Reevaluating the Role of Cytogenetic Testing in Patients with Suspected Myelodysplastic Syndrome in the Era of Next Generation Sequencing
Bibliographic record
Abstract
Background: In patients with suspected myelodysplastic syndrome (MDS), ancillary tests including cytogenetics (CG) and molecular diagnostics often support the diagnosis and add prognostic value guiding treatment decisions. Frequently, high-cost new technologies such as next generation sequencing (NGS) are added to the existing test menu without consideration for redundancy or added value. In our institution most patients with suspected MDS or cytopenias of undetermined origin will have conventional CG and NGS routinely ordered in addition to bone marrow (BM) morphology and flow cytometry (FCM). In a previous retrospective study, we evaluated combined NGS and CG in 120 patients and we found that our NGS panel had enhanced diagnostic and prognostic advantages over standard karyotyping. Based on these results, we undertook a quality improvement (QI) project to streamline molecular diagnostic testing, reduce test redundancy, turnaround time and cost. Methods: Between February and June 2019 we prospectively evaluated an "NGS first approach" to investigate patients with suspected MDS or cytopenias of undetermined origin. We assessed BM morphology, FCM, NGS testing (Oncomine Myeloid Research Assay, Thermo-Fisher) and CG for all patients. To assess whether BM aspirates can be used to triage appropriate use of NGS and CG, expert morphologists assigned BM samples to either the NGS/CG group or NGS only group, based exclusively on the presence of morphological abnormalities suggesting the possibility of an MDS. Results: We included 50 patients with suspected MDS or cytopenias of undetermined origin. Of these, 33 (66%) were triaged into the NGS/CG group and the remaining 17 (34%) into the NGS only group. In the NGS/CG group NGS testing revealed DNA mutations in 27 (81.8%) patients, whereas CG showed an abnormal karyotype in 12 (36.4%). Among the 21 patients with normal karyotype, NGS revealed mutations in 17 (81%). Two patients (6%) were identified as MDS by morphological examination and had an abnormal karyotype but negative NGS. Of those assigned to the NGS/CG group, 27 (81.8%) were morphologically diagnosed as either MDS (54.5%), acute myeloid leukemia (AML) (15.2%), MDS/myeloproliferative neoplasms (MPN) (6.1%), or therapy related myeloid neoplasms (t-MNs) - MDS/AML (6.1%). Among the patients assigned to the NGS only group, NGS testing showed no abnormalities in 16 (94.1%) patients. One patient was found to carry a BRAF mutation and subsequently diagnosed with hairy cell leukemia. CG testing showed a normal karyotype in 16 (94.1%) patients. One patient was found to carry an inv(2)(p11.2q13) and was diagnosed as clonal B cell lymphocytosis. Conclusion: We proposed and validated a testing algorithm based on an "NGS first approach" with CG restricted to patients with morphological changes suggestive of MDS, in order to reduce the number of samples karyotyped. Overall, in patients with a morphological diagnosis of MDS, NGS defined genetic abnormalities in more patients (84.2%) compared to CG (47.4%) alone. Additional cytogenetic testing only detected chromosomal abnormalities in less than 10% of MDS cases. Most importantly, nearly no mutations or CG abnormalities were detected in patients without dysplastic features. Based on these results we estimated that we could reduce karyotyping by 10% to 20% for patients presenting with probable MDS or cytopenias of undetermined origin using an "NGS first approach". Further studies are warranted to validate and provide cost saving estimates of this approach. Disclosures Hsia: Amgen: Honoraria; Jansen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".