Evidence map›Paper›PMID 42639990›Full record

ArticleCancer medicine2026

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.

Gokul Sarveswaran, Abhinav Ramraj, Jayasankar Sankarapillai, Swetha Punathil, Prashant Mathur

Abstract readValidation Study
In one paragraph

Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gokul SarveswaranIndian Council of Medical Research-National Institute of NCD Epidemiology (ICMR-NINE), Bengaluru, India.
Abhinav RamrajIndian Council of Medical Research-National Institute of NCD Epidemiology (ICMR-NINE), Bengaluru, India.ORCID https://orcid.org/0009-0002-9621-3248
Jayasankar SankarapillaiIndian Council of Medical Research-National Institute of NCD Epidemiology (ICMR-NINE), Bengaluru, India.
Swetha PunathilIndian Council of Medical Research-National Institute of NCD Epidemiology (ICMR-NINE), Bengaluru, India.
Prashant MathurIndian Council of Medical Research-National Institute of NCD Epidemiology (ICMR-NINE), Bengaluru, India.ORCID https://orcid.org/0000-0002-9271-1373

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough 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

methodsThis 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.

resultsOur 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.

conclusionThis 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.

Indexed as

NeoplasmsNeoplasm StagingPublic HealthDeveloping CountriesFemaleHumansIndiaMaleRegistriesUterine Cervical Neoplasmscancer registrycancer stagingdata harmonizationepidemiological surveillanceSEER summary stageTNM classification

Identifiers

PMID42639990
PMCPMC13505189

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.