Estimating the Burden of Illness of Relapsed Follicular Lymphoma and Marginal Zone Lymphoma in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Many patients with advanced follicular lymphoma (FL) and marginal zone lymphoma (MZL) relapse after first-line chemotherapy. OBJECTIVE: To examine healthcare resource utilization (HCRU) and cost, treatment patterns, progression, and survival of patients with FL and MZL who relapse after first-line treatment, in Ontario, Canada. METHODS: A retrospective, administrative data study identified patients with relapsed FL and MZL (1 January 2005-31 December 2018). Patients were followed for up to three years post relapse to assess HCRU, healthcare costs, time to next treatment (TTNT), and overall survival (OS), stratified by first- and second-line treatment. RESULTS: The study identified 285 FL and 68 MZL cases who relapsed after first-line treatment. Average duration of first-line treatment was 12.4 and 13.4 months for FL and MZL patients, respectively. Drug (35.9%) and cancer clinic costs (28.1%) were major contributors to higher costs in year 1. Three-year OS was 83.9% after FL and 74.2% after MZL relapse. No statistically significant differences were observed in TTNT and OS between patients with FL who received R-CHOP/R-CVP/BR in the first line only versus both the first- and second- line. A total of 31% of FL and 34% of MZL patients progressed to third-line treatment within three years of initial relapse. CONCLUSION: Relapsing and remitting nature of FL and MZL in a subset of patients results in substantial burden to patients and the healthcare system.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".