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Incomplete preoperative staging results in suboptimal treatment in rectal cancer patients: A population-based study.

2022· article· en· W4206792321 on OpenAlexafffundabout
Sunil V. Patel, Chad McClintock, Shaila J. Merchant, Christopher M. Booth, Antonio Caycedo Marulanda, C Bankhead, Carl Heneghan

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersCanadian Institutes of Health Research
KeywordsMedicineColorectal cancerStage (stratigraphy)Cancer registryPopulationCancerCancer stagingSurgeryCohortInternal medicine

Abstract

fetched live from OpenAlex

20 Background: Individuals with rectal cancer require a number of pre-treatment investigations to determine the local-regional and overall stage of disease. Stage of rectal cancer determines treatment plan; therefore incomplete or inadequate staging may result in sub-optimal care and outcomes. Methods: This is a population based study of all individuals undergoing surgical resection for rectal cancer in Ontario, Canada (population 14.6 million) between 2010 and 2019. Individuals were identified using the Ontario Cancer Registry which includes approximately 95% of all incident cases of rectal cancer in the province. “Complete Staging” in Rectal Cancer has previously been defined and includes assessments of distant metastasis, local-regional stage and an attempt at colonic assessment for synchronous lesions. Patient and care provider characteristics, staging investigations, stage of disease, treatments and long-term outcomes were determined using linked administrative databases. Results: The study cohort included 10,957 individuals with rectal cancer; 24% Stage I, 21% Stage II, 40% Stage III, 7% Stage IV, 8% Missing Stage. The average age was 65 (STD 12.6) and males accounted for 63% of the study population. Incomplete staging occurred in 26%, with incomplete local regional staging being the most common deficiency (21%). Increasing patient age (< 0.001), low volume surgeons (P < 0.001) and low volume hospitals (P < 0.001) were associated with incomplete staging. There was significant regional variation in the completeness of staging (low 68% - High 84%). In those with locally advanced rectal cancer (Stage II and Stage III), incomplete staging was associated with lower rates of preoperative radiation oncology assessments (27% vs. 80%, P < 0.001) and medical oncology assessments (12% vs. 39%, P < 0.001). In addition, incomplete staging was associated with lower rates of any radiation (pre or postoperative) (45% vs. 82%, P < 0.001), lower rates of preoperative neoadjuvant therapy (22% vs. 74%, P < 0.001) and higher rates of post operative radiation (23% vs. 8.3%, P < 0.001). Those with incomplete staging had a lower 5 year overall survival (73% vs. 81%, P < 0.001). Conclusions: In this study, we identified several modifiable risk factors for incomplete staging prior to treatment for rectal cancer. Incomplete staging likely results in suboptimal care in this population, as demonstrated by less oncology referrals and less use of appropriate neoadjuvant therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.155
Threshold uncertainty score0.308

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.137
GPT teacher head0.484
Teacher spread0.347 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2022
Admission routes3
Has abstractyes

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