Revised Bethesda Guidelines for Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome) and Microsatellite Instability
Revised Bethesda Guidelines for Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome) and Microsatellite Instability is a research paper published in JNCI Journal of the National Cancer Institute (2004). On theSindex it has a DataRank of 1.2. It has been cited 3,172 times.
Abstract
Hereditary nonpolyposis colorectal cancer (HNPCC), also known as Lynch syndrome, is a common autosomal dominant syndrome characterized by early age at onset, neoplastic lesions, and microsatellite instability (MSI). Because cancers with MSI account for approximately 15% of all colorectal cancers and because of the need for a better understanding of the clinical and histologic manifestations of HNPCC, the National Cancer Institute hosted an international workshop on HNPCC in 1996, which led to the development of the Bethesda Guidelines for the identification of individuals with HNPCC who should be tested for MSI. To consider revision and improvement of the Bethesda Guidelines, another HNPCC workshop was held at the National Cancer Institute in Bethesda, MD, in 2002. In this commentary, we summarize the Workshop presentations on HNPCC and MSI testing; present the issues relating to the performance, sensitivity, and specificity of the Bethesda Guidelines; outline the revised Bethesda Guidelines for identifying individuals at risk for HNPCC; and recommend criteria for MSI testing.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
1.2
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.