 95% CI: 2.07 to 4.17; P<0.001), and best supportive care (HR 3.31; 95% CI: 1.97 to 5.58; P<0.001, compared to anti-cancer treatment) were significant predictive factors for mortality in older SCLC patients (Table S7).

Risk factors for mortality in NSCLC patients with poor performance status (ECOG 2–4)

According to multivariate Cox analysis, older age (HR 1.05; 95% CI: 1.02 to 1.07, P=0.001), lower DLco (HR 0.99; 95% CI: 0.98 to 1.00, P=0.01), higher clinical stage (HR 5.51; 95% CI: 2.16 to 14.05, P<0.001, stage IV compared to stage I), and best supportive care (HR 4.80; 95% CI: 1.65 to 13.97, P=0.004, compared to surgery) were significant risk factors for mortality in NSCLC patients with poor performance status (Table 6).

Risk factors for mortality in SCLC patients with poor performance status (ECOG 2–4)

According to multivariate Cox analysis, lower BMI (HR 0.85; 95% CI: 0.76 to 0.95; P=0.004) and higher clinical stage (HR 2.96; 95% CI: 1.40 to 6.27; P=0.005) were significant risk factors for mortality in SCLC patients with poor performance status (Table S8).

Risk factors for mortality in NSCLC patients with low BMI (<20 kg/m²)

Multivariate Cox analysis presented older age (HR 1.04; 95% CI: 1.02 to 1.06; P<0.001), male sex (HR 2.33; 95% CI: 1.32 to 4.11; P=0.004), poor performance status (HR 1.87; 95% CI: 1.12 to 3.13; P=0.02), lower DLco (HR 0.99; 95% CI: 0.98 to 1.00; P=0.002), higher clinical stage (HR 5.07; 95% CI: 2.53 to 10.15; P<0.001, stage IV compared to stage I), and best supportive care (HR 3.79; 95% CI: 1.93 to 7.46; P<0.001) as significant prognostic factors for mortality in NSCLC patients with low BMI (Table 7).

Risk factors for mortality in SCLC patients with low BMI (<20 kg/m²)

Multivariate Cox analysis presented poor performance status (HR 6.83; 95% CI: 2.35 to 19.89; P<0.001) and lower FVC (HR 0.19; 95% CI: 0.08 to 0.43; P<0.001) as meaningful prognostic factors for mortality in SCLC patients with low BMI (Table S9).

OS by age, ECOG or BMI stratification in lung cancer patients

The time of OS was significantly shorter for eldest patients than younger groups (Figure 1A). Regarding performance status, the time of OS was significantly shorter for patients with ECOG 2–4 than those with ECOG 0–1 (Figure 1B). By BMI stratification, the time of OS was significantly shorter for patients with lowest BMI than those with higher BMI (Figure 1C).

Figure 1 Kaplan-Meier curves for OS in lung cancer patients according to (A) age stratification, (B) ECOG stratification, (C) BMI stratification. BMI, body mass index; ECOG, Eastern Cooperative Oncology Group; OS, overall survival.

Discussion

In this analysis of a nationwide database, 2,808 patients newly diagnosed with lung cancer in 2016 were studied, focusing on those with compromised health status who exhibited reduced survival compared to other groups. Additionally, the study identified specific subgroups of patients with fragile health conditions who could potentially benefit from anti-cancer treatments.

Older age, male sex, lower BMI, squamous cell carcinoma, poor performance status, lower lung function, higher clinical stage and non-surgical treatment or receiving best supportive care only were significant factors for mortality in NSCLC patients. In previous studies, age and performance status have been recognized as prognostic factors affecting survival in lung cancer patients (15,16). In the elderly patients, stage of disease and serum lactate dehydrogenase (LDH) levels were associated with survival (15). Among advanced NSCLC patients, more than half were older than 65 years. However, older patients tend to be undertreated due to relatively decreased functional status, marrow reserve and drug clearance (4). Older patients are at risk of poor survival outcomes due to both undertreatment and toxicity from standard treatment. According to current guidelines, carboplatin-based chemotherapy is recommended for older NSCLC patients with good performance status (17). For those with poor performance status, single-agent chemotherapy could be a valid treatment option. Over the past 3 decades, the treatment options have extended to molecular target therapy and ICIs in NSCLC patients. EGFR-TKI, such as erlotinib and gefitinib, were demonstrated to be well tolerated with good efficacy in older patients with chemotherapy-naïve advanced NSCLC (18,19). When actionable mutations are detected in older advanced NSCLC patients, targeted therapy should be actively considered. According to survival analysis, patients receiving only supportive care have a 3.5 times higher mortality risk compared to those undergoing surgical treatment, particularly among those aged 65 years and older. This finding was consistent with previous studies. According to Japanese and Italian real-world data, the efficacy and safety of immunotherapy in elderly NSCLC patients were demonstrated (20,21). Therefore, when there are viable treatment options, physicians should weigh the benefits and risks of chemotherapy carefully when treating older patients.

Unlike age or poor performance, BMI is not an absolute parameter for candidacy for active anti-cancer treatment. To date, lower BMI is associated with worse survival outcomes for both NSCLC and SCLC patients (22). The paradoxical benefit of obesity, the “obesity paradox” has been found in cardiovascular and pulmonary diseases. Among lung cancer patients undergoing surgery or chemotherapy, obesity has favorable effects on survival outcomes (23). In the present study, older age, male sex, poor performance status, lower DLco, higher clinical stage and best supportive care only were significantly associated with mortality for NSCLC patients with low BMI (<20 kg/m²). Patients receiving best supportive care only showed an approximately 3.5 times higher rate of mortality compared to those who had a history of undergoing lung surgery.

Recently, several studies have reported about cachexia or sarcopenia in lung cancer patients (24,25). Cancer cachexia might reduce the impact of ICIs in advanced NSCLC patients (24). According to a recent article, sarcopenia is a robust prognostic factor in lung cancer patients because of its association of decreased immunotherapy response and increased mortality (25).

In our analyses, OS was longer in the higher BMI group for both NSCLC and SCLC patients, which diverges from previous findings. Furthermore, baseline BMI was significantly higher in the survivor group compared to the non-survivor group, indicating a possible influence on clinical outcomes, although the extent of its impact remains to be clarified. A previous study showed that underweight (BMI <18.5 kg/m²) or morbidly overweight patients (BMI ≥40 kg/m²) had poorer outcomes compared to those who were merely overweight (BMI 25–29.9 kg/m²) or obese (BMI 30–39.9 kg/m²) (26). This discrepancy could be attributed to the larger portion of Caucasians in the referenced study, as BMI impacts may differ between Caucasian and Asian populations. It should be noted that very high BMI, particularly in the range of morbid obesity, is not associated with favorable outcomes due to the increased risk of various comorbidities and heightened systemic inflammation. While one study outside of Korea have suggested an inverse U-shaped relationship between BMI and clinical outcomes, our Korean data included a relatively small proportion of patients with very high BMI, and within this cohort, higher BMI appeared to be associated with better prognosis (27). Additionally, high BMI has been linked to better outcomes in early-stage NSCLC patients undergoing curative resection and those receiving systemic chemotherapy for advanced stages (28,29). However, recent findings indicate that baseline BMI dose not influence outcomes in NSCLC patients receiving first-line chemoimmunotherapy (7,30). Therefore, it is essential to validate the impact of BMI across treatment modalities while accounting for the heterogeneity of treatment backgrounds.

To date, irrespective of age, patients with poor performance status are more likely to experience treatment-related adverse events from chemotherapy and show relatively poorer outcomes (31). However, more patient data are needed to accurately validate the impact of poor performance, as most clinical trials exclude patients with poor performance status (32). According to National Comprehensive Cancer Network (NCCN) guidelines, performance status is a key factor in determining the appropriate treatment strategy for advanced NSCLC patients. In general, combinatorial treatment such as chemo-immunotherapy is recommended for those with an ECOG performance status 0–1 when applicable. For patients with ECOG score of 2, single-agent treatment is generally recommended, and those with a score of 3–4 should receive best supportive care (33). This approach ensures that treatment intensity is appropriately matched to patient endurance and health status. In the present study, analysis among NSCLC patients with poor performance status (ECOG 2–4) showed that older age, lower DLco, higher clinical stage, and best supportive care only compared to receiving surgery were significant prognostic factors for mortality. Patients with best supportive care only had an approximately 5 times higher mortality risk, compared to patients who took surgery. However, there was no significant differences in mortality between non-surgical treatment and surgery. According to a recent article about immune therapy in vulnerable NSCLC patients, the efficacy of ICIs could differ among patients with poor performance state (34). Because those are heterogeneous group, the reason why leads to poor performance status is different. Usually, chemotherapy in patients with poor performance status should be considered meticulously, weighing risk and benefit. Even in patients treated with palliative pembrolizumab monotherapy, ECOG performance status score of at least 2 is associated with poor prognosis in advanced NSCLC patients (3). However, according to a recent study, among NSCLC patients with poor performance status, survival benefit from immunotherapy was shown in those with high programmed death-ligand 1 (PD-L1) expressing tumors (35). Also, Sculier et al. demonstrated that cisplatin-based chemotherapy could improve clinical outcomes of low performance status lung cancer patients (36). According to our study results, even in patients with poor performance status, a selective clinical approach should be chosen to find those who can potentially benefit from active anti-cancer treatment.

In the present study, the mortality of elderly SCLC patients (≥65 years) was associated with BMI, performance status, clinical stage, and treatment option. This result is consistent with previous studies (37,38). Almuradova et al. suggested that active treatment and nutritional support are important in very elderly (≥75 years) SCLC patients to improve survival outcomes (38). Among elderly SCLC patients, male sex and pulmonary function such as FVC or DLco were not significant factors for mortality, unlike elderly NSCLC patients. The difference in risk factors between NSCLC and SCLC may be attributed to the more aggressive nature of SCLC, which could have masked the impact of baseline risk factors, or to the relatively smaller sample size of the SCLC cohort (39). Furthermore, the discrepancy might be due to higher incidence of SCLC in males and smokers (40).

In the subgroup of SCLC patients with poor performance status (ECOG 2–4), BMI and clinical stage were significant factors associated with mortality. Among NSCLC patients with poor performance status, older age and lower DLco were significant prognostic factors for mortality. Because of higher incidence of SCLC in older patients and smokers, age and DLco was not associated with mortality in SCLC patients with poor performance status. In the real world, among advanced SCLC patients, roughly one third have performance status ECOG 2, and 15% have ECOG 3 or 4 (41).

In SCLC patients, elevated systemic inflammatory responses, particularly increased neutrophil-to-lymphocyte ratio and C-reactive protein (CRP) levels, were significantly associated with reduced muscle mass, suggesting that inflammation-driven sarcopenia my help explain the poorer outcomes observed in low BMI populations (42).

When approaching patients with vulnerable conditions such as poor performance, low BMI, and old age, clinicians should decide whether to pursue anticancer treatment and determine the appropriate level of aggressiveness. These decisions depend on whether anticancer treatment can significantly prolong expected survival compared to supportive care alone. Additionally, anticancer treatment should not unnecessarily deteriorate the patient’s quality of life or cause patient avoidable treatment-related adverse events. Multidisciplinary board discussions should evaluate if patients with vulnerable conditions can tolerate active anticancer treatment and assess their ability to handle the toxicity of radiotherapy or chemotherapy. Clinicians should also be familiar with the toxicities and potential benefits of various treatment modalities, including immunotherapy, targeted therapy, platinum-based chemotherapy, radiotherapy, and combinatorial treatments.

Our study has several limitations. First, its retrospective nature, based in Korea, may introduce biases, although the broad, multi-center recruitment covering about 10% of the nation’s lung cancer cases likely reduced selection bias. One noteworthy point is that, despite histological differences in the prognosis of NSCLC and SCLC, undergoing active cancer treatment was associated with better OS in all subgroups. Although we adjusted for treatment type in our analysis, differences in baseline clinical characteristics among treatment groups, including those who received best supportive care, may still have influenced the results. Especially in SCLC, treatment decisions often reflect patients’ overall condition, which may have influenced some of the associations observed, despite efforts to adjust for treatment differences.

Second, we lacked progression-free survival (PFS) data. Lastly, as detailed data on surgical procedures and perioperative chemotherapy regimens were not available, interpretations regarding treatment-related outcomes should be considered with caution.

In spite of above limitations, this study is meaningful, in which we exploratively analyzed Korean patients with vulnerable conditions. In the present study, we could figure out prognostic factors among patients with older age, lower BMI or poor performance status, which was not dealt in clinical trials. These results will serve as a reference for treating patients with compromised health conditions.

Conclusions

Among patients with vulnerable conditions, such as old age, low BMI, and poor performance status, there is a select group who may benefit from active anti-cancer treatment.

Acknowledgments

We acknowledge the support of Korean Association for Lung Cancer, Korea Central Cancer Registry.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-423/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-423/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-423/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-423/coif). The authors have no conflicts of interest to declare.

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 Review Board at the Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea (No. UC23ZISE0213) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Tomita M, Ayabe T, Nakamura K. Low Body Mass Index Is an Independent Predictive Factor after Surgical Resection in Patients with Non-Small Cell Lung Cancer. Asian Pac J Cancer Prev 2017;18:3353-6. [Crossref] [PubMed]
2. Husain ZA, Kim AW, Yu JB, et al. Defining the High-Risk Population for Mortality After Resection of Early Stage NSCLC. Clin Lung Cancer 2015;16:e183-7. [Crossref] [PubMed]
3. Sehgal K, Gill RR, Widick P, et al. Association of Performance Status With Survival in Patients With Advanced Non-Small Cell Lung Cancer Treated With Pembrolizumab Monotherapy. JAMA Netw Open 2021;4:e2037120. [Crossref] [PubMed]
4. Gridelli C, Langer C, Maione P, et al. Lung cancer in the elderly. J Clin Oncol 2007;25:1898-907. [Crossref] [PubMed]
5. Carmichael JA, Wing-San Mak D, O'Brien M. A Review of Recent Advances in the Treatment of Elderly and Poor Performance NSCLC. Cancers (Basel) 2018;10:236. [Crossref] [PubMed]
6. Mollica V, Rizzo A, Marchetti A, et al. The impact of ECOG performance status on efficacy of immunotherapy and immune-based combinations in cancer patients: the MOUSEION-06 study. Clin Exp Med 2023;23:5039-49. [Crossref] [PubMed]
7. Cortellini A, Ricciuti B, Vaz VR, et al. Prognostic effect of body mass index in patients with advanced NSCLC treated with chemoimmunotherapy combinations. J Immunother Cancer 2022;10:e004374. [Crossref] [PubMed]
8. Kim YC, Won YJ. The Development of the Korean Lung Cancer Registry (KALC-R). Tuberc Respir Dis (Seoul) 2019;82:91-3. [Crossref] [PubMed]
9. Lim JU, Han S, Kim HC, et al. Characteristics of female lung cancer in Korea: analysis of Korean National Lung Cancer Registry. J Thorac Dis 2020;12:4612-22. [Crossref] [PubMed]
10. Herbst RS, Baas P, Kim DW, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet 2016;387:1540-50. [Crossref] [PubMed]
11. Brahmer J, Reckamp KL, Baas P, et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer. N Engl J Med 2015;373:123-35. [Crossref] [PubMed]
12. Meyers DE, Pasternak M, Dolter S, et al. Impact of Performance Status on Survival Outcomes and Health Care Utilization in Patients With Advanced NSCLC Treated With Immune Checkpoint Inhibitors. JTO Clin Res Rep 2023;4:100482. [Crossref] [PubMed]
13. Yang L, Yang G, Zhou M, et al. Body mass index and mortality from lung cancer in smokers and nonsmokers: a nationally representative prospective study of 220,000 men in China. Int J Cancer 2009;125:2136-43. [Crossref] [PubMed]
14. Koh WP, Yuan JM, Wang R, et al. Body mass index and smoking-related lung cancer risk in the Singapore Chinese Health Study. Br J Cancer 2010;102:610-4. [Crossref] [PubMed]
15. Tas F, Ciftci R, Kilic L, et al. Age is a prognostic factor affecting survival in lung cancer patients. Oncol Lett 2013;6:1507-13. [Crossref] [PubMed]
16. Kawaguchi T, Takada M, Kubo A, et al. Performance status and smoking status are independent favorable prognostic factors for survival in non-small cell lung cancer: a comprehensive analysis of 26,957 patients with NSCLC. J Thorac Oncol 2010;5:620-30. [Crossref] [PubMed]
17. Pallis AG, Gridelli C, Wedding U, et al. Management of elderly patients with NSCLC; updated expert's opinion paper: EORTC Elderly Task Force, Lung Cancer Group and International Society for Geriatric Oncology. Ann Oncol 2014;25:1270-83. [Crossref] [PubMed]
18. Jackman DM, Yeap BY, Lindeman NI, et al. Phase II clinical trial of chemotherapy-naive patients > or = 70 years of age treated with erlotinib for advanced non-small-cell lung cancer. J Clin Oncol 2007;25:760-6. [Crossref] [PubMed]
19. Crinò L, Cappuzzo F, Zatloukal P, et al. Gefitinib versus vinorelbine in chemotherapy-naive elderly patients with advanced non-small-cell lung cancer (INVITE): a randomized, phase II study. J Clin Oncol 2008;26:4253-60. [Crossref] [PubMed]
20. Morinaga D, Asahina H, Ito S, et al. Real-world data on the efficacy and safety of immune-checkpoint inhibitors in elderly patients with non-small cell lung cancer. Cancer Med 2023;12:11525-41. [Crossref] [PubMed]
21. Luciani A, Marra A, Toschi L, et al. Efficacy and Safety of Anti-PD-1 Immunotherapy in Patients Aged ≥ 75 Years With Non-small-cell Lung Cancer (NSCLC): An Italian, Multicenter, Retrospective Study. Clin Lung Cancer 2020;21:e567-71. [Crossref] [PubMed]
22. Evcil FY, Önal Ö, Özkan EE. The Effect of Body Mass Index on Survival in Lung Cancer. Nutr Cancer 2023;75:857-66. [Crossref] [PubMed]
23. Zhang X, Liu Y, Shao H, et al. Obesity Paradox in Lung Cancer Prognosis: Evolving Biological Insights and Clinical Implications. J Thorac Oncol 2017;12:1478-88. [Crossref] [PubMed]
24. Miyawaki T, Naito T, Kodama A, et al. Desensitizing Effect of Cancer Cachexia on Immune Checkpoint Inhibitors in Patients With Advanced NSCLC. JTO Clin Res Rep 2020;1:100020. [Crossref] [PubMed]
25. Lin TY, Chen YF, Wu WT, et al. Impact of sarcopenia on the prognosis and treatment of lung cancer: an umbrella review. Discov Oncol 2022;13:115. [Crossref] [PubMed]
26. Shepshelovich D, Xu W, Lu L, et al. Body Mass Index (BMI), BMI Change, and Overall Survival in Patients With SCLC and NSCLC: A Pooled Analysis of the International Lung Cancer Consortium. J Thorac Oncol 2019;14:1594-607. [Crossref] [PubMed]
27. McNeill JN, Lau ES, Zern EK, et al. Association of obesity-related inflammatory pathways with lung function and exercise capacity. Respir Med 2021;183:106434. [Crossref] [PubMed]
28. Sepesi B, Gold KA, Correa AM, et al. The Influence of Body Mass Index on Overall Survival Following Surgical Resection of Non-Small Cell Lung Cancer. J Thorac Oncol 2017;12:1280-7. [Crossref] [PubMed]
29. Dahlberg SE, Schiller JH, Bonomi PB, et al. Body mass index and its association with clinical outcomes for advanced non-small-cell lung cancer patients enrolled on Eastern Cooperative Oncology Group clinical trials. J Thorac Oncol 2013;8:1121-7. [Crossref] [PubMed]
30. Li LX, Socinski MA, Kichenadasse G, et al. A lack of association between BMI and chemoimmunotherapy efficacy in advanced non-small cell lung cancer: Secondary analysis of the IMpower150 and IMpower130 clinical trials. BMC Cancer 2024;24:379. [Crossref] [PubMed]
31. Pfister DG, Johnson DH, Azzoli CG, et al. American Society of Clinical Oncology treatment of unresectable non-small-cell lung cancer guideline: update 2003. J Clin Oncol 2004;22:330-53. [Crossref] [PubMed]
32. Araujo LH. MS18.01 Treatment of Patients with Poor Performance Status (ECOG 3-4). Journal of Thoracic Oncology 2018;13:S278-S279.
33. Mo L, Urbauer DL, Bruera E, et al. Recommendations for supportive care and best supportive care in NCCN clinical practice guidelines for treatment of cancer: Differences between solid tumor and hematologic malignancy guidelines. Support Care Cancer 2021;29:7385-92. [Crossref] [PubMed]
34. Morimoto K, Yamada T, Takayama K. The landscape of immune therapy in vulnerable patients with advanced non-small cell lung cancer: a narrative review. Transl Lung Cancer Res 2023;12:2310-21. [Crossref] [PubMed]
35. Veluswamy R, Hu L, Smith C, et al. Immunotherapy Outcomes in Individuals With Non-Small Cell Lung Cancer and Poor Performance Status. JNCI Cancer Spectr 2022;6:pkac013. [Crossref] [PubMed]
36. Sculier JP, Lafitte JJ, Paesmans M, et al. Chemotherapy improves low performance status lung cancer patients. Eur Respir J 2007;30:1186-92. [Crossref] [PubMed]
37. Schild SE, Zhao L, Wampfler JA, et al. Small-cell Lung Cancer in Very Elderly (≥ 80 Years) Patients. Clin Lung Cancer 2019;20:313-21. [Crossref] [PubMed]
38. Almuradova E, Menekse S. Survival outcomes and prognostic nutritional index in very elderly small-cell lung cancer patients: importance of active treatment and nutritional support. Aging Male 2023;26:2251573. [Crossref] [PubMed]
39. Wang WZ, Shulman A, Amann JM, et al. Small cell lung cancer: Subtypes and therapeutic implications. Semin Cancer Biol 2022;86:543-54. [Crossref] [PubMed]
40. Tseng JS, Chiang CJ, Chen KC, et al. Association of Smoking With Patient Characteristics and Outcomes in Small Cell Lung Carcinoma, 2011-2018. JAMA Netw Open 2022;5:e224830. [Crossref] [PubMed]
41. Friedlaender A, Liu SV, Passaro A, et al. The Role of Performance Status in Small-Cell Lung Cancer in the Era of Immune Checkpoint Inhibitors. Clin Lung Cancer 2020;21:e539-43. [Crossref] [PubMed]
42. Kim EY, Kim YS, Seo JY, et al. The Relationship between Sarcopenia and Systemic Inflammatory Response for Cancer Cachexia in Small Cell Lung Cancer. PLoS One 2016;11:e0161125. [Crossref] [PubMed]