Alemtuzumab Added to CHOP for Treatment of Peripheral T-Cell Lymphoma (PTCL) in Previously Untreated Young and Elderly Patients: Pooled Analysis of the International ACT-1/2 Phase III Trials
Bibliographic record
Abstract
Abstract Background: Standard treatment in PTCL pts is unsatisfactory due to a high rate of early progression. Alemtuzumab (A), a monoclonal anti CD52 antibody, has demonstrated efficacy in relapsed PTCL pts. The results of the final analyses of the ACT-1 phase III and the ACT-2 phase III trial, comparing standard CHOP to A-CHOP showed higher response rates, but did not yield significant differences in EFS, PFS and OS in both previously untreated young and elderly patients, but the planned sample sizes could not be reached due to low recruitment. We undertook a planned pooled analysis of both ACT trials comparing CHOP with A-CHOP to increase statistical power. Patients and Methods: Between 2007 and 2013, 252 pts from Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Norway, Poland, Portugal, Sweden and The Netherlands were randomized to receive either 6 cycles CHOP or A-CHOP at 14 day intervals. The planned pooled analysis was performed to compare patient outcome adding A to CHOP with patients treated with CHOP alone. Primary endpoint within ACT-1 and ACT-2 trial was the 3 years event free survival (EFS), secondary endpoints were progression free survival (PFS) and overall survival (OS). EFS is defined as the time from randomization to disease progression, start of salvage treatment, additional (unplanned) treatments, relapse, or death of any cause. Results: 252 pts were randomized (ACT-1: 136; ACT-2: 116). Five patients received no study treatment; therefore, 247 pts were analyzed (CHOP: 124; A-CHOP: 123). Median age was 61 years. 62% were male. Histologies were 33% AITL, 34% PTCL NOS, 33% other subtypes. In the pooled data set, the two treatment groups were comparable. Infections grade ≥3 occurred more often in patients treated with Alemtuzumab (A-CHOP: 55% [95% CI: 45% - 64%] vs. CHOP 23% [16% - 32%]; p<0.001). Complete remissions were achieved in 56% [47% - 65%] of A-CHOP and 43% [34% - 52%] of CHOP pts (p=0.036). However, EFS (A-CHOP at 3 yrs: 32% [23% - 40%] vs. CHOP 25% [17% - 33%]; p=0.159), PFS (33% [25% - 42%] vs. 27% [19% - 35%]; p=0.220) and OS (46% [37% - 55%] vs. 53% [44% - 62%]; p=0.332) showed no significant differences. Multivariate analyses, adjusted for IPI factors, bulky disease and gender, confirmed these results (hazard ratio HREFS: 0.8 ([95% CI: 0.6 - 1.1]; p=0.196), HRPFS: 0.8 ([95% CI: 0.6 - 1.1]; p=0.246), HROS: 1.2 ([95% CI: 0.8 - 1.6]; p=0.370). Male gender (HR 2.5), ECOG > 1 (HR 2.1) and bulky disease (HR 2.1) were the most prominent unfavorable risk factors for EFS. With the sample size of 247 pts the power for detecting the planned EFS difference of 15% was 74%. Conclusion: Adding Alemtuzumab to CHOP increased the rate of CR in PTCL patients, albeit at the costs of higher treatment related toxicity. Addition of Alemtuzumab did not improve EFS, PFS, or OS. Female gender is associated with a significantly better prognosis. This is the largest prospective dataset collected for PTCL. Supported by Federal Ministry of Research BMBF FKZ 01KG0705 and unrestricted research grants by Genzyme-Sanofi and AMGEN Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".