ReviewJournal of family medicine and primary care2024
Early identification of people at high risk of oral cancer-A review of existing risk prediction models.
Review in Journal of family medicine and primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- Comparative trends in oral cancer burden across the globe, China, Europe, the US, Southeast Asia, and Africa (1990-2021): a GBD 2021 analysis.Tropical medicine and health · 2025Article
- Strengthening primary health care: A key strategy in reducing the rising burden of oral cancer.Journal of family medicine and primary care · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction plays a ubiquitous role in cancer care. At every stage of the illness, the patient, the physician, and the family must make numerous decisions. Utilizing epidemiological, clinical, biological, lifestyle, and genetic factors, a cancer-specific risk assessment model calculates the likelihood of developing cancer. In India, oral cancer ranks as the fourth most common cancer, affecting nearly 3,000,00 individuals annually. Because it is in the premalignant stage, oral cancer is easily detectable in the oral cavity. Prompt identification of this lesion can result in better outcomes and a higher standard of living. Advanced statistical techniques have been used to develop prediction algorithms or risk scores that identify individuals with a high risk of developing oral cancer. With the aid of these risk assessment models, specific individuals can be screened to aid in the early detection of the disease, which may result in better outcomes and lifestyle modifications. Finding the best model among the current risk models for oral cancer may be aided by a thorough examination of all these models. Finding and assessing the risk model that primary care physicians can use and easily apply in clinical practice will be made easier with a succinct and straightforward comparison of the models. This review compares the current models to determine which has the best performance metrics, which could lead to a better understanding of the advantages and disadvantages of various risk prediction models of oral cancer.
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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.