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Time to Diagnosis and Treatment of Lymphoma: A Canadian Population Based Study

2015· article· en· W2979936924 on OpenAlexaffabout
Pamela Skrabek, Oliver Bucher, Matthew D. Seftel, Donna Turner

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsCancerCare Manitoba
Fundersnot available
KeywordsMedicineCancer registryPopulationCancerLymphomaNot Otherwise SpecifiedPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction: Prompt diagnosis and treatment are key requirements to improving cancer patients' survival and quality of life. This is particularly relevant in diseases such as the aggressive lymphomas, which are potentially curable with appropriate therapy. The province of Manitoba (MB), Canada, has set a goal of reducing time from suspicion of any cancer to treatment to sixty days. Objectives: To establish a provincial baseline this study examined time intervals in lymphoma patients' journey from high suspicion (HS) to diagnosis date (dx_dt) and treatment (tx). The aims were to determine the portion of patients achieving the goal of sixty days and compare this to other major cancers (Breast, Colorectal and Lung). The effect of place of residence at diagnosis, gender, age and lymphoma subtype on delays were also of interest. Methods: Patients with a first diagnosis of any type of lymphoma between 01/2010 to 12/2013 were identified from the Manitoba Cancer Registry (MCR). Those with a prior cancer diagnosis, diagnosed by autopsy or death certificate only, or incomplete/pending MCR registration were excluded. We accessed provincial health insurance billing claims and hospital registration databases in the year prior to dx_dt. Working backwards from dx to determine the HS point, an algorithm was built using an iterative consultative process referencing chart reviews as a framework for milestones in the patient pathway. The index event for high suspicion (HS) was defined as the first event including: imaging ranked likely related to subsequent lymphoma diagnosis, diagnostic procedure/biopsy, or specialist consultation. Using this index event, the claims data were searched for a referring provider, the last visit with this provider was defined as the date of HS. The influence of lymphoma subtype was explored by examining intervals in patients with Diffuse large B-cell Lymphoma (DLBCL) and classical Hodgkin Lymphoma (HL). Results: The entire cohort included a total of 1182 patients with 338 DLBCL (36.2%), 96 HL (10.3%) and 53.5% other types of lymphoma. The index event for HS was imaging in 477 (51.1%), specialist consult in 92 (9.9%), diagnostic procedure/biopsy in 42 (4.5%), ER visit in 24 (2.6%) and multiple index events in 274 (29.3%). HS-tx was less than sixty days in only 14.8% of patients. 31.3% of patients did not receive any treatment. In patients who received chemotherapy at diagnosis (n=682) HS-tx was less than sixty days in 22.3%. A parallel analysis for Breast, Colorectal and Lung cancers revealed that 29%, 33% and 38% met the target of HS-tx in less than sixty days at baseline. HS-tx was less than sixty days in 84 patients with DLBCL (24.9%) and 25 with HL (26%), p=0.06. Conclusion: In this population based Canadian study, the proportion of lymphoma patients who meet the target for timely commencement of systemic therapy is low, even more than other major solid tumors. There is no difference between the proportion of HL and DLBCL patients meeting this target, which is in contrast to previously published literature that suggests longer delays in HL. In patients treated with chemotherapy a large portion of the delay appears to be after diagnostic biopsy (dx_dt). As part of this initiative clinical advisors have developed a lymphoma pathway with target timelines for milestones which will serve as a reference tool. This study describes the methodology that can be adopted in other jurisdictions treating lymphoma, and also serves as a baseline from which to direct process improvement. 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)0.003
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 score0.030
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.007
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.075
GPT teacher head0.315
Teacher spread0.241 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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