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P5-20-04: Is Primary Prophylaxis with G-CSF Indicated for Adjuvant TC or FEC-D Chemotherapy? A Systematic Review and Meta-Analyses.

2011· review· en· W2334715558 on OpenAlexaff
T. Younis, Daniel Rayson, K. Thompson

Bibliographic record

VenueCancer Research · 2011
Typereview
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineEpirubicinDocetaxelFebrile neutropeniaInternal medicineCyclophosphamideNeutropeniaClinical trialOdds ratioMeta-analysisAdjuvantChemotherapyOncologyGastroenterologySurgery

Abstract

fetched live from OpenAlex

Abstract Background Adjuvant chemotherapeutic regimens incorporating docetaxel, including TC (taxotere 75 mg/m2; cyclophosphamide 600 mg/m2 q 3 weekly for 4 cycles) and FEC-D (5-flurouracil 500 mg/m2; epirubicin 100 mg/m2; cyclophosphamide 500 mg/m2 q 3 weekly for 3 cycles followed by docetaxel 100 mg/m2 q 3 weekly for 3 cycles), appear to be associated with rates of febrile neutropenia (FN) in routine clinical practice that are higher than those reported in the pivotal clinical trials (7-33% vs. 11% & 18–35% vs. 5%, respectively). Although primary prophylaxis with G-CSF (granulocyte colony-stimulating factor) is indicated for chemotherapeutic regimens associated with rates of FN > 20%, the variable FN rates reported with TC and FEC-D outside of clinical trials have precluded definitive recommendations for G-CSF primary prophylaxis in most jurisdictions. A systematic review and meta-analysis was therefore conducted to assess; i) FN rates associated with TC and FEC-D without and with G-CSF primary prophylaxis outside of clinical trial settings, and ii) the potential impact of G-CSF prophylaxis on FN prevention. Methods: A PubMed search was conducted and major conference abstracts were reviewed up to June 15th 2011 to identify all English language reports of FN rates associated with adjuvant TC or FEC-D outside of clinical trial settings. FN rates with and/or without G-CSF prophylaxis were abstracted, and LOS (length of stay in hospital) and mortality following FN were noted. Summary incidences and odds ratios (OR) with 95% confidence intervals (95%CI) were calculated using random- and fixed-effects models. Results: A total of 902 patients treated with TC (average age 55 years, range 27–84, 19% ≥ 65 years) and 1342 treated with FEC-D (average age 52 years, range 24–78, 9% ≥ 65 years) from 13 and 9 relevant studies respectively, were included. Overall FN rates of 17% (range: 7–33%) and 24% (range: 18–35%) were reported for TC and FEC-D, with an average primary G-CSF utilization rate of 47% and 30%, respectively. For TC, the pooled random-effects meta-analysis estimates of FN rates were 7% (95%CI: 5–10%) with primary G-CSF and 29% (95%CI: 24–35%) without G-CSF (OR=0.17, 95%CI: 0.09−0.33). For FEC-D, the FN rates were 9% (95%CI: 4–19%) with and 31% (95%CI: 27–35%) without primary prophylaxis (OR=0.22, 95%CI: 0.09−0.56). For FEC-D, 50% of the FN events occurred during the 1st D cycle and 65% overall occurred during D treatments. Older age (≥ 65 years) did not appear to correlate with higher FN rates. Breakthrough FN occurred in 5% across both regimens despite G-CSF secondary prophylaxis. FN was associated with 3.7 and 4.0 LOS days and 0% and 2% mortality during TC and FEC-D, respectively. Conclusions: TC and FEC-D without G-CSF are associated with unacceptably high FN rates in routine clinical practice. Primary prophylaxis with G-CSF should be considered for adjuvant TC chemotherapy, and for the D-component of FEC-D regimen, irrespective of patient age. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-20-04.

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)0.010
metaresearch head score (Gemma)0.030
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.028
Bibliometrics0.0060.007
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.475
GPT teacher head0.536
Teacher spread0.062 · 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
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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