Cytogenetic Risk Features in MDS-Update and Present State.
Bibliographic record
Abstract
Abstract Abstract 2772 Poster Board II-748 Introduction: The IPSS-Score, published by Greenberg et al. (1997), defines the gold standard in risk stratification of patients with MDS. Since its implementation in 1997 based on 816 patients with primary MDS, the knowledge concerning the prognostic impact of distinct abnormalities increased extensively. The present study proposes a new and comprehensive cytogenetic scoring system based on an international data collection of 3803 patients, originating from the German-Austrian (GA)-, the International Risk analysis workshop (IMRAW)- and the Spanish Cytogenetics working group (GCECGH). Additionally, 53 cases of rare abnormalities were contributed by the International Cytogenetics Working Group of the MDS Foundation (ICWG), resulting in total number of 3856 pts. As compared to our previous reports, the data set was substantially enlarged by adding the GCECGH cases and data quality was improved by updating the clinical and survival data; allowing the analysis of the prognostic impact for isolated abnormalities exclusively to assure a maximum accurateness. Furthermore, multivariate analysis was refined by including peripheral cytopenias. Materials and Methods: Inclusion criteria were defined as follows: Primary MDS, age >=16, and bone marrow blasts <=30%. Regarding therapy, exclusively patients with primary MDS and supportive care, only allowing short courses of oral chemotherapy or hemopoietic growth factors were included. Based on these criteria, 958 pts. were excluded resulting in 2901 pts. available for final analysis. Univariate and multivariate analysis concerning overall survival (OS) and 25% AML-transformation (AML-t) was performed. In multivariate analysis, age, gender, bone marrow blast count and number of peripheral cytopenias were defined as co-variables. OS and AML-t in distinct cytogenetic abnormalities was only calculated when the abnormality occurred as an isolated aberration with a minimal frequency of n=10. Median observation time was 19.0 months. Clinical follow-up was performed until April 2009. Results: In total, 20 cytogenetic subgroups matching the inclusion criteria were detected. Abnormalities were grouped as normal (n=1522, 52.5% of all cases), single (1 abnormality), double (2 abnormalities) or complex (>=3 abnormalities). Single abnormalities found were: del(5q) (176, 6.1%); -7/7q- (59, 2.0%); +8 (130, 4.5%); del(20q) (48, 1.7%), -Y (46, 2.1%); der(1;7)(q10;p10)/t(1;7)(var;var) (10, 0.3%); der(3)(q21)/der(3)(q26) (10, 0.3%); del(11q) (19, 0.7%); del(12p) (17, 0.6%); i(17)(q10) (11, 0.4%); +19 (10, 0.3%), +21 (10, 0.3%) and any other single (150, 5.2%). Double abnormalities were stratified into 3 subgroups: double including del(5q) (45, 1.6%); double including -7/7q- (31; 1.1%) and any other double (98, 3.4%). As reported (Haase et al. Blood 2008), complex karyotypes were sub-divided into 2 groups: Karyotypes with 3 abnormalities (59, 2.0%) vs. >3 abnormalities (188, 6.5%). Finally, 20 pts. (0.7%) displayed cytogenetically unrelated clones. According to OS and AML-t, abnormalities were classified to 4 prognostic subgroups: good (normal, del(5q), double incl. del(5q), der(1;7)(q10;p10)/t(1;7)(var;var), del(11q), del(12p), +19, del(20q), -Y); int-1 (any other double, +8, i(17)(q10), +21, any other single, independent clones); int-2 (double incl. -7/7q-, der(3)(q21)/der(3)(q26), -7/7q-, complex 3 abnormalities) and poor (complex >3 abnormalities). Median survival was 50.6 months for good (n=1936), 25.7 months for int-1 (n=451), 16.0 months for int-2 (n=177) and 5.7 months for poor (n=188) and AML-t was 71.9 months for good (n=1681), 14.7 months for int-1 (n=384), 9.8 months for int-2 (n=148) and 3.4 months for poor (n=159). Differences in OS and AML-t were highly significant (p<0.0001). Multivariate analysis resulted in a Hazard Ratio of 1.0 for good (reference category), 1.8 for int-1, 2.1 for int-2 and 4.8 for poor concerning OS. Regarding AML-t, HR was 1.0 for good, 2.6 for int-1, 3.1 for int-2 and 5.2 for poor (all p <0.0001 for OS and AML-t). Conclusions: In summary, we were able to generate a solid database for a revised cytogenetic scoring system, which can serve as the cytogenetic model for the upcoming revision of the IPSS. Acknowledgments: The authors like to thank the MDS-Foundation for its support. 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".