Clinical utility of viral load measurements in individuals with chronic hepatitis C infection on antiviral therapy
Bibliographic record
Abstract
SUMMARY: Both absolute viral load and log decline in viral load from baseline were found clinically useful in predicting sustained virological response and lack of sustained virological response (non-sustained virological response, NSVR) to treatment. We assessed the clinical utility of hepatitis C virus (HCV) RNA quantitation and changes in viral load using the VERSANT HCV RNA 3.0 Assay (bDNA) in 351 HCV-infected individuals treated with interferon plus ribavirin. We show that viral load decision thresholds provided negative predictive values (NPVs) of >95% at week 4 using a 100 000 IU/mL cut-off and at weeks 8 and 12 using 10 000 IU/mL cut-offs. A 2-log decline from baseline provided NPVs >95% at weeks 8 and 12. Combinations of absolute viral loads and changes in viral load from baseline did not enhance the performance of the decision rules for predicting NSVR. The positive predictive values (PPVs) at weeks 8 and 12 were 59.1 and 67.3%. This study highlights the critical importance of viral quantitation in gauging therapeutic response in patients with chronic HCV infection on antiviral therapy. Early changes in viral load, measured as absolute viral loads or change in viral load from baseline, are highly predictive of NSVR at 8 and 12 weeks. PPVs are modest but these data may provide encouragement to patients who are in the early phases of treatment when side effects are frequent. Additionally, we demonstrated the need for cautious interpretation of stopping rules when the values are at or near the decision thresholds.
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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 | 0.003 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".