Hepatitis B and Hepatitis C Viral Infections in Patients with Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
BACKGROUND: Whether chronic hepatitis B virus (HBV) or hepatitis C virus (HCV) infections contribute to the pathogenesis and⁄or course of chronic lymphocytic leukemia is unclear. OBJECTIVE: To document the prevalences of HBV and HCV infections in chronic lymphocytic leukemia patients, and to determine whether infected patients experience more aggressive disease than those without infection. METHODS: Patient sera were screened for antibodies to HBV core antigen and HCV (anti-HCV) using ELISA; both sera and peripheral blood lymphocytes were further tested (regardless of antibody results) for HBV-DNA and HCV-RNA using real-time polymerase chain reaction. Prognostic markers for chronic lymphocytic leukemia included Rai stage, IgVH mutational status, β2-microglobulin levels, Zap-70 and CD38 status. RESULTS: Fourteen of 222 (6.3%) chronic lymphocytic leukemia patients and two of 72 (2.8%) healthy controls tested positive for previous or ongoing HBV infection (OR 2.4 [95% CI 0.5 to 7.7]; P=0.25) while four of 222 (1.8%) chronic lymphocytic leukemia patients and one of 72 (1.4%) controls tested positive for HCV markers (OR 1.3 [95% CI 0.2 to 6.4]; P=0.81). The levels and distribution of the various indicators of aggressive chronic lymphocytic leukemia disease were similar among HBV- and HCV-infected and uninfected patients. Survival times were also similar. Occult HBV and HCV infection (HBV-DNA or HCV-RNA positive in the absence of diagnostic serological markers) were uncommon in chronic lymphocytic leukemia patients (0.5% and 1.8%, respectively). CONCLUSIONS: The results of the present study do not support the hypothesis that HBV or HCV infections play an important role in the pathogenesis or course of chronic lymphocytic leukemia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".