P502: CLINICAL IMPLEMENTATION OF GERMLINE GENETIC TESTING FOR HEMATOLOGIC DISORDERS
Bibliographic record
Abstract
Background: Up to 18% of adult hematology patients (pts) suspected of having an inherited predisposition are found to have a germline mutation leading to a hereditary hematologic disorder (HHD). Timely identification of these disorders leads to heightened surveillance for malignancies, specific treatment regimens, donor selection, transplant conditioning regimens, cascade testing in family members and supportive care. Unlike solid tumour hereditary cancer syndromes, the investigations in HHD are more complex and there is no formal consensus of referral criteria or genetic testing criteria. We describe our initial experience in this patient population at our centre, the Princess Margaret Cancer Centre (PM). We have established a workflow to initiate germline genetic testing in pts under suspicion for a HHD. This involves a collaboration with a genetics clinic to 1) capture pts based on their personal/family history of cancer and suggestive genetic findings identified on bone marrow/blood, 2) procure a skin biopsy for fibroblast culture and germline DNA extraction and 3) provide follow-up counselling and management for positive results. Aims: Our goal is to evaluate the positivity rate of germline mutations in adult hematology pts who were referred for genetics assessment. Methods: The PM is the largest leukemia Centre in Canada, and has seen over 3000 adult pts with a malignant disorder from 2015-2021 (AML:1597, MDS:472, ALL:286, MPN:664 and marrow failure:22). We performed a retrospective chart review of all adult hematology pts referred to cancer genetics service for HHD workup during this time period. Results: 116 pts (66 male, 50 female) were suspected for a HHD and referred for germline genetic testing on fibroblast DNA. 52 pts (45%) were ≤40y old and 64 pts (55%) >40y old (age range 18-86y, median 53y). 71 pts (61%) were referred with a positive family history of hematologic disorders (HD). In addition, 61 pts presented with a myeloid malignancy (46 with MDS, AML, or CML, and 15 with a MPN), 42 presented with a lymphoid malignancy (ALL, CLL, or lymphoma), 8 presented with bone marrow failure, and 5 presented with other HD. 40 pts were found to have a germline genetic mutation, 7 of which were associated with carrier status. In total, 33 (28.4%) referred pts were found to have at least one actionable germline mutation. This corresponds to a positive genetic result found in 30% of pts referred with MDS/AML, 33% of pts referred with a lymphoid malignancy, and 18% of pts referred with bone marrow failure, MPN, or other HD. Additionally, 18 (55%) of these pts had a positive family history of HD, while 15 (45%) presented with no family history of HD. Of these 33 positive cases, 13 (11.2% of all referrals) occurred in a gene associated with a hematologic malignancy and resulted in a HHD diagnosis. 20 pts were found to have a mutation in a gene associated with a non-hematologic hereditary cancer syndrome. After the implementation of a HHD genetics workflow in 2018, we saw an increase in the total number of referrals to a genetics clinic over the past seven years, with 25 pts (6 positive cases) referred between 2015-2018, and 91 pts (27 positive cases) referred between 2019-2021. Image:Summary/Conclusion: Our overall positivity rate was 28.4% which includes mutations in any hereditary cancer gene, and 11.2% for HHDs. Our high pickup rate across all age groups and the increase in the number of referrals to genetics service suggests that more pts with HD, including older pts, would benefit from consultation with specialized centres that are experienced in the evaluation and treatment of these disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".