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Differences in Outcomes in Males and Females with Diffuse Large B-Cell Lymphoma with Induction Rituximab and Follicular Lymphoma Treated with Maintenance Rituximab

2012· article· en· W2980279621 on OpenAlexaff
Thomas M. Habermann, Fangxin Hong, Vicki A. Morrison, Shaker R. Dakhil, James K. Weick, Stanley R. Frankel, Randy D. Gascoyne, Richard I. Fisher, Bruce D. Cheson, Edie Weller, Brad S. Kahl, B. A. Peterson, Howard S. Höchster, Sandra J. Horning

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsRituximabMedicineFollicular lymphomaVincristineCHOPPrednisoneInternal medicineDiffuse large B-cell lymphomaProportional hazards modelLymphomaCyclophosphamideRandomizationOncologyRandomized controlled trialChemotherapy

Abstract

fetched live from OpenAlex

Abstract Abstract 3705 Improved outcomes were reported in USA studies in DLBCL (Habermann et al. J Clin Oncol 2006) in a two-staged randomized study of R-CHOP (rituximab, cyclophosphamide, Adriamycin, vincristine, and prednisone) versus CHOP with a second randomization assignment to maintenance rituximab (MR) or observation (OBS) (E4494) and in follicular lymphoma (FL) in patients in a trial with CVP (cyclophosphamide, vincristine, and prednisone) followed by randomization to MR versus OBS in advanced-stage indolent lymphoma (E1496) (Hochster et al. J Clin Oncol 2009). The details of the treatment regimens have been previously described. The German High Grade Lymphoma Study Group has reported differences between men and women in outcomes in DLBCL with improved outcomes in women treated with rituximab (Müller et al. Blood 2012). Methods: Survival outcomes by sex were analyzed using a stratified weighted cox regression, removing the effect of maintenance rituximab in DLBCL (E4494), and a log-rank test in patients with follicular histology (E1496). A Cox regression model was used to evaluate the differences between males and females together with weight (below or above the median). Wilcoxon test and Fisher's exact test were used to compare medians and proportions, respectively. Results: In DLBCL, there were 273 eligible males and 273 females. The median age was 69 in males and 70 in females. There were no differences in baseline patient characteristics among the male and female populations. 138 males and 129 females were treated with R-CHOP. There was no difference in treatment received, with 83% females and 75.3% males receiving 6 cycles or more of R-CHOP treatment (p=0.14). The complete remission (CR) and partial remission (PR) rates after RCHOP were higher in females (82.6%) versus males (71.5%) (P = 0.04). With a median follow-up of 9.45 years, the failure free survival (FFS) and overall survival (OS) were improved in females (P = 0.02, 0.002; HR=0.63, 0.54) compared with males in the R-CHOP group. The outcomes were not different in the CHOP group for FFS (P = 0.81) or OS (P= 0.57) between males and females. Within the R-CHOP group, the failure free survival (FFS) was significantly different between women and men (P = 0.002) and body weight (P = 0.03), but only female sex (P = 0.001) was significant and not weight (P = 0.26) for OS. Of 282 evaluable patients with advanced-stage follicular lymphoma who received initial treatment with CVP, 115 patients were randomly assigned to MR and 113 to OBS. 120 patients were male, and 108 were female. The median age was 58 years in the MR arm and 54 years in the OBS arm. At a median follow-up of 8.04 years, MR markedly improved the PFS (P=0.003) compared with OBS. There were no differences in PFS (P= 0.17) between males and females treated with MR or OS (P = 0.27). In conclusion, in induction therapy with rituximab in DLBCL there is a sex dependent effect with rituximab with males benefiting less than females. In contrast, in patients with follicular lymphoma treated with chemotherapy followed by maintenance rituximab, there were no differences. The differences in outcomes in patients of different sex with DLBCL treated with immunochemotherapy and FL treated with maintenance rituximab will require further analysis of multiple clinical and biologic variables. Disclosures: Fisher: Roche: Advisory Board Other. Cheson:Genentech: Consultancy. Kahl:Genentech, Roche: Consultancy, Research Funding. Horning:Genetech, Roche: Employment, stock (Roche) Other.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.221
Teacher spread0.208 · 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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Citations3
Published2012
Admission routes1
Has abstractyes

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