Predictive significance of absolute lymphocyte count and morphology in adults with a new onset peripheral blood lymphocytosis
Bibliographic record
Abstract
AIMS: Lymphocytosis is commonly encountered in the haematology laboratory. Evaluation of blood films is an important screening tool for differentiating between reactive and malignant processes. The optimal lymphocyte number to trigger morphological evaluation of the smear has not been well defined in the literature. Likewise, the significance of lymphocyte morphology has not been well studied and there are no consensus guidelines or follow-up recommendations available. We attempt to evaluate the significance of lymphocyte morphology and to define the best possible cut-off value of absolute lymphocyte count for morphology review. METHODS: 71 adult patients with newly detected lymphocytosis of 5.0×10(9)/L or more were categorised to either a reactive process or a lymphoproliferative disorder. We performed statistical analysis and morphology review to compare the difference in age, gender, lymphocyte count and morphological features between the two groups. Receiver operating characteristic analysis was performed to determine an optimal lymphocyte number to trigger morphology review. RESULTS: Lymphoproliferative disorders are associated with advanced age and higher lymphocyte count. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of lymphocyte morphology as a screening test were 0.9, 0.59, 0.60, 0.58 and 0.71, respectively. The optimal cut-off of lymphocyte number for morphology review was found to be close to 7×10(9)/L. CONCLUSIONS: We found a moderate interobserver agreement for the morphological assessment. 'Reactive' morphology was very predictive of a reactive process, but 'malignant' morphology was a poor predictor of a lymphoproliferative disorder.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".