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Record W4213341255 · doi:10.1093/jcag/gwab049.137

A138 TEMPORAL CHANGES IN SURVIVAL OF METASTATIC COLORECTAL CANCER PATIENTS: A POPULATION BASED STUDY

2022· article· en· W4213341255 on OpenAlexaffabout
C Wang, Sujoy Ghosh, Omar M. E. Abdel‐Salam, Hatim Karachiwala

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineColorectal cancerCancer registryPopulationCancerComorbidityInternal medicineDiseaseRegimenStage (stratigraphy)Survival analysisRelative survivalOncologyEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background Colorectal cancer (CRC) remains a significant cause of morbidity and mortality in Canada. While early screening programs and improvements in surgical and oncologic therapies have led to a steady decline in the mortality rate of CRC, survival in metastatic stage IV disease remains low. Furthermore, it is unclear which factors have the largest impact on survival leading to a wide range in quoted survival times between studies. Aims This study examines the impact of various disease, patient, and treatment factors on the outcomes and survival of stage IV CRC patients in Alberta, Canada from 2004–2014 and compares the survival data of this population to the most current statistics from clinical trials. It is hypothesized that survival should increase over the past decade and factors such as age, presence of comorbidities, number of metastases, and chemmotherapy regimen chosen will have significant impacts on overall survival. Methods A registry-based analysis was conducted identifying patients diagnosed with advanced colorectal cancer in Alberta. Specifically, we collected demographic information for patients in 3 time intervals: 2004–2006, 2008–2010, and 2012–2014. Data collected included year of diagnosis, age, sex, number of metastatic sites at diagnosis (single vs multiple), area of residence (rural vs urban), Charlson comorbidity index, and primary site of disease. The survival data from the three timeframes were compared. Results A total of 1476 patients were studied across the 3 time intervals. Over the three time periods examined in this study, there was essentially no clinically significant difference in the survival curves. Median survival from 2004–2006 was 22.3 months, from 2008–2010 was 24.4 months, and from 2012–2014 was 24.0 months. While median survival did increase over the 3 time periods, the improvement was not statistically significant (p=0.196). Overall survival in this cohort was 23.9 months. Patients who were >68 years old or those who had multiple sites of metastases and multiple comorbidities had a worse overall survival (p<0.05). Conclusions Despite a decade of advances in both the surgical and medical management of Stage IV CRC, the overall survival remains low. Furthermore, there remains a wide range in the quoted survival for studies performed with this cohort. This variation is almost certainly due to the heterogeneity of the study population in stage IV disease. Future studies should employ broad inclusion criteria in order to address these important gaps in the external validity of oncology trials. Survival of Stage IV Colorectal Cancer Over One Decade (2004–2014) Funding Agencies None

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)0.001
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 score0.753
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.016
GPT teacher head0.270
Teacher spread0.254 · 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".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

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