Prognostic Factors and Survival Outcomes in Esophageal Cancer Patients from North-East India: A Hospital-Based Cohort Study Using Log-Rank Test and Binary Logistic Regression Analysis
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.12.15Keywords:
Esophageal cancer, Survival analysis, Prognostic factors, Parametric model, Binary logistic regression, Log-Rank test, Chemotherapy, Radiotherapy.Dimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Background: Esophageal cancer remains one of the most prevalent malignancies in North-East India, accounting for significant morbidity and mortality. The region demonstrates age-adjusted incidence rates substantially higher than other parts of India, with squamous cell carcinoma being the predominant histological type. Understanding prognostic factors and survival outcomes is essential for optimizing therapeutic interventions and patient counseling.Abstract
Objective: This study aimed to identify prognostic factors influencing survival outcomes in esophageal cancer patients from North-East India using log-rank test and binary logistic regression analysis.
Methods: A hospital-based retrospective cohort study of 502 esophageal cancer patients was conducted at the State Cancer Institute, Gauhati Medical College, Assam, India, for the period 2019–2021. Survival data were analyzed using the Kaplan-Meier method with log-rank tests to compare survival curves between demographic and clinical variables. Binary logistic regression with logit link function was employed to identify independent predictive factors for mortality.
Results: The study cohort consisted of 502 patients (80.68% aged ≥50 years, 67.3% males) with 271 deaths (54%) recorded during follow-up. Median overall survival was 14 months (95% CI: 11.99–16.01). Log-rank test revealed statistically significant associations with survival for esophagostomy surgery (p<0.001) and chemotherapy (p<0.001). Binary logistic regression identified chemotherapy (p=0.003, OR=1.891) and radiotherapy (p=0.049, OR=0.626) as independent prognostic factors, with chemotherapy conferring increased odds of mortality, whereas radiotherapy demonstrated protective effects.
Conclusions: This study demonstrates that chemotherapy and radiotherapy status constitute independent prognostic factors for esophageal cancer survival in North-East India. The protective effect of radiotherapy and the association with chemotherapy warrant further investigation to optimize multimodal treatment strategies. Socioeconomic status and basic demographic factors did not significantly influence survival outcomes after adjustment for treatment variables.
How to Cite
Downloads
Similar Articles
- Deepesh Bhardwaj, Niyati Chaudhary, Blueprints of Green: Determining Key Determinants of Sustainable Real Estate Projects in Delhi NCR , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RFSVMDD: Ensemble of multi-dimension random forest and custom-made support vector machine for detecting RPL DDoS attacks in an IoT-based WSN environment , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- Dharmendra Singh, Surabhi Singh, Identification of Microsatellite DNA for Population Genetic Analysis in Tor tor , The Scientific Temper: Vol. 11 No. 1&2 (2020): The Scientific Temper
- Priya Sharma, Jyoti Rana, Understanding Customer Awareness and effectiveness of Social Media Marketing in Banks , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
- Vikas Chaudhary, Parul Jhajharia, Mediation of competitive advantage between strategy management practices and organizational performance , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Arunima Dey, New gender representation on the Indian OTT platform: A study on web series “Made in Heaven” , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Modenisha U, Ritha W, A mathematical model for sustainable landfill allocation and waste management , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- V. Yamuna , P. Kandhavadivu, Recent developments in the synthesis of superabsorbent polymer from natural food sources: A review , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Renuka Thapliyal, Can Shimla be fitted into the compact city model? , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Olivia C. Gold, Jayasimman Lawrence, Ensemble of CatBoost and neural networks with hybrid feature selection for enhanced heart disease prediction , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 30 31 32 33 34 35 36 37 38 39 > >>
You may also start an advanced similarity search for this article.

