Survival Rates and Predictors of Mortality in Lung Cancer: A Multi-Centre Study in Kerala

Abstract

Background:

Lung cancer is a major health problem in India and accounts for 5.9% of all cancers and 8.1% of all cancer-related deaths. Survival analysis studies are scarce in India as they require long-term follow-up and a good database. Therefore, the present study was conducted to understand survival rates and factors associated with lung cancer mortality in India.

Methods:

It was a hospital-based registry, wherein six hospitals were selected from three zones – north, central, and south zones of Kerala. Patients of pathologically proven primary lung cancer (ICD-11 code C 33 and C 36) were recruited. All patients were followed up for 2 years from the date of diagnosis.

Results:

A total of 761 patients were registered from six tertiary care hospitals of Kerala who were diagnosed with primary lung cancer during the period 2017–2019. The median survival of the study population was 8.6 months (IQR 2.9–21.6). The cumulative mortality rates at the end of 6 months, 1 year, and 2 years were 39.9%, 57.8%, and 70.2%, respectively. The overall mortality rate was 6.38 (CI 3.03–12.97) per 100 person months. In adjusted Cox-proportional hazard model, participants with lymph node status of N2 (HR = 4.9, 95% CI 1.0–23.6), N3 (HR = 5.9, 95% CI 0.53–66.7), and NX (HR = 31.7, 95% CI 2.8–354.7) had higher mortality risk compared to those with N1 status.

Conclusion:

This study includes significant implications for policy in cancer diagnosis and first health system contact for treatment. Findings are crucial to effectively stratify risk in lung cancer beyond smoking history, comprehensive identification, and assessment of potential predictors of mortality.

INTRODUCTION

Noncommunicable diseases (NCDs), alternatively termed chronic conditions, often persist over extended periods and stem from a blend of genetic, physiological, environmental, and behavioral influences. Predominant NCD categories encompass cardiovascular issues (like infarction to myocardium and strokes), cancer, chronic lung-related ailments (such as chronic obstructive pulmonary disease and asthma), and diabetes.[1] Significant shifts occurred in the global health landscape in the past 3 decades, driven by economic growth, population growth, aging demographics, increased longevity, unhealthy lifestyle choices, and environmental pollution.[2] Epidemiological data indicate that NCDs have emerged as the primary causes of death and disability-adjusted life years (DALYs) on a global scale.[3] Approximately 41 million deaths worldwide equivalent to nearly three out of every four deaths can be attributed to NCDs.[4] Although NCD mortality rates are on the decline in high-income nations, the burden in LMICs is escalating due to the epidemiological transition, with these countries now bearing 85% of NCD-related deaths.[5,6] Cancers are a major contributor to disease burden, and projections forecast that the global burden will continue to grow for at least the next 2 decades. Cancer continues to be a prominent contributor to global mortality, accounting for around 10 million reported deaths in 2020. Lung cancer is a worldwide health problem and is now reported as the most frequently diagnosed cancer. In 2019, lung cancer was not only the most diagnosed cancer worldwide but also the leading cause of cancer-related deaths. In India, lung cancer accounts for 5.9% of all cancers and 8.1% of all cancer-related deaths.

In India, the estimated number of cancer cases for 2022 was 1,461,427. The crude incidence rate of cancer in India was 100.4 per 100,000 populations. There were more cases among females, with 749,251 cases (105.4 per 100,000 women), compared to males, with 712,176 cases (95.6 per 1 lakh men). The assessed age-adjusted rate (AAR) for all locations of cancer in India was 107.0 per 1 lakh population.[7] Lung cancer stands out as a leading cause of mortality in India, marked by a challenging prognosis. According to Globocan, estimation of lung cancer in India indicates that the incidence of lung cancer in India is 70,275 (for all ages and both genders) with an age standardized incidence rate being 6.9 per 100,000 of our population.[8] Despite its significant impact, survival analysis studies on lung cancer remain sparse within the country due to the demanding nature of long-term follow-ups and the inadequacy of robust databases. There is a steady increase in the incidence of cancer in Kerala over the past decade with a rise in both crude rate and AAR. The AAR increased from 121.7 per 100,000 men to 137.8 and among women 108.3 to 127.3 in Thiruvananthapuram from 2006–2008 to 2012–2016 period.[9] Only a few studies investigated survival predictors of lung cancer among the Indian population. This study provides a better understanding of survival rates, thereby enhancing the assessment of current treatment protocols. The objective of the study is to assess the survival rates and median survival time among lung cancer patients in Kerala, India, and to identify the predictors of mortality outcomes among lung cancer patients in Kerala.

MATERIALS AND METHODOLOGY

The study was conducted in tertiary cancer care hospitals in Kerala. Six hospitals were selected from Kerala’s north, central, and south zones. A registry of lung cancer patients was established in these hospitals. Consecutive primary lung cancer subjects diagnosed histologically (ICD code C 33 and C 36) from January 2017 to December 2019 were included in the study. Patients with metastatic lung disease (primary in another organ) were excluded using a screening tool. The study design was a multicenter lung cancer registry with follow-up for 2 years. Data for 2 years (2017–2019) were obtained from patient records. All patients were followed up further for a minimum period of 2 years from the date of diagnosis.

Sample size was estimated using STATA 13. The sample size was computed for Cox PH regression Wald test for detecting a minimum hazard ratio of 1.3. The probability of event was 0.60 for all-cause mortality among lung cancer patients, with an alpha (two-sided) of 0.05 and a standard deviation of covariate under consideration of 0.50. The sample size and required number of events were estimated for 80% power. The required sample size was 761. A chart review was conducted to collect the data. The file number of patients with lung cancer was taken from the hospital cancer registry and handed over to the medical records department of the hospital for retrieving the file. The individual patient file was taken from medical records, and data were collected using a structured data collection tool. There were four parts of data collection tool. Part I of data collection tool was filled out initially, and subsequent forms were filled out if the patient was eligible for the study. Histological and lab data, available in chart, were collected. Data regarding sociodemography, presenting complaints, investigations, past medical history, ECOG performance status at diagnosis, date and mode of diagnosis, treatment modalities, and treatment outcome were gathered from the subject chart. The last hospital visit date was obtained from the patient chart. Part IV of the data collection tool was filled by contacting the patient or their caregiver. The patient/caregiver was contacted telephonically to assess the vital status at the time of data collection and every 6 months till 2 years of diagnosis in the absence of event of interest (all-cause mortality). If the patient/caregiver was not accessible by phone, the data collector tried to access the patient through Primary Health Centre/Anganwadi Worker/Accredited Social Health Activist (ASHSA) of the respective areas using available address. Three attempts were made to collect relevant follow-up data from each patient or their family members.

After obtaining written consent from the institution head and treating doctor, data were retrieved from patient files of eligible patients. On behalf of the treating doctor, one of their team members contacted the patient or their relative and sought their verbal consent for a telephonic interview. A structured data extraction format was used to collect data from the files. The patient/caregiver was contacted to assess the patient’s vital status. Institution Ethical Clearance was obtained from all six study sites and SCTIMST (SCT/IEC/1658/DECEMBER-2020), and the study was registered with Clinical Trial Registry of India (CTRI/2021/02/031/031299).

The data were inputted into an Excel spreadsheet, and analysis was conducted using STATA 13. Data for continuous measurements were reported as mean and standard deviation, whereas results for categorical measurements were provided as numbers and percentages. Kaplan–Meier survival curves were generated, and log rank test was employed to compare overall survival among study groups. A multivariable Cox proportional hazard model was employed to evaluate factors that predict all-cause death. The hazard ratios and their corresponding 95% confidence intervals were derived from the Cox-proportional hazard model.

RESULTS

761 patients were enrolled in the study. The proportion of study participants who lost to follow-up was a little more than 8%. The mean age was around 65 years, with most patients in the age group between 55 and 75 years [Table 1]. There were 144 (18.9%) female study participants and 617 (81.1%) male study participants [Figure 1]. Among them, 749 (98.4%) were currently married, and 12 (1.6%) were never married. Among the study participants, 292 (38.4%) were Hindu, 260 (34.2%) were Christian, and 209 (27.5%) were Muslim [Table 1]. Among the study population, 429 (56.4%) had adenocarcinoma, and 196 (25.8%) had squamous cell carcinoma (SCC). Additionally, 71 (9.3%) patients were diagnosed with undifferentiated, 56 (7.4%) with small cell carcinoma, and 9 (1.2%) with large cell carcinoma. Among the participants, 571 (75.0%) were diagnosed with stage IV disease. Stage III, stage II, and stage I were diagnosed in 76 (9.9%), 72 (9.5%), and 42 (5.5%) participants, respectively. The T, N, M status of participants is mentioned in Table 2. Based on the T N M status, 280 (36.8%), 316 (41.5%), and 326 (40.8%) participants were T2, N2, and Mc stage, respectively. Among the participants, 219 (28.8%) were current smokers, and 202 (26.5%) were past smokers. The mean duration of smoking was 25.32 (±10.59), ranging from 2 to 60 years. However, 26.9% of participants reported consumption of alcohol.

Table 1.

Age group with TNM staging and mortality rate among the study participants

Factors	Total (n=761)	%
Age group
60-69 years	258	33.9
70-79 years’	235	30.9
<60 years’	226	29.7
≥80 years	42	5.5
Tumour stages
T1	101	13.3
T2	280	36.8
T3	233	30.6
T4	147	19.3
Node status
Nx	36	4.7
N1	93	12.3
N2	316	41.5
N3	316	41.5
Metastasis
M0	43	5.7
M1a	202	26.5
M1b	326	42.8
M1c	43	5.7
Mortality
At 6 months	304	39.95
At 1 year	440	57.82
At 2 years	572	75.16

Mean age: 65.11 (±10.22), ranging from 14 to 93 years

Figure 1.

Gender and survival probability

Table 2.

Sociodemographic characteristics with Cox-proportional hazard model of mortality in lung cancer

Variables	n (%)	Unadjusted hazard ratio (95% CI)	P	Adjusted hazard ratio (95% CI)	P
Sex
Female	144 (18.9)	1 (-)	-	1 (-)	-
Male	617 (81.1)	1.32 (1.06-1.65)	0.011	1.12 (0.86-1.46)	0.39
Religion
Christian	260 (34.1)	1 (-)	-	1 (-)	-
Hindu	292 (38.3)	0.91 (0.15-5.61)	-	1.25 (-)	--
Muslim	209 (27.4)	0.92 (0.15-5.20)	0.62	1 (-)
Consumption of alcohol
No	465 (69.4)	1 (-)		1 (-)	-
Yes	205 (30.6)	1.45 (1.20-1.75)	<0.001	1.25 (0.89-1.75)	0.19
Smoking history
Nonsmoker	340 (44.7)	1 (-)	-	1 (-)	-
Past smoker	202 (26.5)	1.32 (1.06-1.59)	0.010	1.04 (0.82-1.31)	0.77
Current smoker	219 (28.8)	1.54 (1.27-1.87)	0.001	1.03 (0.79-1.34)	0.84
No of symptoms	2.32 (0.9)	1.14 (1.05-1.25)	0.003	1.10 (-)	-
BMI	21.3 (3.4)	0.91 (0.89-0.95)	<0.001	-(1.29)	-
Number of metastatic sites	0.97 (0.8)	1.85 (1.69-2.02)	0.001	1.29 (1)	-
Vessel invasion
Absent	405 (53.2)	1 (-)	-	1 (-)	-
Present	355 (46.6)	2.29 (1.93-2.71)	<0.001	1.29 (1.07-1.55)	0.30
Pleural involvement
Absent	213 (27.9)	1 (-)		1 (-)	0.003
Present	548 (72.0)	2.49 (2.02-3.01)	<0.001	1.19 (0.95-1.51)	0.001

CI- CI-Confidence Interval; BMI-Body Mass Index

Nearly half (n = 376, 49.4%) of the study population underwent chemotherapy, and out of that, 191 (25.1%) and 183 (24.0%) had definitive and palliative chemotherapy, respectively. In total, 52 (6.8%) patients underwent surgical treatment (36 lobectomy, 4 bilobectomy, 2 pneumonectomy, 8 sleeve resection, 2 wedge resection). In total, 171 (22.5%) patients underwent radiation therapy. Most of them (n = 96, 12.6%) reported palliative therapy, with three patients reported for definitive therapy. The findings may highlight the importance of integrating palliative care approaches into the management package to optimize symptom control and quality of life.

The mortality rate among the study participants at the end of 1 year was high, with 440 (57.82%) as compared to the second year, 304 (39.95%), and six months, 172 (75.16%) [Table 1]. The all-cause mortality rate per 100 person-months was 6.38, with a maximum at stage IV contributing 10.01 events per 100 person-months, whereas in stage I disease, the all-cause mortality rate was only 0.7 per 100 person-months [Table 1]. The cumulative mortality events at 2 years were 572 (75.1%). The median survival time was 8.57 (±0.61) months, ranging from 7.38 to 9.75 months. The overall survival was better for women than for men with a median survival of 359 days in women, whereas males had 225 days [Figure 1]. Overall survival was the lowest in participants with an ECOG score of three [Figure 2] compared to ECOG-Eastern Co-operative Oncology Group (ECOG) scores 1 and 2 (log-rank P < 0.001). As the size of the tumor increased from status I to IV [Figure 3], the survival probability decreased (log-rank P < 0.001). Participants without metastasis had better survival [Figure 4] than participants with metastasis (log-rank P = 0.01). Current smokers had worse survival [Figure 5] compared to past smokers and nonsmokers (log-rank P < 0.001).

Figure 2.

ECOG score and survival probability

Figure 3.

Tumor stage and survival probability

Figure 4.

Metastasis and survival probability

Figure 5.

Smoking history and survival probability (n = 678)

Males showed higher mortality risk with an unadjusted HR of 1.32 (P = 0.01) compared to females [Table 2]. However, in the multivariable Cox-PH model, this association was statistically nonsignificant after adjustment for other variables (Adjusted HR = 1.12, P = 0.39). Current smokers exhibited an increased risk of mortality compared to nonsmokers with an HR of 1.54 (P = 0.001), which remains nonsignificant after adjustment for other variables (Adjusted HR = 1.03, P = 0.84). Past smokers showed an elevated risk for mortality compared to nonsmokers, with an HR of 1.3 (P = 0.01). However, this association remained nonsignificant statistically after adjustment for other variables (Adjusted HR = 1.04, P = 0.77) [Table 2]. The mortality risk was lower in large cell carcinoma with an HR of 0.3 compared to adenocarcinoma (P = 0.03), which remained nonsignificant after adjustment for other variables (Adjusted HR = 0.7, P = 0.54). The mortality risk was, however, higher in small cell carcinoma with an HR of 1.57 (P = 0.004). After adjustment, this association was statistically nonsignificant (Adjusted HR = 1.24, P = 0.18). SCC and undifferentiated tumors showed no difference in mortality compared to adenocarcinoma (Adjusted HR ranging from 0.7-0.54, P = 0.54) [Table 3].

Table 3.

Multivariable Cox-proportional hazard model of mortality in lung cancer

Variables	n (%)	Unadjusted hazard ratio (95% CI)	P	Adjusted hazard ratio (95% CI)	P
Lymph node status
Nx	36 (4.7)	1 (-)	-	1 (-)	-
N1	93 (12.2)	1.95 (0.91-4.19)	-	1.51 (0.69-3.25)	0.30
N2	316 (41.5)	6.94 (3.43-14.05)	<0.001	3.05 (2.16-9.37)	0.003
N3	316 (41.5)	11.92 (5.89-24.13)		4.52 (2.16-9.37)	0.001
ECOG PS	1.77 (0.7)	3.51 (3.09-3.97)	<0.001	2.16 (1.74-2.68)	0.002
Tumor size in cm	5.86 (14.8)	1.01 (1.01-1.02)	<0.001	1.07 (1.01-1.12)	0.02
Histological type
Adenoca	429 (56.3)	1 (-)	-	1	-
Large cell ca	9 (1.1)	0.31 (0.10-0.93)	-	0.71 (0.22-2.24)	0.54
Small cell ca	56 (7.3)	1.57 (1.16-2.13)	0.003	1.24 (0.91-1.71)	0.18
Squamous cell ca	196 (25.7)	1.06 (0.87-1.29)	-	1.12 (0.91-1.37)	0.27
Undifferentiated	71 (9.3)	1.31 (1.0-1.73)	-	1.14 (0.86-1.52)	0.35
TNM stage
Stage I	42 (5.5)	1 (-)	-	1 (-)	-
Stage II	72 (9.5)	0.82 (0.23-2.95)	-		-
Stage III	76 (10.0)	0.41 (0.09-1.88)	<0.001	-	-
Stage IV	571 (75.0)	0.88 (0.25-3.12)	-	-	-

ECOG PS-Eastern Cooperative Oncology Group Performance Status

T2, T3, and T4 stages were linked with an increased risk for all-cause mortality compared to T1, with HRs ranging from 1.49 to 3.41 (P < 0.01). The N2 and N3 stages were also linked with a greater risk for all-cause mortality compared to Nx, with HRs ranging from 6.94 to 11.92 (P < 0.01) [Table 3]. Patients with metastasis were at a relatively increased risk for all-cause mortality compared to patients without metastasis (HR of 2.44, P = 0.001). However, this association became nonsignificant after adjustment for other variables (Adjusted HR = 1.19, P = 0.13). Tumor size (the tumor size increases by 1 cm, the hazard of mortality increases by 1%) and the number of metastatic sites were associated with a greater risk for all-cause mortality (P < 0.001).

In the multivariable Cox PH model, after adjustment for all other variables, a number of metastatic sites, vessel invasion, lymph node status, ECOG PS, and tumor status were associated with all-cause mortality. With an increasing number of metastatic sites, all-cause mortality was increased by 29% (HR = 1.29, 95% CI 1.15–1.45, P = 0.001), and if vessel invasion by the tumor was present, all-cause mortality was increased by 29% (HR = 1.29, 95% CI 1.07–1.55, P = 0.007). With increasing numbers of lymph node involvement, all-cause mortality also increased drastically (HR = 1.51–4.52, 95% CI 1.47–2.68, P = 0.001). With a unit increase in ECOG performance status score, all-cause mortality increased two times (HR = 2.16, 95% CI 1.74–2.68, P = 0.002) [Table 3]. Each centimeter increase in tumor size was associated with 7% increase in all-cause mortality (HR = 1.07, 95% CI 1.01–1.12, P = 0.02).

DISCUSSION

The study’s main aim is to assess the survival rates and the predictor variables of mortality outcomes among lung cancer patients in Kerala. We enrolled 761 patients with primary lung cancer in the registry. The proportion of study participants who lost to follow-up was a little more than 8%. The mean age was around 65 years, with most patients in the age group between 55 and 75 years. Although we observed male preponderance, one in five participants was female. The mean age of lung cancer in India is substantially lower than that of high-income countries. However, over the past 2–3 decades, there has been an increase in the mean age of diagnosed lung cancer patients in India.[10] Our findings concur with more recent findings from India, where the mean age at diagnosis was 65 years. This increase in mean age may be attributed to a better quality of life and longevity among the Indian population. In Kashmir, the majority of cases (92%) were male, while only 8% were female.[11] In Uttarakhand, research conducted over a 10-year period in a tertiary medical center revealed a mean age of 59 years, with a preponderance of males (83%),[12] which is similar to our study. It is observed that the median age at diagnosis has increased, showing a population getting the disease at a later age, and when compared to older studies, the incidence of disease among females is increasing, possibly owing to other risk factors of cancer other than smoking.[13]

In terms of histological type, adenocarcinoma was the most common pathologic type among males and females, followed by squamous cell and small-cell carcinoma. In a study done among hospitalized patients from Kashmir,[11] the most prevalent histological type of tumor in both genders was Smoker’s lung cancer (SCC) followed by adenocarcinoma. Among smokers, the predominant histological subtypes of lung cancer were SCC and small cell carcinoma. It is observed that prevalence of SCC has been reduced and other variants are increasing, may be because of other risk factors of lung cancer. A study based on the National Cancer Registry Programme revealed that adenocarcinoma was the most common histological type of lung cancer, comprising 34% of cases in males.[14] In females, adenocarcinoma constituted over half of lung cancers, emerging as the predominant histological type, while SCC accounted for 11% of cases,[15] which is similar to our study findings. Histological subtype distribution, with adenocarcinoma and squamous cell carcinoma being the most prevalent, highlights the heterogeneity of lung cancer and the necessity of personalized treatment strategies based on tumor biology.

In our study, more than two-thirds of patients had stage IV disease. Tumor stages of T2 and T3 were less than one third among them. Around half of them had lymph node involvement of N2, and metastasis was present in more than 85% of subjects, with common sites being the liver, brain, and adrenal glands. These data revealed that for most subjects, around 75% were detected at later stages of the disease (Stage III-B and IV), which is supported by a similar study conducted in Delhi and showed Uttarakhand.[16] In India, lung cancer is diagnosed at an advanced stage due to the absence of screening and late presentation of the disease.[17] Screening for lung cancer is not part of the National Program for Non-Communicable Diseases (NP-NCD), which may contribute to the higher number of cases diagnosed at a late stage. The screening tools used in High-Income Country (HICs) are not suitable for people in Low- and Middle-Income Countries (LMICs) as communicable diseases may mimic lung cancer findings.[18]

The median time of survival among our study population was a little less than 9 months, with 25% dying within 3 months and 60% within 1 year. The survival analysis predicted that presence of bone or brain metastasis, and with squamous or undifferentiated carcinoma, pleural involvement, vessel invasion, along with advanced stage of cancer were predictors of time to mortality. The median survival in advanced-stage lung cancer is still poor, as evident by the study conducted by Murali et al. 2017[19] Strategies such as personalized medicine and use of second-line and maintenance chemotherapy may significantly improve the survival in patients with advanced-stage lung cancer in developing countries. However, in small-cell lung cancer, earlier stage of presentation and younger age were associated with considerably better survival. The substantial proportion of patients with stage IV disease highlights the importance of integrating palliative care approaches into the management package to optimize symptom control and quality of life. The identification of predictors of mortality, including a number of metastatic sites, lymph node involvement, ECOG performance score, vessel invasion, pleural involvement, and tumor size, highlights the importance of comprehensive prognostic assessment in treatment decision-making. As the disease is diagnosed at a later stage, the median survival is low. One important factor for late diagnosis of this disease is late presentation. Symptoms/signs of the disease mostly present after metastasis of the disease. Patients stay asymptomatic at an early stage of disease.

In a study among 151 lung cancer patients, the 2-year survival rate stood at 66%, with 60% experiencing distant metastasis throughout follow-up. The median time of carcinoma-specific survival time was 18 months,[15] which is higher than our study population. It is observed that developed countries have better survival rates due to screening of high-risk populations and early diagnosis, availability of treatment facilities, and better disease management modalities. According to Bogere et al.,[20] in 2022, survival outcomes of lung cancer patients were much lesser than our study population. Survival research outcomes can differ due to a range of factors. These encompass variation in study populations stemming from regional demographics, lifestyle elements, and environmental factors. Discrepancies may also arise from distinctions in study design, diagnostic approaches, healthcare availability, and evolving trends in cancer treatment over time. Furthermore, reporting biases and statistical variations in small sample sizes can affect the findings of survival studies. Therefore, it is important to consider these factors when analyzing and contrasting survival data from different studies.

CONCLUSIONS

This study analyzed demographic and clinical characteristics among lung cancer patients, revealing several noteworthy findings and underscoring this disease’s multifaceted nature. This observation emphasizes the importance of gender-specific considerations in disease management and the need for interventions targeting high-risk populations. The high prevalence of metastatic spread and advanced disease stages at diagnosis emphasizes the challenges in early detection and the urgent need for improved screening modalities; therefore, the findings of the study include significant implications for policy in cancer diagnosis and first health system contact for treatment. Findings are crucial to effectively stratify risk in lung cancer beyond smoking history, comprehensive identification, and assessment of potential predictors of mortality.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.