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Record W2564860930 · doi:10.1158/1538-7445.am2015-4525

Abstract 4525: The impact of chemoimmunotherapy dose intensity in diffuse large b-cell lymphoma

2015· article· en· W2564860930 on OpenAlexaff
Michael P. Chu, Sunita Ghosh, Andrew Belch, Neil Chua, Amélie Fontaine, Randeep Sangha, Robert Turner, Christopher P. Venner, Vickie E. Baracos, Michael B. Sawyer

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsAlberta Cancer Foundation
Fundersnot available
KeywordsMedicineChemoimmunotherapyInternational Prognostic IndexCyclophosphamideVincristineInternal medicineDiffuse large B-cell lymphomaRituximabCHOPChemotherapyOncologyDoxorubicinLymphomaEtoposideGastroenterology

Abstract

fetched live from OpenAlex

Abstract Introduction Chemotherapy dose intensity (DI) impacts outcomes across tumor subtypes. In diffuse large B-cell lymphoma (DLBCL), DI played a large role prior to rituximab, but is still a subject of investigation. Research into intensifying treatment for poorer prognostic lymphoma subtypes has yielded dose-adjusted EPOCH-R where etoposide is added to standard R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone). Though, R-CHOP given every 14 vs. 21 days has not been found to improve survival, this study examines if delays in treatment or reductions in R-CHOP21 DI impact patient outcomes. Methods In this single institution review, DLBCL patients (pts) treated with first-line R-CHOP between 2004 and 2010 were included. After factoring in covariates such as revised International Prognostic Index (R-IPI) and gender, pts were compared by DI (ratio of actual total dose received vs. prescribed dose) of cyclophosphamide, doxorubicin, and treatment duration as a whole for their impact on progression-free (PFS) and overall survival (OS). Results Of 232 pts identified, 224 were included in final review. Median age and ECOG performance status was 62 years and 1, respectively. Majority had stage IV disease (46%). 124 patients were male with pts evenly distributed between R-IPI 0-1 (low, 28%), 2 (low-intermediate, 21%), 3 (high-intermediate, 26%), and 4-5 (high, 25%). A median DI of both cyclophosphamide and doxorubicin was 97%. 118 pts had >/ = 1 week delay during treatment duration. Cutpoint analysis found that DI was more important at 85% for both cyclophosphamide and doxorubicin. Median PFS for patients who received / = 85% cyclophosphamide DI was 27.2 vs. 55.0 months (hazard ratio [HR] 2.48, p = 0.03). Similarly, median OS was 41.8 months vs. not reached (HR 2.79 p = 0.02), respectively. PFS and OS for doxorubicin was similar at 27.6 vs. 53.7 months (HR 2.25, p = 0.04) and 40.9 months vs. not reached (HR 2.54, p = 0.02), respectively. Actual treatment durations that differed <15% of the planned durations were protective for PFS (HR 0.44, p = 0.008), but less so for OS (HR 0.63, p = 0.18). Taking R-IPI scores and gender in multivariate Cox proportional hazards modeling found the impact of cyclophosphamide and doxorubicin DI on PFS and OS maintained significance but not treatment duration. Though multiple reasons for reduced DI exist, growth factor support use trended towards higher DI pts (32 vs. 19%, p = 0.10). Conclusions While intensifying R-CHOP by shortening cycles to every 14 days has not been beneficial, this study suggests that delays and dose reductions in R-CHOP21 substantially impact outcomes. In doing so, it highlights that maintaining pts on schedule is important and that more accurate methods of determining appropriate chemotherapeutic doses may affect both survival and toxicity. Although it is our standard to only use growth factor support with delays it may be beneficial to starting all patients up front on growth factor support. Citation Format: Michael P. Chu, Sunita Ghosh, Andrew Belch, Neil S. Chua, Amelie Fontaine, Randeep Sangha, Robert Turner, Christopher Venner, Vickie Baracos, Michael B. Sawyer. The impact of chemoimmunotherapy dose intensity in diffuse large b-cell lymphoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4525. doi:10.1158/1538-7445.AM2015-4525

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.435
Teacher spread0.327 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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