12 Cost-Benefit Analysis of Newborn Screening for Severe Combined Immune Deficiency: literature review and results transferability
Bibliographic record
Abstract
Abstract Background The purpose of screening for Severe Combined Immune Deficiency (SCID) is to enable timely diagnosis and treatment for this condition. Untreated SCID is uniformly fatal by 2 years of age. Hematopoietic stem cell transplantation is an effective treatment for SCID, and the success rate depends on the age at which it is performed. Earlier treatment improves survival, long term quality of life and decreases costs of treating patients, specifically by shortening hospitalization days. Screening, however, carries short-term implementation costs, that could potentially be a barrier to adding SCID to the newborn screening (NBS) panels. Objectives This literature review aimed to evaluate the cost-effectiveness of NBS for SCID and perform basic economic analysis review on available published sources. We also assessed the published results and clinical inputs for transferability between different centers. Design/Methods We conducted a systematic search of medical electronic databases: Google Scholar, Ovid, Medline, PubMed, CINAHL, EMBASE, the Cochrane Library, Science Citation Index and Evidence-Based Medicine and hand searched related references. We used the Preferred Reporting Items for Systematic review and Meta-analyses (PRISMA-2009) statement to report the findings. We extracted the details of individual study characteristics from each publication, assessed study quality, evaluated the effect sizes and assessed the influence of study design on the estimated effect size. The presence of small effect sizes was investigated using Funnel plots and Egger’s tests. Search terms included: newborn, SCID, newborn screening, cost-effectiveness, cost-benefit, cost-effectiveness analysis, cost-utility analysis, medical costs, the value of a statistical life, quality-adjusted life-years (QALYs) We included cross-sectional, case-control, and cohort studies that have been published in peer-reviewed journals, data from regional/national surveys. Results 298 records identified through database searching, 192 records removed. A total of 106 articles were found to be eligible for screening, 72 sources were excluded after abstracts review. Forty-four full -text articles were assessed for eligibility, and 14 were excluded (lack of relevance, misleading abstract). Thirty articles were included in the final literature review. We were looking for Level I evidence studies as a high-quality randomized trial or prospective study, sensible costs and alternatives, values obtained from many studies with multiway sensitivity analyses, a systematic review of Level I RCTs and Level I studies. A comparative economic analysis was performed on reviewed sources to determine the average cost-benefit of NBS for SCID among different centers. We used standard conversion to calculate total health costs and charges in US dollars. An average cost of screening for SCID per sample varies between 3.0 -6.0 US$, and at present, there are no known missed cases in SCID NBS programs. The average cost of treatment and QALY were the most common variables used in all reviewed sources and presented in Table 1. Charges for hospital care were more than 5 times higher for late-diagnosed cases of SCID compare to the early diagnosed cases (within the first 2 months of life). These results found to be none-specific to the particular countries, and have high potential transferability among different centers. Conclusion Our literature review analysis supports the cost-effectiveness of NBS for SCID. The opportunity of early treatment is a strong economic rationale for the addition of SCID screening to NBS programs.
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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 | 0.026 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.023 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".