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Record W3212868920 · doi:10.2217/fon-2021-0592

Patterns of Colorectal Cancer Diagnosis Among Younger Adults in a Real-World, Population-Based Cohort

2021· article· en· W3212868920 on OpenAlexaffabout
Omar Abdel‐Rahman, Hatim Karachiwala, Sheryl Koski

Bibliographic record

VenueFuture Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineQuartileColorectal cancerPopulationOdds ratioDemographyLogistic regressionRetrospective cohort studySocioeconomic statusInternal medicineCohortCancerConfidence interval

Abstract

fetched live from OpenAlex

Aims: To review the patterns of early-onset (<50 years old) colorectal cancer (CRC) in Alberta across the past 15 years among different socioeconomic and demographic patient subgroups. Methods: This is a retrospective, population-based study based on Alberta administrative databases. Income level was identified via income information from the 2006 Canadian census. Patients with colorectal adenocarcinoma diagnosed 2004–2018 were included. Frequency analyses were used to examine the percentage of early-onset CRC cases among different subgroups over the period studied. Multivariable logistic regression analysis was used to examine factors associated with the development of early-onset CRC. Results: A total of 24,912 patients were included, of whom 2096 (8.4%) were diagnosed at age <50 years and 22,816 (91.6%) at age ≥50 years. The percentage of patients diagnosed at age <50 years increased over time (10.2% in 2018 vs 7.9% in 2004; p < 0.003). Higher income was associated with younger age at diagnosis of CRC (odds ratio [OR] for quartile 1 vs quartile 4: 0.54; 95% CI: 0.47–0.62). Other factors associated with younger age at diagnosis included female sex (OR for male vs female: 0.85; 95% CI: 0.78–0.94), distal CRC (OR: 1.66; 95% CI: 1.50–1.84) and North zone (OR for South zone vs North zone: 0.74; 95% CI: 0.60–0.92). Conclusion: The proportion of patients (out of the overall CRC population) with early-onset CRC, increased in Alberta throughout the study duration (particularly left-sided CRC). There is a need to reassess the current age limits for CRC screening in Canada in view of these findings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.302
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2021
Admission routes2
Has abstractyes

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