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Abstract P1-13-08: A prospective non-randomized clinical trial of adjuvant carboplatin chemotherapy in triple negative breast cancer

2019· article· en· W2920021859 on OpenAlexaff
C Hamm, Swati Kulkarni, Ruchi Gupta, John D. Mathews, Khalid Amin, Ahmed Hussein, Lucy Porter

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCarboplatinMedicineRegimenInternal medicineOncologyTriple-negative breast cancerTaxaneBreast cancerDocetaxelChemotherapyAnthracyclineCancerCisplatin

Abstract

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Abstract Background: The addition of carboplatin in the neoadjuvant setting has demonstrated improved outcomes in patients with triple negative breast cancer (TNBC). Carboplatin in the adjuvant setting has not been demonstrated to be an accepted regimen to date. This trial addresses this issue. Methods: The primary objectives of this study were to assess the toxicity of an adjuvant carboplatin-containing regimen for early stage TNBC patients, and to correlate outcomes with molecular markers including Spy-1. Secondary objectives included determination of progression free (PFS) and overall survival (OS), and comparing these to our institutional historical controls. Patients received the backbone of a dose dense anthracycline, taxane, cyclophosphamide (DD ACT), with the addition of carboplatin. Results: Ninety patients with stage I to III patients with triple negative breast cancer were accrued to this trial between Jan 2011 and June 2017. We discovered that DD ACT with carboplatin with an AUC of 5 given on the second and last paclitaxel was well tolerated. Chemotherapy delays were minimized when the parameters for administration of the carboplatin was to allow chemotherapy to proceed if the platelet count was >/= 70,000 x10^9/L and dose adjustment of paclitaxel was allowed based on neuropathy. There were no grade 4 adverse events. 4% of patients had grade 3 peripheral neuropathy (PN), 28% had grade 2 PN and 45% had grade 1 PN. Results of molecular profiles will be reported. Univariate analysis are reported, and were found to be very promising. Using log-rank statistic, a trend to improvement in overall survival was found when compared to historical controls (p=0.089). Median follow-up is 24 months. Longer follow-up is necessary to determine PFS and overall survival benefit. Conclusion: If considering an adjuvant regimen for triple negative breast cancer patients DDAC/TC with the carboplatin administered with an AUC of 5 on the second and fourth taxol of DDACT is a well-tolerated regimen. Univariate Analysis Comparing Carboplatin vs Historical Controls that did not receive CarboplatinVariableHistorical (no carbo)Carbo containing chemop overall n = 179n = 82 Age56.3 (13.1)49.8 (11.0)< 0.001Stage0.188Stage I47 (26.3%)15 (18.3%) Stage II88 (49.2%)50 (61.0%) Stage III44 (24.6%)17 (20.7%) Grade0.011Grade 18 (4.5%)0 (0.0%) Grade 233 (18.4%)7 (8.8%) Grade 3138 (77.1%)73 (91.2%) Remission Status0.009In Remission126 (70.4%)70 (86.4%) Relapsed53 (29.6%)11 (13.6%) Survival< 0.001Alive121 (67.6%)73 (90.1%) Deceased58 (32.4%)8 (9.9%) Citation Format: Hamm C, Kulkarni S, Gupta R, Mathews J, Amin K, Hussein A, Porter L. A prospective non-randomized clinical trial of adjuvant carboplatin chemotherapy in triple negative breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-13-08.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.086
GPT teacher head0.503
Teacher spread0.417 · 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 designNon-randomized trial
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
Published2019
Admission routes1
Has abstractyes

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