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Record W3214760680 · doi:10.3390/curroncol28060411

Screening for Colorectal Cancer Leading into a New Decade: The “Roaring ‘20s” for Epigenetic Biomarkers?

2021· review· en· W3214760680 on OpenAlexvenueno aff
Hélder Almeida-Lousada, André Mestre, Sara Ramalhete, Aryeh J. Price, Ramon Andrade de Mello, Ana Marreiros, Ricardo Pires das Neves, Pedro Castelo‐Branco

Bibliographic record

VenueCurrent Oncology · 2021
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsMedicineEpigeneticsColorectal cancerCancerBioinformaticsOncologyComputational biologyInternal medicineGeneticsBiologyGene

Abstract

fetched live from OpenAlex

Colorectal cancer (CRC) has an important bearing (top five) on cancer incidence and mortality in the world. The etiology of sporadic CRC is related to the accumulation of genetic and epigenetic alterations that result in the appearance of cancer hallmarks such as abnormal proliferation, evasion of immune destruction, resistance to apoptosis, replicative immortality, and others, contributing to cancer promotion, invasion, and metastasis. It is estimated that, each year, at least four million people are diagnosed with CRC in the world. Depending on CRC staging at diagnosis, many of these patients die, as CRC is in the top four causes of cancer death in the world. New and improved screening tests for CRC are needed to detect the disease at an early stage and adopt patient management strategies to decrease the death toll. The three pillars of CRC screening are endoscopy, radiological imaging, and molecular assays. Endoscopic procedures comprise traditional colonoscopy, and more recently, capsule-based endoscopy. The main imaging modality remains Computed Tomography (CT) of the colon. Molecular approaches continue to grow in the diversity of biomarkers and the sophistication of the technologies deployed to detect them. What started with simple fecal occult blood tests has expanded to an armamentarium, including mutation detection and identification of aberrant epigenetic signatures known to be oncogenic. Biomarker-based screening methods have critical advantages and are likely to eclipse the classical modalities of imaging and endoscopy in the future. For example, imaging methods are costly and require highly specialized medical personnel. In the case of endoscopy, their invasiveness limits compliance from large swaths of the population, especially those with average CRC risk. Beyond mere discomfort and fear, there are legitimate iatrogenic concerns associated with endoscopy. The risks of perforation and infection make endoscopy best suited for a confirmatory role in cases where there are positive results from other diagnostic tests. Biomarker-based screening methods are largely non-invasive and are growing in scope. Epigenetic biomarkers, in particular, can be detected in feces and blood, are less invasive to the average-risk patient, detect early-stage CRC, and have a demonstrably superior patient follow-up. Given the heterogeneity of CRC as it evolves, optimal screening may require a battery of blood and stool tests, where each can leverage different pathways perturbed during carcinogenesis. What follows is a comprehensive, systematic review of the literature pertaining to the screening and diagnostic protocols used in CRC. Relevant articles were retrieved from the PubMed database using keywords including: "Screening", "Diagnosis", and "Biomarkers for CRC". American and European clinical trials in progress were included as well.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.270
GPT teacher head0.501
Teacher spread0.231 · 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 teacher head, not a consensus.

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".

Quick stats

Citations18
Published2021
Admission routes1
Has abstractyes

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