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An exploratory comparative effectiveness analysis of febrile neutropenia incidence among patients with cancer receiving granulocyte colony stimulating factors.

2022· article· en· W4298147379 on OpenAlexaff
Pamala A. Pawloski, Catherine M. Lockhart, Gabriela Vazquez‐Benitez, Terese A. DeFor, Aaron B. Mendelsohn, James Marshall, Érick Moyneur, Cara L. McDermott

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsPegfilgrastimFilgrastimMedicineFebrile neutropeniaInternal medicineOncologyNeutropeniaChemotherapy

Abstract

fetched live from OpenAlex

408 Background: We conducted an exploratory comparative effectiveness analysis comparing various G-CSF (pegfilgrastim/filgrastim) products to each other in incidence of febrile neutropenia (FN) among patients with breast, lung, colon, pancreatic, ovarian cancers or non-Hodgkin’s lymphoma (NHL) in the Biologics and Biosimilars Collective Intelligence Consortium’s (BBCIC) Distributed Research Network. Methods: We included patients aged > = 20 years who, in 2015-2019, per insurance claims, received any pegfilgrastim or filgrastim products as febrile neutropenia (FN) prophylaxis during the first cycle of chemotherapy posing a high or intermediate FN risk per National Comprehensive Cancer Network guidelines. We compared the FN risk starting at day 5 following day 1 of chemotherapy receipt between products using Poisson regression model with standardized inverse probability weights and robust variance to estimate the Relative Risk (RR) and 95% Confidence intervals (CI). Results: A total of 15,941 patients received a pegfilgrastim product in cycle 1 of chemotherapy: 15,115 (95%) pegfilgrastim, 484 (3%) pegfilgrastim_cbqv, 342 (2%) pegfilgrastim_jmdb. 565 patients received a filgrastim product: 284 (50%) filgrastim, 201 (36%) filgrastim_sndz, 80 (14%) tbo-filgrastim. FN events by product were: 346 pegfilgrastim (2.3% of users), 11 pegfilgrastim_cbqv (2.3%), 8 pegfilgrastim_jmdb (2.3%), 13 filgrastim (4.6%), 5 filgrastim_sndz (2.5%), 2 tbo-filgrastim (2.5%). We found no difference in FN incidence when comparing pegfilgrastim_cbqv to pegfilgrastim (RR 0.83, 95% CI 0.41-1.69), pegfilgrastim_jmdb to pegfilgrastim (RR 1.03, 95% CI 0.56-1.92), and pegfilgrastim_jmdb to pegfilgrastim_cbqv (RR 1.11, 95% CI 0.45-2.74). Similarly, we found no difference in FN incidence when comparing filgrastim_sndz to filgrastim (RR 0.46, 95% CI 0.17-1.28), tbo-filgrastim to filgrastim (RR = 0.30, 95% CI 0.06-1.36), or tbo-filgrastim to filgrastim_sndz (RR 0.54, 95% CI 0.10-2.77). Adverse events were rare, with similar rates observed among all products. Conclusions: We observed no significant difference in FN incidence among patients when comparing various G-CSF products, including when biosimilars were compared to their reference counterparts.

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)0.029
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.009
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.106
GPT teacher head0.461
Teacher spread0.354 · 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 designMeta-analysis
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
Published2022
Admission routes1
Has abstractyes

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