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Diagnostic Delays and Survival for Medicare Patients with Chronic Myeloid Leukemia in the Pre-Imatinib Era.

2009· article· en· W2556435626 on OpenAlexaff
Christopher R. Friese, Lysa S. Magazu, Bridget A. Neville, Lisa C. Richardson, Craig C. Earle, Gregory A. Abel

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsInstitute for Clinical Evaluative SciencesCancer Care Ontario
Fundersnot available
KeywordsMedicineImatinibMedical diagnosisImatinib mesylateEpidemiologyInternal medicineProportional hazards modelSurveillance, Epidemiology, and End ResultsPediatricsCancer registryMyeloid leukemiaPathology

Abstract

fetched live from OpenAlex

Abstract Abstract 1369 Poster Board I-391 Background: Timeliness of diagnosis is a quality of care measure endorsed by the Institute of Medicine. Clinical outcomes for patients with chronic myelogenous leukemia (CML) are better when tyrosine kinase inhibitors, such as imatinib, are initiated in the early stages of disease. However, the patterns of care surrounding the CML diagnosis period, as well as the relationship between diagnosis delay and overall survival in the pre-imatinib era, are unknown. Methods: The Surveillance, Epidemiology and End Results (SEER)-Medicare linked database was used to identify traditional Medicare enrollees diagnosed with CML during 1991 through May 2001 (prior to the FDA approval of imatinib). Both inpatient and outpatient claims were analyzed from one year before, through six months following, the SEER diagnosis date. Signs, symptoms, and diagnostic studies commonly encountered in CML diagnoses were identified by CPT procedure and ICD-9 diagnosis and procedure codes. We calculated the time between the first visit for a sign or symptom and the SEER diagnosis date, and defined this time period as ‘diagnostic delay’ if it met or exceeded the median number of days for the sample. An accelerated failure time model examined variables associated with diagnostic delay. Overall survival was examined using a Cox proportional hazards model. Analyses were adjusted to account for a possible lag time in SEER cancer diagnosis dates, as well as year of diagnosis. Results: We studied 768 patients who met eligibility criteria. The most frequent signs and symptoms prior to CML diagnosis were infection (29.4%), anemia (22.4%), leukocytosis (13.4%) and fatigue (11.9%). The median time between any sign or symptom and CML diagnosis date in SEER was 90 days (interquartile range = 270). The median survival time was 3.5 years. The time between sign or symptom and CML diagnosis was increased for patients with at least one comorbidity (β=0.83, p < .001), and for those diagnosed at age 75 or greater (β=0.30, p < .05). Males had shortened times to diagnosis (β=-0.41, p < .01). Diagnostic delay was not a significant predictor of overall survival (HR = 1.04, 95% CI = 0.88-1.23). Conclusions: The most common signs and symptoms older patients experience prior to CML diagnosis are nonspecific, which may impair diagnostic efforts. Prior to the approval and general availability of imatinib, differences in timeliness of diagnosis were observed by age, gender, and presence of comorbidities. Examination of patient-provider interactions stratified by these variables may aid efforts to standardize the diagnostic process, although diagnostic delay was not significantly associated with overall survival in the pre-imatinib era. Disclosures: No relevant conflicts of interest to declare.

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)0.004
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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
Published2009
Admission routes1
Has abstractyes

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