Introduction

India and many other developing countries that are transitioning towards achieving a status of developed nation are witnessing a change in the epidemiological trend, with the burden of diseases shifting from communicable to non-communicable diseases (NCDs). Among these NCDs, cancer remains a significant and leading cause of death and disability, making it one of the biggest public health problems. According to the World Health Organization’s International Agency for Research on Cancer, India reported 1,413,316 new cancer cases in 2022, a figure projected to rise by 73.8% to approximately 2,456,478 by 2045. Cancer-related deaths were estimated at 916,827 in 2022 and are expected to increase by 80.3% to 1,657,519 by 2045.[1] Advancing age is one of the most important risk factors for cancer.[2] The rising burden of cancer is driven by demographic and epidemiological changes, particularly rapid growth in the geriatric population.[3] Mortality patterns and prognosis also vary with cancer type and the age of affected individuals.[4] This makes population aging as one of the prime reasons for increasing disease burden; various studies show that the geriatric group and older adults are at higher risk of developing cancer, developing disability due to cancer, and dying due to cancer. Also older cancer patients have poor prognoses because of existing comorbidities, higher treatment dropout rates, and poor response to treatment.[5] The geriatric population is increasing at high rates, and out of this, a large number of older people now live in LMICs and developing nations. WHO estimates that by 2050, 80% of geriatric population will live in LMICs. Between 2015 and 2050, the proportion of the world's population over 60 years will nearly double from 12% to 22.8%.[6] The United Nations (UN) Sustainable Development Goals (SDGs) also mention the need for reducing cancer burden as part of target 3.4, stating, “By 2030, reduce by one third premature mortality from non-communicable diseases [NCDs] through prevention and treatment and promote mental health and well-being.”India and other countries need to pace their efforts to meet the targets of SGD. The United Nations has addressed and emphasized the early diagnosis and treatment of cancer in a United Nations high-level meeting in 2018 on NCD.[7,8]

The Indian government took different measures to reduce mortality and disability due to different cancer types, which include the National Program for Non-Communicable Diseases, the National Cancer Registry Programme (NCRP), and the National Institute of Cancer Prevention and Research.[9] For fulfilling the SDG goals and reducing the disability and mortality due to cancer, the comprehensive local study of cancer death and other patterns is required, which is still sparse. Because cancer incidence, disability and mortality pattern show large variation with epidemiological factors, and also change for different organs.[10] This study aims to fill this gap and find out the pattern of different cancer sites and their survival in different age groups in the study area. With a large sample size collected over a decade, it will not only act as a regional guide for age- and gender-wise screening, indicating which cancer should be suspected in a particular age and gender, improving screening modalities, but this study will also act as a data subset for other studies trying to find out a pattern of cancer and its mortality among different regions and races. This data study will compare the similarity in global data with the data of the tertiary care center of Bareilly, UP.

Objectives

To evaluate the patterns and survival outcomes of major anatomical site–specific cancers across different age groups and genders over a ten-year period at a tertiary care center in the Bareilly region of Uttar Pradesh, India.

Methodology

Study design: This was a retrospective, record based study conducted at the tertiary cancer center, Bareilly, Uttar Pradesh. The study analyzed patient records from January 2014 to November 2024. The study region covered all patients from districts within Bareilly region of western Uttar Pradesh.

Data retrieval: Patient records were initially obtained from the hospital registry/medical records department. Patients data abstraction was conducted using a standardized format including demographic, clinical, and admission details (IP number, patient number, address, city/district, age, sex, admission and discharge dates, diagnosis, discharge status, and ICD codes), were retrieved from the hospital registry for analysis. Then data cleaning de-duplication, and de-identification procedures were applied to maintain data quality and protect patient confidentiality.

Study population: All patients with histologically confirmed cancers, residing in treated at a Bareilly region and nearby districts, treated at a tertiary care center in Bareilly, UP were eligible. Non- confirmed cases and incomplete data were excluded.

Data Retrieval and Cleaning: “The process started with screening of an initial dataset of 58,899 cancer patients, which represented all cancer types recorded during the study period. Following de-duplication procedures, which removed repeat admissions/redundant records, a total of 32,581 unique patient entries were retained corresponding to approximately 55% of the original dataset. This cleaning stage ensured that each patient was represented only once in the analysis. From this refined cohort, based on diagnostic coding and clinical verification. Socio-demographic variables (age, sex, district, and block), clinical variables (tumor site, discharge outcome) and residential addresses were extracted from medical records and the institutional cancer registry. For confidentiality, patient identifiers were stripped prior to analysis.Follow-up was based solely on hospital registry records and no active patient tracing was done. Death was defined as in-hospital mortality which was recorded at discharge; patients were censored at last hospital contact or study end that is November 2024.”

Statistical analysis: For all statistical analysis R software (R Studio version 2026.01.0-392) was used. To summarize baseline characteristics of the study population descriptive statistics were used. Categorical variables were expressed as frequencies and percentages. Overall survival was defined as the time from date of first admission/diagnosis to death or last follow-up. Patients who were alive at the end of follow-up were treated as censored observations. Kaplan–Meier method was used to estimate the survival probabilities and survival curves, which was generated for different cancer sites using R software. Cox proportional hazards regression analysis was done to evaluate the association between clinical and demographic variables, and mortality. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to estimate the relative risk of death for different cancer sites. A p-value <0.05 was considered statistically significant.

Ethical consideration: The study protocol was approved by the Institutional Ethics Committee through ethical clearance certificate no. SRMSIMS/ECC/2025/154, dated 18 October 2025. The study used retrospective hospital registry data, and all patient identifiers were removed prior to analysis to maintain confidentiality.

Result

Table 1 represents a total of 32,581 patients, which were included in our analysis. The most frequent cancer sites seen was oral cavity and pharynx (26.0%), followed by female genital organs (23.6%), lung and bronchus (16.4%), breast (15.1%), and gallbladder and bile ducts (10.2%). Colorectal cancer burden was found to be 4.8% of all cases, while lymphoid and hematopoietic malignancies (2.1%) and male genital organ cancers (1.9%) were the least reported malignancies overall. The cohort of the study was predominantly geriatric age group,around 59% patients were aged ≥75 years, which was followed by 45–59 years age group whose burden was seen to be 18% and 60–74 years accounted for 14%; whereas only 9.7% of patients were younger than 45 years. This age pattern was similar for most of the solid tumors analysed. Breast (70%), colorectal (61%), lung (58%), and female genital malignancy (57%) revealed a majority of patients aged ≥75 years. Gallbladder and bile duct tumors were comparatively seen in younger population, with around 50% of patient aged ≥75 years and higher representation in the 45–74 age group. Whereas, lymphoid/hematopoietic and male genital malignancies revealed a comparitively very younger age group, which is roughly one-fourth of cases occurring before age 45.

Gender analysis revealed, 57% of patients were female and 43% were male. Breast (98%) occurred almost exclusively in women. Oral cavity and pharyngeal cancers showed strong male predominance (87.1%) in the study region; similarly lung cancer also did (79%). Gallbladder and bile duct cancers were found to be more frequent in women (68%), whereas colorectal cancer showed moderate male predominance (58%). Median follow-up time had variance significantly by anatomical site of cancer, ranging from 10 days (IQR 2–83) for lymphoid and hematopoietic malignancies to 195 days (IQR 50–516) for breast cancer. The overall mortality during follow-up was 6.2% (n = 2,011). Site-specific mortality was seen highest in patients having lymphoid and hematopoietic cancers (10%), gallbladder and bile duct cancers (9.0%), and lung cancer (8.5%), while lower mortality was observed in patients of colorectal (3.1%) and breast cancer (4.4%).

Figure 1 shows Kaplan–Meier analysis which shows significant heterogeneity in overall survival across cancer sites (log-rank test; p < 0.0001). Survival probabilities diverged early following first admission and they continued to separate over time, which indicates significant differences in both early/long-term mortality patterns of different anatomical site malignancy.

Patients having colorectal and breast cancers revealed the most favorable survival profiles. Whereas colorectal cancer patients showed the highest sustained survival probability throughout follow-up, which was only declined gradually over time. Patients suffering from breast cancers similarly have demonstrated consistently a high survival, which had relatively limited early mortality and stable long-term survival estimates.

In comparison,patients suffering from gallbladder and bile duct cancer showed the lowest survival rates.In these patients survival declined sharply within the first 2–3 years of arrival of symptoms, showing pronounced early mortality. By around 3 years, survival probability had declined markedly when compared with all other cancer sites, and long-term survival remained substantially low.

Patients with lung cancer and lymphoid/hematopoietic malignancies also exhibited negative survival trends, which was marked by steeper early reduction compared with breast and colorectal cancers. Although their survival trajectories were less sudden than those reported for gallbladder cancer, they consistently remained among the poor survival curves over follow-up.

Oral cavity and pharyngeal cancers and male genital organ cancers revealed intermediate survival patterns. While early survival was relatively maintained, gradual declines were observed with time, resulting in moderate long-term survival probabilities. Female genital organ cancers showed survival results between the higher-survival (breast, colorectal) and lower-survival (lung, gallbladder, hematologic) groups. The number-at-risk table reveals high attrition over time, particularly beyond 5–7 years, with very small risk sets after 8–9 years in several cancer groups. Consequently, long-term survival estimates in the tail of the curves should be interpreted with caution due to increasing statistical uncertainty.

Figure 1: Kaplan–Meier Survival Curves and Number at Risk by Cancer Site

Table 2 shows the factors associated with mortality among cancer patients. Using breast cancer as the reference category, the hazard of death was significantly higher among patients with gallbladder/bile duct cancer (HR = 4.64, 95% CI: 3.79–5.68, p < 0.001), lung/bronchus cancer (HR = 3.15, 95% CI: 2.55–3.91, p < 0.001), and oral cavity/pharynx cancer (HR = 2.54, 95% CI: 2.04–3.17, p < 0.001). However, colorectal cancer (HR = 1.01, 95% CI: 0.73–1.40, p = 0.93) and female genital cancer (HR = 1.12, 95% CI: 0.94–1.35, p = 0.22) did not show a statistically significant difference in hazard compared to breast cancer. This indicates that patients with gallbladder/bile duct, lung/bronchus, and oral cavity/pharynx cancers had significantly poorer survival compared to breast cancer patients.With patients aged <30 years as the reference group, those aged 45–59 years had a significantly higher hazard of death (HR = 2.29, 95% CI: 1.02–5.15, p = 0.04). Although hazard ratios were higher in the age groups 30–44 years (HR = 2.10, p = 0.08), 60–74 years (HR = 1.42, p = 0.40), and 75+ years (HR = 1.25, p = 0.59), these were not statistically significant at the 5% level. This suggests that mortality risk increases with age, but the increase was statistically significant only for the 45–59 years age group in this model.

Sex was not significantly associated with survival (HR = 1.02, 95% CI: 0.88–1.19, p = 0.79), indicating no significant difference in mortality risk between males and females.

Discussion

This study analyses one of the largest single center data of last decade of around 32 thousand cancer in Bareilly, UP. The findings show a large variation across gender, age groups, and different cancer types based on organ affected. While majority of the data of this study supports global cancer epidemiology, there are certain findingswhich also highlight unique regional variations carrying clinical and public health importance. Oral cancer ranks 6^th in the world in prevalence with burden of 3-4% of total cancer burden[11] but this study shows oral cancer as the most common cancer with rank of 1^st in prevalence and a burden of around 26%. This is well constant with other prevalence studies of south Asia. Oral cancer is disproportionately high in India due to widespread use of smokeless tobacco, betel quid, and smoking practices.[12] This regional excess has been constantly reported in multiple registries based studies of India and reflects socio-cultural habits and inadequate screening. Thus this regional excess suggests and points towardsimproving the targeted screening approach in this region for oral cancer.

Similarly the high burden of female genital cancer is also constant with evidence from other studies showing high incidence in low and middle income countries (LMIC), whereas cervical cancer still remains one of the leading cause death due to malignancy in females. The major contributor for this problem remains poor coverage of HPV vaccination and suboptimal screening. In contrast high income countries are seeing a decline in the incidence of cervical cancer, which is due to strong vaccination coverage and robust public screening measures. This shows a strong disparity in the healthcare systems[13]

The large number of cases of gall bladder and bile duct cancers is something to note because globally gallbladder cancer is relatively rare. However, north India and specifically Uttar Pradesh is considered as high incidence belt. Environmental exposures (such as arsenic-contaminated water), chronic infections, gallstones, and dietary factors have been suggested reasons behind this.[14]

A crucial finding in this study is 59% patients of cancer were above the age of 75 years, which supports many global studies where peak of cancer cases is seen in the age group of around 75-90years of age. This might be due to increasing life expectancy, or certain biases such as referral bias or hospital based sampling bias.[15] The higher proportion of elderly patients may also suggest delayed healthcare utilization, where the patient enters the healthcare system late but it must also be correlated with staging of the cancer, hence more studies are required to answer this gap. In present study, hazard ratios for mortality were not highest in the oldest age group, with relatively higher hazards observed in middle-aged patients (30–59 years). This finding is against to established epidemiological trends, where mortality typically increases with advancing age.[15] A likely explanation is the limitation of survival assessment to in-hospital outcomes, which may underestimate mortality in elderly patients who are more likely to experience death outside the hospital setting or after discharge. However one thing remains significant and important, that is mortality burden is very high in the elderly age group and policy changes should be more focused on increased frequency of screening of different cancers especially in age group above 50 years of age.

Male predominance in oral (87.1%) and lung cancers (79%) is well documented and attributed to more exposure to Tobacco and other carcinogens.[12] Female predominance in gallbladder cancers (68%) can be attributed to the hormonal factors in, higher prevalence of gallstones, and metabolic differences in addition to north Indian plane.[16] The breast cancer is almost exclusively reported in females but still has fewer burdens when compared to western countries – where breast cancer is still the leading cause of malignancy. This shows the difference in the cancer profile of developing and developed countries.[17] The gender disparity that is seen is not just biological susceptibility but also shows the role of behavior and healthcare access. High number of cases in males shows poor health seeking behavior in rural females. This study has several important findings which suggest certain changes however more such region based studies with data of staging is required to make a more accurate comment.

The suggestions are that region specific Tabaco control strategy for oral cancer control should be used. Also for control of gall bladder cancer, in north Indian plane specific strategy for environmental control and dietary interventions can be used. Cancers like lung cancer and gall bladder cancer have extremely poor prognosis, for early detection of such cancers strong screening programs would be of great use. Secondly, for more research and better tracking of survival at population level robust cancer registry can be maintained. Lastly, screening programs must be age, region and gender specific because global burden might not be our priority locally.So, data for age, gender and region for cancer must be studied by different researches at local levels. The data strongly indicates that primary prevention must target tobacco and environmental exposures of carcinogens, Screening programs should expand beyond breast and cervical cancers, Regional cancer registries must be strengthened for accurate surveillance,and Geriatric oncology services need prioritization.

Limitations

This study was a retrospective hospital based study that predisposes it to selection bias, information bias and data irregularities, although best efforts were made to clean and validate the data. This data, as was derived from hospital based registry may not fully represent the general population of Bareilly. The Patients reporting to the tertiary care hospital are often more sick or are referred with advanced disease; this can influence the occurrence and survival pattern.The data on important clinical variables such as staging of disease, socioeconomic status of the patient, treatment modalities, and comorbidities were not recorded uniformly or were not available. Absence of these variables limits the ability to do adjusted survival analysis.

Strength

This study has a large sample size of 32 thousand patients collected over a decade making it one of the most comprehensive single center studies of Bareilly region. This large dataset improves statistical power and reliability of the observed patterns. This study provides an analysis of multiple major anatomical site cancers within a single frame. This helps in comparative evaluation across different malignancy. The study incorporates survival analysis using Kaplan–Meier curves and Cox proportional hazards regression, enabling both descriptive and analytical assessment of outcomes.

Conclusion

This study concludes significant heterogeneity in survival across cancer sites, with breast and colorectal cancers showing the most favorable survival outcomes, whereas gallbladder, lung, and oral cavity/pharyngeal cancers were associated with significantly poorer survival. Distinct age- and sex-specific patterns were also observed, reflecting the regional epidemiology of cancer in North India. These findings highlight the need for region-specific cancer control strategies, like strengthened tobacco-control measures/improved early detection, and targeted screening for high-burden, poor-prognosis cancers such as oral cavity, lung, and gallbladder cancers. The study provided useful evidence for planning age-sex specific awareness/screening initiatives. Furthermore, hospital-based cancer registries can generate valuable real-world evidence to identify regional trends and support healthcare planning. However, prospective multicenter studies incorporating detailed clinical information, including cancer stage, treatment modalities, and long-term follow-up, are needed to better characterize survival outcomes and guide evidence-based cancer control policies in the region.

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