Immunosuppressive Treatment for Patients with Myelodysplastic Syndromes: A Review of 358 Patients
Bibliographic record
Abstract
Abstract Abstract 1717 Scientific and clinical evidence support a role for immune dysregulation in the pathogenesis of myelodysplastic syndromes (MDS) in some patients, and immunosuppressive therapy (IST) is considered a standard treatment for selected patients with MDS. Despite a number of studies showing its efficacy in MDS, IST has not been widely adopted because of uncertainty about therapeutic benefit, perceived toxicities of antibody treatment, and confusion about patient selection. To better define the place of IST in MDS, we reviewed all published clinical trials of IST for adult patients with MDS to determine its therapeutic benefit and treatment-related toxicity. We also sought to define clinical and laboratory predictors for response to IST. IST was defined as T cell directed therapies, including the following drugs administered alone or in combination: cyclosporine A (CsA), rabbit or horse anti-thymocyte globulin (ATG), alemtuzumab, sirolimus, tacrolimus, mycophenolate mofetil, or daclizumab. Electronic databases were scanned for all peer-reviewed clinical trial reports concerning IST for MDS from inception through August 1, 2011. Risk of bias for each study was assessed by two independent investigators using the Cochrane Risk of Bias Tool, and the Newcastle-Ottawa Scale. The searches of MEDLINE, Cochrane Clinical Trials Register, SCOPUS, Web of Science and EMBASE yielded a total of 1950 articles, and 1937 were subsequently discarded based on our a priori exclusion criteria. A total of 13 reports from 13 individual clinical trials enrolling 358 patients met criteria for this review. IST was well tolerated with a treatment-related mortality rate of 1.3%. Hematologic improvements (HI), partial response (PR), and complete response (CR) was defined using International Working Group for MDS criteria. The overall response rate (ORR) to IST was 41% (HI 18%, PR 15%, and CR 8%). ORR according to treatment regimen were alemtuzumab 68% (n= 31 patients), CsA 56% (n=111 patients), h-ATG 35%, (n=83 patients), r-ATG/CsA 30% (n= 20 patients), r-ATG 27%, (n=15 patients), and h-ATG/CSA 25% (n=79 patients). Response rates were higher when patients were treated on protocols incorporating specific selection criteria versus unselected patients (ORR 59% vs 41%, p=0.01). Patients with a hypocellular bone marrow had response rates that were equal to individuals with normal or increased marrow cellularity: ORR 63% vs 63%, (p=0.99); PR 25% vs 23%, (p=0.81); CR 15% vs 11%, (p=0.46). Patients younger than 60 years had significantly higher response rates to IST than older individuals (ORR 59% vs 40%, p=0.004), irrespective of the treatment regimen administered. Patients who were transfusion dependent had response rates equal to those who were transfusion independent at the time of treatment (ORR 60% vs 55%, p=0.57). Response rates in patients with low and intermediate cytogenetic risk groups as defined by the International Prognostic Scoring Scale (IPSS) were 51% and 49%, respectively. Response rates varied according to World Health Organization (WHO) Prognostic Scoring Scale (WPSS) morphology categories, with overall response rates of 57% (n=128 patients), 10% (n=10 patients), and 21% (n=39 patients) in individuals with very low, low, and intermediate morphology categories, respectively. Response rates did not vary according to gender or cell lineages involved. These results indicate that the choice of IST may be critical in optimizing responses and that IST should be considered for MDS patients younger than 60 years old, with low and intermediate risk IPSS cytogenetics and very low WHO morphology categories, regardless of bone marrow cellularity and duration of transfusion dependence. CsA Alemtuzumab hATG hATG/CsA rATG rATG/CsA Sirolimus ANOVA Response R% (range) No. R% (range) No. R% (range) No. R% (range) No. R% (range) No. R% (range) No. R% (range) No. P-value CR 3 3/111 23 7/31 5 4/83 10 8/79 20 3/15 15 3/20 0 0/19 0.002 (1–8) (10–41) (1–12) (5–19) (4–48) (3–38) — PR 24 27/111 13 4/31 16 13/83 4 3/79 7 1/15 15 3/20 16 3/19 0.013 (17–33) (4–30) (9–25) (1–11) (0.1–32) (3–38) (3–40) HI 29 32/111 32 10/31 15 12/83 11 9/79 0 0/15 0 0/20 0 0/19 <0.0001 (21–38) (17–51) (8–24) (5–21) — — — ORR 56 62/111 68 21/31 35 29/83 25 20/79 27 4/15 30 6/20 16 3/19 <0.00001 (46–65) (49–83) (25–46) (16–36) (8–55) (12–54) (3–40) 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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".