BMC Infectious Diseases (Aug 2021)

Comparison of yield and relative costs of different screening algorithms for tuberculosis in active case-finding: a cross-section study

  • Fei Zhao,
  • Canyou Zhang,
  • Chongguang Yang,
  • Yinyin Xia,
  • Jin Xing,
  • Guolong Zhang,
  • Lin Xu,
  • Xiaomeng Wang,
  • Wei Lu,
  • Jianwei Li,
  • Feiying Liu,
  • Dingwen Lin,
  • Jianlin Wu,
  • Xin Shen,
  • Shuangyi Hou,
  • Yanling Yu,
  • Dongmei Hu,
  • Chunyi Fu,
  • Lixia Wang,
  • Jun Cheng,
  • Hui Zhang

DOI
https://doi.org/10.1186/s12879-021-06486-w
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 10

Abstract

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Abstract Background Part of tuberculosis (TB) patients were missed if symptomatic screening was based on the main TB likely symptoms. This study conducted to compare the yield and relative costs of different TB screening algorithms in active case-finding in the whole population in China. Methods The study population was screened based on the TB likely symptoms through a face-to-face interview in selected 27 communities from 10 counties of 10 provinces in China. If the individuals had any of the enhanced TB likely symptoms, both chest X-ray and sputum tests were carried out for them furtherly. We used the McNemar test to analyze the difference in TB detection among four algorithms in active case-finding. Of four algorithms, two were from WHO recommendations including 1a/1c, one from China National Tuberculosis Program, and one from this study with the enhanced TB likely symptoms. Furthermore, a two-way ANOVA analysis was performed to analyze the cost difference in the performance of active case-finding adjusted by different demographic and health characteristics among different algorithms. Results Algorithm with the enhanced TB likely symptoms defined in this study could increase the yield of TB detection in active case-finding, compared with algorithms recommended by WHO (p < 0.01, Kappa 95% CI: 0. 93–0.99) and China NTP (p = 0.03, Kappa 95% CI: 0.96–1.00). There was a significant difference in the total costs among different three algorithms WHO 1c/2/3 (F = 59.13, p < 0.01). No significant difference in the average costs for one active TB case screened and diagnosed through the process among Algorithms 1c/2/3 was evident (F = 2.78, p = 0.07). The average costs for one bacteriological positive case through algorithm WHO 1a was about two times as much as the costs for one active TB case through algorithms WHO 1c/2/3. Conclusions Active case-finding based on the enhanced symptom screening is meaningful for TB case-finding and it could identify more active TB cases in time. The findings indicated that this enhanced screening approach cost more compared to algorithms recommend by WHO and China NTP, but the increased yield resulted in comparative costs per patient. And it cost much more that only smear/bacteriological-positive TB cases are screened in active case-finding.

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