| Literature DB >> 32372659 |
Tanitra Tantitamit1, Nipon Khemapech2, Piyalamporn Havanond2, Wichai Termrungruanglert2.
Abstract
To identify the optimal cost-effective strategy for cervical cancer screening program in Thailand by comparing the different algorithms which based on the use of primary human papilloma virus (HPV) assay. We use a Microsoft Excel-based spreadsheet to calculate the accumulated cases of preinvasive and invasive cervical cancer and the budget impact of each screening program. The model was developed to determine the cost-effectiveness of 3 screening strategies: pooled HPV test with reflex liquid-based cytology triage, HPV genotyping with reflex p16/ki67 dual stain cytology, and pooled HPV test with dual stain. The main outcomes were the total cost, incremental quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). Strategy entailing primary HPV genotyping and reflex dual stain cytology is the least costly strategy (total cost US$37 893 407) and provides the similar QALY gained compared to pooled high-risk HPV testing with reflex dual stain (Average QALY 24.03). Pooled HPV test with reflex dual staining is more costly compared to strategy without reflex dual staining. The ICER was US$353.40 per QALY gained. One-way sensitivity analysis showed that the model is sensitive to the cost of dual stain and the cost of cancer treatment. Decreasing the incidence of cervical cancer case and increasing the QALYs can be successful by using dual stain cytology as the triage test for pooled HPV test or HPV genotyping. The result of our analysis favors the use of HPV genotyping with the reflex dual stain as it offers the most QALY at the lowest cost.Entities:
Keywords: biomarkers; cancer screening; cervical cancer; cost-effectiveness analysis; human papillomavirus DNA tests
Mesh:
Year: 2020 PMID: 32372659 PMCID: PMC7218320 DOI: 10.1177/1073274820922540
Source DB: PubMed Journal: Cancer Control ISSN: 1073-2748 Impact factor: 3.302
Figure 1.Model natural history of cervical cancer.
Figure 2.Screening model. A, Pooled HPV test with reflex LBC triage. B, HPV genotyping test with reflex dual stain. HPV indicates human papilloma virus.
Clinical Parameters.
| The Performance of Screening Test[ | Input Value |
|---|---|
| Cytology (threshold = ASCUS) | |
| Sensitivity of cytology for cervical intraepithelial neoplasia 2 | 53.20% |
| Sensitivity of cytology for cervical intraepithelial neoplasia 3 | 57.70% |
| Sensitivity of cytology for invasive cervical carcinoma | 57.70% |
| Specificity of cytology | 73.40% |
| HPV testing | |
| Sensitivity of pooled high-risk HPV testing for cervical intraepithelial neoplasia 2 | 86.40% |
| Sensitivity of pooled high-risk HPV testing for cervical intraepithelial neoplasia 3 | 89.90% |
| Sensitivity of pooled high-risk HPV testing for invasive cervical carcinoma | 89.90% |
| Specificity of pooled high-risk HPV testing | 62.70% |
| Sensitivity of genotyping 16/18 for cervical intraepithelial neoplasia 2 | 43.60% |
| Sensitivity of genotyping 16/18 for cervical intraepithelial neoplasia 3 | 53.40% |
| Sensitivity of genotyping 16/18 for invasive cervical cancer | 59.20% |
| Specificity of genotyping 16/18 | 91.90% |
| Dual staining | |
| Pooled HPV triage | |
| Sensitivity for cervical intraepithelial neoplasia 2 | 86.80% |
| Sensitivity for cervical intraepithelial neoplasia 3 | 89.80% |
| Specificity for cervical intraepithelial neoplasia 2+ | 71.40% |
| Sensitivity for invasive cervical cancer | 93.80% |
| Epidemiology data[ | Input |
| Prevalence of high-risk HPV | 5.6% |
| Prevalence of HPV16 and 18 | 1.7% |
| Prevalence of cervical intraepithelial neoplasia 1 | 0.6% |
| Prevalence of cervical intraepithelial neoplasia 2 | 0.3% |
| Prevalence of cervical intraepithelial neoplasia 3 | 0.8% |
| Prevalence of invasive cervical cancer | 0.075% |
| General population annual death rate | 0.800% |
| % of high grade squamous intraepithelial lesion (HSIL) + population that is HPV+ | 88.4% |
| % of low grade squamous intraepithelial lesion (LSIL) population that is HPV+ | 61.5% |
| % of atypical squamous cells of undetermined significant (ASCUS) population that is HPV+ | 21.4% |
| % cervical intraepithelial neoplasia 1 that are high-risk HPV 16/18 | 13.6% |
| % cervical intraepithelial neoplasia 2 that are high-risk HPV 16/18 | 23.1% |
| % cervical intraepithelial neoplasia 3 that are high-risk HPV 16/18 | 50.3% |
| % of invasive cervical carcinoma that are high-risk HPV 16/18 | 75.0% |
| Natural history parameters [ | Input |
| Progression | |
| Well to high-risk HPV infection | 3.20% |
| Transformation from high-risk HPV (12 types) to: | |
| cervical intraepithelial neoplasia 1 | 9.10% |
| cervical intraepithelial neoplasia 2 (3year FU Luyten) | 0.10% |
| cervical intraepithelial neoplasia 3 | 0.10% |
| Transformation from high-risk HPV 16/18 to: | |
| cervical intraepithelial neoplasia 1 | 7.30% |
| cervical intraepithelial neoplasia 2 | 2.20% |
| cervical intraepithelial neoplasia 3 | 2.00% |
| Progression from cervical intraepithelial neoplasia 1 | |
| to cervical intraepithelial neoplasia 2 | 3.10% |
| to cervical intraepithelial neoplasia 3 | 0.90% |
| Progression from cervical intraepithelial neoplasia 2 | |
| to cervical intraepithelial neoplasia 3 (2year FU, Luyten) | 4.20% |
| to invasive Cervical Cancer | 0.00% |
| to cervical intraepithelial neoplasia 3 to invasive Cervical Cancer | 4.50% |
| Annual mortality rate for cervical cancer | 8.30% |
| Regression | |
| Regression from high-risk HPV (12 types) to: | |
| with NORMAL smear to well | 58.60% |
| with BORDERLINE/MILD smear to well | 45.60% |
| Regression from high-risk HPV 16/18 to: | |
| with NORMAL smear to well | 43.80% |
| with BORDERLINE/MILD smear to well | 21.80% |
| Regression from cervical intraepithelial neoplasia 1 | |
| to well | 21.20% |
| to high-risk HPV | 2.40% |
| Regression from cervical intraepithelial neoplasia 2 | |
| to well | 9.40% |
| to cervical intraepithelial neoplasia 1 | 9.40% |
| Regression from cervical intraepithelial neoplasia 3 | |
| to well | 3.80% |
| to cervical intraepithelial neoplasia 1 | 1.60% |
Abbreviations: HPV, human papilloma virus.
Cost Parameters.a
| Cost | Input Value (USD) |
|---|---|
| Screening costs[ | |
| Office visit (routine/repeat screening) | 2.00 |
| Cytology test (lab fee) | 5.30 |
| Cytology test (professional fee) | 3.00 |
| HPV DNA test | 17.00 |
| P16/Ki67 dual staining | 35.00 |
| Diagnostic costs[ | |
| Office visit (diagnostic follow-up) | 12.86 |
| Colposcopy plus biopsy | 21.42 |
| Treatment costs[ | |
| Treatment for cervical intraepithelial neoplasia 2/3 | 1292.00 |
| Treatment for invasive cervical cancer | 7403.00 |
| End of life cancer treatment cost | 10019.00 |
| Discounting rate | |
| Discount rate for cost | 0.035 |
| Discount rate for health outcomes | 0.035 |
Abbreviation: HPV, human papilloma virus.
a The currency used was USD (US Dollar exchange rate on March 1, 2019, US$1 = 32 THB).
Base Case Results of Outcome, Cost, and ICER per QALY Gained.
| HPV Genotyping Test With Reflex Dual Stain (Strategy 2) | Pooled HPV Test With Reflex LBC (Strategy 1) | Pooled HPV Test With Reflex Dual Stain (Strategy 3) | |
|---|---|---|---|
| Screening performance (%) | |||
| Cervical cancer detected | 88.9 | 73.5 | 87.4 |
| Cervical intraepithelial neoplasia 3 detected | 85.2 | 73.3 | 85.9 |
| Cervical intraepithelial neoplasia 2 detected | 79.2 | 67.7 | 81.2 |
| Total number of cases detected | |||
| Cervical cancer detected | 31 607 | 35 577 | 31 765 |
| Cervical intraepithelial neoplasia 3 detected | 257 188 | 240 952 | 260 658 |
| Cervical intraepithelial neoplasia 2 detected | 230 669 | 200 524 | 239 577 |
| Average QALY | 24.029947 | 23.98 | 24.029999 |
| Total cost (USD) | 1 326 269 261 | 1 360 038 064 | 1 500 586 513 |
| Total cost per person (USD) | 167 | 171 | 189 |
| Incremental cost per person (USD) | – | 4 | 18 |
| Incremental effectiveness | – | −0.049947433159300 | 0.0499999999995993 |
| ICERa (USD/ QALY gained) | – | −85b | 353.405 |
Abbreviations: HPV, human papilloma virus; ICER; Incremental cost and effectiveness; LBC, liquid-based cytology; QALY, Quality adjust life year.
a The difference in cost divided by the difference in detected case for each strategy compared with the next best strategy.
b Strategies shown cost more but were less effective than the next most expensive strategy and were therefore dominated.