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Record W4281706558 · doi:10.1200/go.22.00004

Colorectal Cancer Treatment Characteristics and Concordance With Guidelines in Sri Lanka: Results From a Hospital-Based Cancer Registry

2022· article· en· W4281706558 on OpenAlexaff
Don Thiwanka Wijeratne, Sanjeeva Gunasekara, Christopher M. Booth, Scott Berry, Matthew Jalink, Laura M. Carson, Bishal Gyawali, Hasitha Promod, Umesh Jayarajah, Sanjeewa Seneviratne

Bibliographic record

VenueJCO Global Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineConcordanceColorectal cancerCancer registryCancerStage (stratigraphy)Internal medicinePopulationOncologyCohortAdjuvant therapy

Abstract

fetched live from OpenAlex

PURPOSE: Colorectal cancer (CRC) ranks among the top five incident cancers in Sri Lanka (SL). Here, we describe disease characteristics and treatment patterns of patients with CRC in SL. METHODS: All adult patients (age > 18 years) diagnosed with CRC during 2016-2020 were identified from the National Cancer Institute SL cancer registry. Cancer stage at diagnosis was defined according to the seventh edition of the TNM staging system. Concordance between recommendations for adjuvant therapy and actual rates of delivery was also analyzed. Descriptive statistics were used to describe the study cohort and treatment patterns. RESULTS: A total of 1,578 patients were diagnosed with CRC during the study period, 53% (n = 830) with colon cancer and 47% (n = 748) with rectal cancer. Mean age was 61 (range, 18-91) years. Stage distribution was 13%, 28%, 46%, and 12% for stage I, II, III, and IV cancers, respectively. Adjuvant chemotherapy was delivered to 82% of patients with stage III colon cancer. There was a lack of concordance with delivery of neoadjuvant chemoradiotherapy, which was only delivered to 50% of patients with stage III rectal cancer for whom this treatment was indicated. CONCLUSION: Aging population and advanced stage of CRC at diagnosis will continue to challenge the provision of high-quality CRC care in SL. Further quantitative and qualitative research may help better understand the nonconcordance with treatment guidelines. Such information would help ease the burden of advanced-stage CRC in SL.

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 score0.176
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.337
Teacher spread0.312 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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