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Record W4287974549

Noninvasive Fetal RhD Blood Group Genotyping: A Health Technology Assessment.

2020· review· en· W4287974549 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed · 2020
Typereview
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGenotypingPregnancySystematic reviewPediatricsFamily medicineObstetricsEmergency medicineMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: RhD blood group incompatibility during pregnancy can cause serious health problems for the fetus. Noninvasive fetal RhD blood group genotyping is a test for fetal RhD status that may help prevent unnecessary preventive treatment (Rh immunoglobulin [RhIG] injections) and intensive pregnancy monitoring. We conducted a health technology assessment of noninvasive fetal RhD blood group genotyping for RhD-negative (RhD-) pregnancies. Our assessment evaluated the test's diagnostic accuracy, clinical utility, and cost-effectiveness, the budget impact of publicly funding this test, and patients' and providers' preferences and values. METHODS: We performed a systematic literature search of the clinical and economic evidence to conduct an overview of reviews for test accuracy, a systematic review for clinical utility, and a review of the test's cost-effectiveness compared with usual care. We assessed the risk of bias of each included systematic review and study using the ROBIS and RoBANs tools, respectively. We assessed the quality of the body of clinical evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We developed probabilistic Markov microsimulation models to determine the cost-effectiveness and cost-utility of noninvasive fetal RhD genotyping compared with usual care from the Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding this test in Ontario. To examine patient and provider preferences related to noninvasive fetal RhD genotyping, we conducted a literature survey of quantitative studies on preference; the Canadian Agency for Drugs and Technologies in Health (CADTH) performed a review of qualitative literature about patient preferences; and we conducted interviews and an online survey with Ontario patients. RESULTS: We included six systematic reviews in the overview of reviews on diagnostic test accuracy and 11 studies in the clinical utility review. Across systematic reviews, test accuracy was high for noninvasive fetal RhD genotyping. The evidence suggests that implementation of noninvasive fetal RhD genotyping may lead to avoidance of unnecessary RhIG prophylaxis (GRADE: Low), good compliance with targeted RhIG prophylaxis (GRADE: Very low), and high uptake of genotyping (GRADE: Low). Alloimmunization may not increase when using noninvasive fetal RhD genotyping to target prenatal RhIG prophylaxis (GRADE: Very low), and may allow unnecessary monitoring and invasive procedures to be avoided in alloimmunized pregnancies (GRADE: Very low).We included eight published economic studies that reported inconsistent results regarding the cost-effectiveness of noninvasive fetal RhD genotyping. In nonalloimmunized RhD- pregnancies, compared with usual care, the intervention identified more maternal alloimmunization cases (probability: 0.0022 vs. 0.0020) and was associated with a reduced number of RhIG injections per pregnancy (1.79 vs 1.43). It was more expensive ($154, 95% credible interval [CrI] $139 to $169) but had little impact on the QALYs of newborns followed over a 10-year time horizon (0.0007, 95% CrI -0.01 to 0.01). The cost of noninvasive fetal RhD genotyping and inclusion of paternal RhD typing were drivers of the cost-effectiveness results in this population. In alloimmunized RhD- pregnancies, noninvasive fetal RhD genotyping was associated with lower resource use during the pregnancy. Compared with usual care, it was less costly (-$6,280, 95% CrI -$6,325 to -$6,229) and more effective (0.19 QALYs, 95% CrI 0.17 to 0.20).The annual budget impact of publicly funding noninvasive fetal RhD genotyping in nonalloimmunized RhD- pregnancies in Ontario ranges from $2.6 million in year 1 (uptake of 80%) to $3.4 million in year 5 (uptake of 100%), with a 5-year total of about $14.8 million. In alloimmunized pregnancies, we estimate cost savings, from about $9 million in year 1 to about $12 million in year 5, with 5-year total savings of about $51.5 million.We included two studies in the survey of quantitative preferences literature. In the quantitative literature, RhD- pregnant people support routine offering of noninvasive fetal RhD genotyping as part of pregnancy care, with a preference to be adequately informed about the test process, attributes, timing, and risks in advance of the test, ideally in a dialogue with their health care provider. More than half of obstetric health care providers were supportive of offering the test. The qualitative review by CADTH and our own engagement with Ontario patients yielded similar results. Participants consistently expressed a desire for more information about the test and assurance about its safety. They also consistently mentioned the prevention of unnecessary monitoring and treatment as potential benefits. CONCLUSIONS: Noninvasive fetal RhD blood group genotyping is an accurate test to determine RhD incompatibility and guide management of RhD- pregnancies. Compared with usual care, noninvasive fetal RhD genotyping is less costly and more effective for the management of alloimmunized pregnancies. For nonalloimmunized pregnancies, noninvasive fetal RhD genotyping would generally not be considered cost-effective, compared with usual care, unless the cost of testing is much lower than what is proposed now. Publicly funding noninvasive fetal RhD genotyping for guiding the management of RhD- pregnancies in Ontario over next 5 years is associated with a total budget impact of about $15 million in nonalloimmunized pregnancies and total cost savings of about $51 million in alloimmunized pregnancies. Patients and providers indicated support for the routine use of noninvasive fetal RhD genotyping in RhD- pregnancies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.090
metaresearch head score (Gemma)0.286
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.120
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.286
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.012
Bibliometrics0.0250.021
Science and technology studies0.0010.002
Scholarly communication0.0070.005
Open science0.0040.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.052
GPT teacher head0.320
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations13
Published2020
Admission routes1
Has abstractyes

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