Abhinav Ramraj
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Abhinav Ramraj has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
Gokul Sarveswaran
Indian Council of Medical Research–National Institute of NCD Epidemiology (ICMR‐NINE) Bengaluru India
1 shared publicationJayasankar Sankarapillai
Indian Council of Medical Research–National Institute of NCD Epidemiology (ICMR‐NINE) Bengaluru India
1 shared publication- Prashant Mathur
Indian Council of Medical Research–National Institute of NCD Epidemiology (ICMR‐NINE) Bengaluru India
1 shared publication Swetha Punathil
Indian Council of Medical Research–National Institute of NCD Epidemiology (ICMR‐NINE) Bengaluru India
1 shared publication
Latest Publications
- Open Access
- 25 August 2026
- Published by Wiley in Cancer Medicine
- Vol. 15 (8)
Harmonization Framework for Translating Clinical Cancer Staging Systems for Public Health and Surveillance Use in Low‐ and Middle‐Income Countries: Validation Using Indian Cancer Registry Data
Introduction: Although accurate information on cancer stage at diagnosis is critical for surveillance, cancer registries in low‐ and middle‐income countries (LMICs) report incomplete stage data. The use of multiple stage classification systems—UICC/AJCC‐TNM‐system, SEER‐Summary‐Stage (SSS), Essential‐TNM (ETNM), and Condensed‐TNM (CTNM) complicates their utility and interoperability. The lack of a unified framework for translating between their categories limits data harmonization for global epidemiological analyses. Materials and Methods: This study introduces a mapping framework for translating these four staging systems for common screening‐amenable cancers (breast, cervical, colorectal, and oral). Using the TNM criteria as reference, all categories were systematically compared and mapped to corresponding categories in SSS, ETNM, and CTNM. The fields were color‐coded to visualize prognostic gradients across classifications. This mapping was then validated using a registry‐wide representative sample of 4,000 cancer cases with an assigned TNM stage. Matches were categorized as either being complete or as first‐ or second‐degree mismatches to assess the extent of concordance and discordance. Results: Our analysis highlighted cancer‐specific variations in prognostic gradation and concordance. Cervical and colorectal cancers had a steady gradient, representing the best‐case scenarios, while breast and oral cancers showed greater discordance. Overall, SSS aligned with TNM categories, depicting maximal one‐to‐one associations. While ETNM is more concordant for colorectal cancer (100% match vs. 89%), SSS is most concordant for cervical cancer (80%), and to a lesser extent, breast cancer (77%). CTNM offers the least concordance with traditional TNM across cancer sites. Localized and metastatic stages aligned almost universally, except in oral cancer. Conclusion: This mapping exercise provided a comprehensive framework for translating cancer stage categories, offering LMIC registries a way to balance clinical relevance, epidemiological utility, and operational feasibility. Concordance among the systems varied by cancer type, underscoring the need for cancer‐specific adaptations.
- 25 August 2026
- Published by Wiley in Cancer Medicine
- Vol. 15 (8)
Open AccessHarmonization Framework for Translating Clinical Cancer Staging Systems for Public Health and Surveillance Use in Low‐ and Middle‐Income Countries: Validation Using Indian Cancer Registry Data
Introduction: Although accurate information on cancer stage at diagnosis is critical for surveillance, cancer registries in low‐ and middle‐income countries (LMICs) report incomplete stage data. The use of multiple stage classification systems—UICC/AJCC‐TNM‐system, SEER‐Summary‐Stage (SSS), Essential‐TNM (ETNM), and Condensed‐TNM (CTNM) complicates their utility and interoperability. The lack of a unified framework for translating between their categories limits data harmonization for global epidemiological analyses. Materials and Methods: This study introduces a mapping framework for translating these four staging systems for common screening‐amenable cancers (breast, cervical, colorectal, and oral). Using the TNM criteria as reference, all categories were systematically compared and mapped to corresponding categories in SSS, ETNM, and CTNM. The fields were color‐coded to visualize prognostic gradients across classifications. This mapping was then validated using a registry‐wide representative sample of 4,000 cancer cases with an assigned TNM stage. Matches were categorized as either being complete or as first‐ or second‐degree mismatches to assess the extent of concordance and discordance. Results: Our analysis highlighted cancer‐specific variations in prognostic gradation and concordance. Cervical and colorectal cancers had a steady gradient, representing the best‐case scenarios, while breast and oral cancers showed greater discordance. Overall, SSS aligned with TNM categories, depicting maximal one‐to‐one associations. While ETNM is more concordant for colorectal cancer (100% match vs. 89%), SSS is most concordant for cervical cancer (80%), and to a lesser extent, breast cancer (77%). CTNM offers the least concordance with traditional TNM across cancer sites. Localized and metastatic stages aligned almost universally, except in oral cancer. Conclusion: This mapping exercise provided a comprehensive framework for translating cancer stage categories, offering LMIC registries a way to balance clinical relevance, epidemiological utility, and operational feasibility. Concordance among the systems varied by cancer type, underscoring the need for cancer‐specific adaptations.