Supplement Error Corrected in HPV Self-Testing Cost-Effectiveness Study
A correction to a JAMA Network Open Original Investigation has reset one of the basic inputs behind the economic modeling of HPV self-testing for cervical cancer screening. In eTable 3 of Supplement 1, the annual cost of the intervention per member in year 1 was listed as $6945; the corrected figure is $69.45. The article, “Cost-Effectiveness of HPV Self-Testing Options for Cervical Cancer Screening,” was published October 1, 2025, and has since been amended.
A single misplaced decimal can distort an entire cost-effectiveness framework. When a model is built to compare screening strategies, the intervention cost is not a peripheral detail; it is one of the core variables that determines whether an option appears economically viable, especially in a preventive setting where the clinical benefit depends on broad implementation and sustained participation over time.
The correction does not introduce new clinical data, nor does it alter the study design or add fresh endpoint results. What it does is repair a numeric error in the supplementary material, where the year 1 annual cost per member was inflated by a factor of 100. For any health economic analysis, that kind of discrepancy can change the visual and analytic weight of a model, particularly when readers, payers, and policy teams rely on supplemental tables to examine the assumptions driving the primary conclusions.
Why a Decimal Point Matters in Health Economic Modeling
Cost-effectiveness work depends on the precision of its inputs. Screening interventions are often assessed not only by their ability to detect disease earlier, but also by whether they can do so at a price that health systems can absorb at scale. In cervical cancer prevention, HPV self-testing has drawn attention because it may expand screening access, reduce friction tied to clinic-based collection, and support participation among patients who otherwise remain unscreened.
Those potential benefits are only part of the equation. The economic case for self-testing hinges on practical costs: test distribution, processing, follow-up, staffing, and the administrative burden of implementation. A year 1 per-member cost of $69.45 fits plausibly into that type of framework. A figure of $6945 would not. The corrected value therefore restores internal consistency to the supplement and prevents readers from interpreting the intervention as vastly more expensive than intended.
A correction like this is not cosmetic. It is a reminder that health economic studies are especially sensitive to the accuracy of their tables because small typographical mistakes can ripple into downstream interpretation, media coverage, institutional review, and policy discussion.
What the Correction Means for Readers of the Study
The correction is limited to eTable 3 in Supplement 1. No additional errors are described in the notice. The main published article remains the same in title, scope, and topic: a cost-effectiveness analysis of HPV self-testing options for cervical cancer screening.
For clinicians, the practical takeaway is narrower than the error itself. The corrected supplementary value should be used when reviewing the study’s assumptions, reproducing the model, or discussing the affordability of screening strategies. For health economists, the notice reinforces a familiar but consequential point: supplementary materials are not ancillary in a trivial sense. They often contain the numerical scaffolding that supports the main result.
In preventive medicine, where programs are judged on population reach, follow-up efficiency, and budget impact, cost inputs can carry as much influence as the biological endpoint being modeled. Cervical cancer screening is a prime example because the value proposition depends on whether an intervention can move patients into the screening pathway at acceptable cost and with workable logistics.
The correction also preserves the credibility of the publication record. Journals issue amendments for this reason: to keep the literature aligned with the underlying data and to prevent a decimal-point error from hardening into an incorrect citation. In this case, the change was straightforward and specific, but the implications are familiar to anyone who reads economic studies carefully. When a single number is off by two orders of magnitude, the error can mislead even experienced readers if it is not corrected quickly.
Cervical Cancer Screening Economics Depend on Accurate Inputs
The broader subject of the original investigation remains clinically important. Cervical cancer screening depends on identifying patients who are eligible, making testing accessible, and ensuring follow-up after abnormal results. Self-collection strategies have generated interest because they may reduce access barriers and make prevention more reachable for people who face logistical, social, or procedural obstacles to in-clinic screening.
Economic models try to capture those realities in numeric form. They compare intervention costs against the downstream benefits of earlier detection, fewer missed screenings, and more efficient use of health resources. If the baseline cost estimate is wrong, the final interpretation can be distorted even when the underlying clinical rationale is sound.
This correction does not answer whether one self-testing option is superior to another, and it does not change the central public health question around how best to expand screening coverage. What it does is correct the cost input so readers are not left with an erroneous first-year per-member expense that would have made the intervention appear implausibly costly.
For any institution or payer considering implementation, the distinction is concrete. A per-member cost in the tens of dollars can be reviewed within the ordinary range of preventive program planning. A figure in the thousands would trigger a very different response, including skepticism about scalability and budget impact. The corrected supplement aligns the study’s reported number with a realistic economic frame and prevents that mismatch from carrying forward.
In health services research, errors of this kind are usually found not because the study is fundamentally flawed, but because the numerical machinery behind the analysis must be precise down to the last digit. The correction to JAMA Network Open is brief, but its relevance reaches beyond one table: cost-effectiveness findings depend on correct arithmetic, and even a single misplaced digit can alter how a screening strategy is judged.