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Record W4414752292 · doi:10.1186/s12913-025-13475-1

Advocacy to action for cervical cancer elimination in the state of Assam: a narrative review of the government policies and the latest report of NCDIR survey

2025· review· en· W4414752292 on OpenAlexaboutno aff
Debabrata Barmon, Anita Nath, Aparajita Aparajita, Jagannath Dev Sharma, Ravi Kannan, Mohammad Shah Alam, Adity Sharma

Bibliographic record

VenueBMC Health Services Research · 2025
Typereview
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsnot available
Fundersnot available
KeywordsCervical cancerGovernment (linguistics)Health careNursing researchQuarter (Canadian coin)CancerPublic healthCancer screeningCall to action

Abstract

fetched live from OpenAlex

BACKGROUND: Assam is the state of north-eastern region of India and is called the 'cancer capital' of the country. There have been accelerated developments in the field of cancer care in the state of Assam in recent times. Though the highest burden of cervical cancer is found in the northeast region, no government- initiated specific programme for cervical cancer elimination has been developed. The strategies implemented at various health care level is mostly derived from the 'umbrella' initiatives of NPCDCS. Due to unique cervical cancer profile of the state, there is a need to fill in the data gaps that needs to be investigated and reported and possible solutions should be outlined to optimise the continuum of care. AIMS AND OBJECTIVES: In this article, we have reviewed the government policies related to cervical cancer and their implementation at various level of health care system of Assam. Primary objective was to report the gap existing for implementation of cervical cancer prevention and treatment strategies in the state of Assam and secondary objective was to outline possible interventions to optimize the delivery of cervical cancer screening. METHODOLOGY: The relevant articles related to government policies were searched on electronic database including Pubmed, national and state-level government websites on health welfare programmes and reports of NCDIR. The data for quantification of gap in cervical cancer services and awareness was extracted from the NCDIR survey conducted as a part of cancer research in the North East Region (CaRes NER), a multidisciplinary programme for preventing and controlling cancer in the north-eastern states run by ICMR-NCDIR, Bengaluru. RESULTS: Timeline of development in the field of cancer care has been summarised in this review under the headings of government initiatives so far for cancer care and its reflection in Assam, call for cervical cancer elimination and its implications in Assam, the current situation in the state of Assam, recent developments in cancer care field in Assam. The quantification of the gaps in cervical cancer care in the state of Assam is based on data from NCDIR survey. Among 2,817 respondents, fewer than a quarter were aware of cancer screening for major cancers, with no specific data available on awareness of cervical cancer. The majority of respondents reported learning about cancer through media or friends and family, while health awareness camps contributed minimally. Only 0.8% were aware of the HPV vaccine, and 0.2% expressed hesitation in discussing cancer. Notably, none of the respondents had undergone cervical cancer screening by any method. In terms of healthcare infrastructure, less than 10% of surveyed Primary Health Centers (PHCs) and none of the Community Health Centers (CHCs) or District Hospitals provided cancer screening services. Fewer than a quarter of PHCs had counseling services for risk behavior, provided by counselors or specialized personnel. Among the medical officers at PHCs, 38.5% had received training under NPCDCS, NHM, or other state-level non-communicable disease (NCD) programs. Gynecologists were available in approximately half of the CHCs and over 80% of district hospitals. However, over 90% of PHCs reported a shortage of laboratory facilities for cancer detection. Regarding HPV vaccination, none of the CHCs offered the service, while it was available in 14.3% of district hospitals and 20.0% of private health facilities CONCLUSION: The key findings of this review and the proposed corrective steps in this paper can be implemented in systematic manner to optimise the delivery of cancer care services and improve the outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.599
Teacher spread0.464 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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