ReviewCureus2025
Enhancing Cancer Screening and Early Diagnosis in India: Overcoming Challenges and Leveraging Emerging Technologies.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Review
- Article
- Enhancing Rural Breast Cancer Screening Uptake: A Three-Arm Comparative Study of Outreach Strategies.International journal of breast cancer · 2026Article
- Article
- The global cancer crisis: a review of growing burden, deepening inequality and initiatives for prevention and early detection.Ecancermedicalscience · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review addresses the significant challenges and technological developments in cancer screening and early diagnosis in the context of India's diverse and resource-constrained healthcare landscape. Selected cancers like breast, cervical, oral, lung, and colorectal cancers are focused on, and established screening methods such as clinical breast examination (CBE), mammography, visual inspection with acetic acid (VIA), HPV DNA testing, and oral visual inspection (OVI) are reviewed. These are cost-effective strategies that are proven to reduce mortality. However, they face systemic barriers, including low awareness, socio-cultural stigma, and discontinuous healthcare access. Emerging technologies in cancer screening like liquid biopsy (detecting circulating tumor DNA), artificial intelligence (AI)-driven imaging (enhancing radiological accuracy), next-generation sequencing (identifying genetic mutations), and methylation-based ctDNA analysis (epigenetic profiling) are considered to be transformative in cancer management. Digital pathology and telemedicine are also found to improve diagnostic precision and rural/remote outreach. However, high costs, technical complexity, and limited validation in Indian settings are the major challenges that hinder their widespread adoption. The review emphasizes the need for culturally tailored awareness campaigns, integration of screening with the already existing public health programs, and increased investments in indigenous research to address genetic and environmental risk factors. It specifically advocates for strengthening the primary healthcare infrastructure, training community health workers, and leveraging mobile screening units to bridge urban-rural disparities. A combination of scalable low-resource methods and strategic adoption of emerging technologies can help in mitigating India's growing cancer burden. This aligns with global targets to reduce premature non-communicable disease (NCD) mortality by 2030. This synthesis of evidence-based practices and innovative strategies offers a roadmap for policymakers and stakeholders to enhance equitable cancer care delivery nationwide.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.