Quantifying the impact of real-world evidence: the sacubitril/valsartan experience
Bibliographic record
Abstract
Abstract Background The impact of publication of real-world evidence (RWE) on the use of approved cardiovascular therapies—including the size and timing of impact after publication—is unknown. Methods We assessed the relationship between the cadence of RWE publications and sales of sacubitril/valsartan following launch. Publication data were derived from a PubMed search over 7/01/2015–12/31/2023 for English-language, human subjects’ studies with the drug name and indication (heart failure) in the title or abstract. Studies were classified as RWE-related if the abstract contained patient endpoints (clinical and/or cost) derived from real world experience as assessed by a study author (SSR). Quarterly RWE publication data were combined with quarterly sacubitril/valsartan sales reported in Novartis Securities and Exchange Commission 6K reports over the 34-quarter period spanning Q3 2015 through Q4 2023. Quarter-to-quarter change in total sales was modeled with linear regression as a function of counts of previously published RWE-related studies, adjusting for a linear time trend to control for any underlying trends in sales growth; change in total sales from the quarter prior to publication to the quarter of publication to control for recent sales changes; and the cumulative count of RWE publications from Q3 2015 through the previous quarter to control for the contribution of previous RWE publications to future sales. Results The PubMed search identified 888 studies; of these, 333 (37.5%) were classified as RWE-related. For an additional RWE-related publication (in quarter, q) an estimated mean increase in quarterly sales of $1.8M (from quarter q to q+1 following publication), $3.5M (from q+1 to q+2), and $2.7M (from q+2 to q+3) was observed. In adjusted models, an additional RWE publication was associated with a mean gain in sales from quarter q+1 to q+2 of $2.6M (95% CI −$0.2M to $5.4M). RWE publications were not associated with an increase in sales in the quarter following publication, and the association was attenuated by third quarter following publication. Conclusion The number of RWE publications was associated with increased use of sacubitril/valsartan, typically peaking 2 quarters following publication. These results provide preliminary empirical evidence of RWE’s ability to support therapy adoption. Our findings suggest effective RWE approaches and continued cadence of publications may help to drive continued therapy adoption long after therapy approval.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.211 | 0.484 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".