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Record W1874333151 · doi:10.1158/1538-7445.am2014-4136

Abstract 4136: Comparison of overall survival of Chronic Lymphocytic Leukemia (CLL) patients referred or not referred to a specialized CLL clinic: A Canadian population-based study

2014· article· en· W1874333151 on OpenAlexaffabout
Sara Beiggi, Versha Banerji, Angela Deneka, Jane Griffith, Spencer B. Gibson, James B. Johnston

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsCancerCare ManitobaUniversity of Manitoba
Fundersnot available
KeywordsMedicineChronic lymphocytic leukemiaHazard ratioInternal medicineProportional hazards modelReferralPopulationCohortCancer registryCancerMedical diagnosisPediatricsLeukemiaConfidence intervalPathologyFamily medicine

Abstract

fetched live from OpenAlex

Abstract Chronic Lymphocytic Leukemia (CLL) patients in Manitoba are either referred to the CancerCare Manitoba (CCMB) CLL clinic or receive care from other hematologists/general practitioners. However, it is unknown whether referral to the CLL-specialized clinic alters patients' outcome. All CLL/SLL diagnoses in Manitoba 2007-2011 were obtained from the Manitoba Cancer Registry to create an immunophenotipically confirmed population-based cohort. Referred patients to the CLL-specialized clinic were identified from the CCMB charts. Association between age and treatment was measured by chi-squared test. Hazard ratio (HR) was determined using Cox Proportional Hazard Regression model. Of 555 CLL/SLL diagnoses, 281 (51%) were referred to the CLL-specialized clinic. For referred and non-referred patients the median age was 68y (39-99) and 72y (45-96), treated patients were 77 (27%) and 31 (11%), time to first treatment was 5m (0-5.5y) and 3m (0-2.5y), respectively. M:F was 1.7:1 for both groups. CLL was the primary cause of death in both referred and non-referred patients (57% and 35%, respectively). Comorbidities such as cardiovascular diseases had equal contributions to mortality in both populations (7% and 9.5% in referred and non-referred patients, respectively). When patients older than 70 years were investigated, elderly patients that were referred to the clinic were more likely to receive treatment (p = 0.0002). When adjusted for age (≥80y HR 10.79, p: >0.0001; 71-79y HR 5.44, p: 0.0007; 62-70y HR 4.07, p: 0.0051; <62 HR 1.00), gender (male HR 1.61, p: 0.0414), pre-CLL cancer (HR 1.85, p: 0.0187) and post-CLL Cancer (HR 2.31 p: 0.0208), patients seen by CLL-specialists had a >2-fold increased OS compared to non-referred patients (HR 2.39, p: 0.0003) in the Manitoba population. In the non-referred population, there was a striking correlation between advancing age and decreasing OS. This correlation was almost eliminated in the referred population. Thus, patients seen in a specialized clinic have an improved survival compared to non-referred patients and this appears to be primarily related to improved OS in the elderly. Whether this observation is related to improved therapy/supportive care in the specialized clinic or to referral bias is under investigation. Citation Format: Sara Beiggi, Versha Banerji, Angela Deneka, Jane Griffith, Spencer Gibson, James Johnston. Comparison of overall survival of Chronic Lymphocytic Leukemia (CLL) patients referred or not referred to a specialized CLL clinic: A Canadian population-based study. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4136. doi:10.1158/1538-7445.AM2014-4136

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 score0.050
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.175
GPT teacher head0.469
Teacher spread0.293 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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