Placental Alpha-Microglobulin-1 Test in Resource-Limited Settings: A Cost-Effectiveness Analysis

Academic Article

Abstract

  • © 2016 by The American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved. OBJECTIVE: To evaluate whether the use of placental alpha-microglobulin-1 (PAMG-1) for the diagnosis of preterm premature rupture of membranes is costeffective in resource-limited settings. METHODS: We designed a decision-analytic model from a third-party payer's perspective to determine the cost-effectiveness of the PAMG-1 test compared with the traditional diagnostic test of pooling, Nitrazine, and ferning in diagnosing preterm premature rupture of membranes in a resource-limited setting. The primary health outcome of interest is the number of hospital transfers averted by each strategy per 1,000 patients screened. Baseline probabilities and cost assumptions were derived from published literature. We conducted sensitivity analyses using both deterministic and probabilistic models. Cost estimates reflect 2015 U.S. dollars. RESULTS: Under our baseline parameters, the use of a PAMG-1 test was the preferred cost-effective strategy. The PAMG-1 test averted hospital transfers of 447 truenegative patients per 1,000 tested at a cost of $143,407 ($320.82 per hospital transfer averted). The traditional test averted hospital transfers of 395 true-negative patients per 1,000 tested at a cost of $172,652 ($437.40 per hospital transfer averted). In a Monte Carlo simulation of 10 million trials, the PAMG-1 test was selected as the most cost-effective strategy with a frequency of 74%. The traditional test was only selected with a frequency of 26%. The "do-nothing" strategy was not selected throughout the trial. CONCLUSION: Among women presenting at resourcelimited settings with a history suspicious of preterm premature rupture of membranes between 24 and 36 weeks of gestation, our analysis provides evidence suggesting that PAMG-1 is the most cost-effective testing strategy.
  • Authors

    Published In

    Digital Object Identifier (doi)

    Pubmed Id

  • 22551396
  • Author List

  • Echebiri NC; Sinkey RG; Szczepanski JL; Shelton JA; McDoom MM; Odibo AO
  • Start Page

  • 584
  • End Page

  • 591
  • Volume

  • 127
  • Issue

  • 3