The predictive value of the Sokal and Hasford scoring systems in chronic myeloid leukaemia in the imatinib era
Bibliographic record
Abstract
Objectives: Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder characterized by the presence of Philadelphia chromosome (Ph) or BCR-ABL1 chimeric gene; which codes for an abnormal tyrosine kinase responsible for the malignant proliferation of myeloid cells. Imatinib mesylate, a selective inhibitor of this kinase, is the first choice of therapy in patients with CML. The study aimed to determine the effect of imatinib on the survival of different risk groups based on the Sokal and Hasford scoring systems. Methods: Between August 2003 and December 2009, 134 patients [ 83 males ( 62% ) , 51 females ( 38%) ] who came in first chronic phase (CP1) were recruited. Median age was 36 years (range, 13 - 75). Patients were followed up with monthly complete blood counts. Karyotyping and chemistries were done at 6 and 12 months into therapy and then yearly. Overall survival (OS), progression-free survival (PFS) and frequency of complete cytogenetic remission (CCR) were evaluated. Survival studies were analyzed using the Kaplan- Meier technique and P -value < 0.05 was considered significant. Results: OS was 99% and 94%, while PFS was 95% and 83%, at one and two years respectively. Both the Sokal and Hasford risk groups predicted significantly better PFS for low- and intermediate-risk patients ( P = 0.012 and P = 0.0001 respectively). However, neither of the scores was predictive for differences in OS or CCR. Conclusions: These results suggests that the Sokal and Hasford scoring systems are inadequate in predicting OS and CCR of CML patients in CP1 managed on imatinib, as compared to their usefulness before the imatinib era.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".