| Literature DB >> 26223975 |
Anna Melissa Guerrero1, Anne Julienne Genuino1, Melanie Santillan2, Naiyana Praditsitthikorn3, Varit Chantarastapornchit4, Yot Teerawattananon5, Marissa Alejandria6, Jean Anne Toral7.
Abstract
BACKGROUND: Cervical cancer is the second leading cause of cancer cases and deaths among Filipino women because of inadequate access to screening and treatment services. This study aims to evaluate the health and economic benefits of HPV vaccination and its combination with different screening strategies to find the most optimal preventive strategy in the Philippines.Entities:
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Year: 2015 PMID: 26223975 PMCID: PMC4520072 DOI: 10.1186/s12889-015-2046-1
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Assumptions in coverage scenarios for HPV vaccination and screening as used in the economic modeling
| Scenarios | Vaccination | Screening |
|---|---|---|
| Scenario I – Worst case | 20 % (poorest quintile) | 8 % |
| Scenario II | 20 % | 80 % |
| Scenario III | 80 % | 8 % |
| Scenario IV – Best case | 80 % | 80 % |
Parameters used in the model and their sampling distribution for the probabilistic sensitivity analysis
| Parameters | Mean (SE) | Distribution | Reference |
|---|---|---|---|
| Baseline Parameters | |||
| Discount Rate for both costs and outcomes | 3.5 % | DOH, 2013 | |
| Age start in the model (years) | 11 | ||
| PPP conversion factor, (Pesos per 1$) | 24.8 | World data bank, 2013 | |
| Epidemiological Parameters | |||
| Prevalence of HPV infection | 0.100 (0.064) | Beta | Myers et al. [ |
| Prevalence of CIN1 | 0.010 (0.010) | Beta | Myers et al. [ |
| Age specific (y) incidence of HPV infection | |||
| 11 | 0.019 (0.007) | ||
| 15 | 0.100 (0.038) | Beta | Myers et al. [ |
| 16 | 0.100 (0.038) | Beta | |
| 17 | 0.120 (0.046) | Beta | |
| 18 | 0.150 (0.057) | Beta | |
| 19 | 0.170 (0.065) | Beta | |
| 20 | 0.150 (0.057) | Beta | |
| 21 | 0.120 (0.046) | Beta | |
| 22 | 0.100 (0.038) | Beta | |
| 23 | 0.100 (0.038) | Beta | |
| 24 | 0.050 (0.019) | Beta | |
| 30 | 0.010 (0.004) | Beta | |
| 50+ | 0.005 (0.002) | Beta | |
| Yearly Transitional Probability | |||
| HPV infection to CIN1 | 0.072 (0.015) | Beta | Myers et al. [ |
| CIN1 to CIN2/3 (age [y]) | |||
| 15 | 0.017 (0.010) | Beta | Myers et al. [ |
| 35 | 0.069 (0.013) | Beta | |
| CIN 2/3 to invasive CA | 0.050 (0.008) | Beta | |
| Stage I to Stage II | 0.438 (0.351) | Beta | Myers et al. [ |
| Stage II to Stage III | 0.536 (0.351) | Beta | |
| Stage III to Stage IV | 0.684 (0.140) | Beta | |
| Regression | |||
| Age-specific (y) probability of regression: HPV infection to healthy | Myers et al. [ | ||
| 15 | 0.552 (0.084) | Beta | |
| 25 | 0.370 (0.033) | Beta | |
| 30 | 0.103 (0.018) | Beta | |
| Age-specific (y): CIN1 to HPV infection or healthy | Myers et al. [ | ||
| 15 | 0.161 (0.024) | Beta | |
| 35 | 0.082 (0.021) | Beta | |
| CIN 2/3 to CIN1 or healthy | 0.069 (0.013) | Beta | Myers et al. [ |
| Proportion of CIN1 reverting to healthy | 0.900 (0.128) | Beta | |
| Proportion of CIN2/3 reverting to healthy | 0.500 (0.128) | Beta | |
| Proportion of having symptoms | Myers et al. [ | ||
| Stage I | 0.150 (0.150) | Beta | |
| Stage II | 0.225 (0.225) | Beta | |
| Stage III | 0.600 (0.600) | Beta | |
| Stage IV | 0.900 (0.900) | Beta | |
| Weibull survival by CA stage and patient age (y) | |||
| Stage I | |||
| constant | −8.749 (1.259) | Log-Normal | Praditsitthikorn et al. [ |
| Age coefficient | 0.041 (0.020) | Log-Normal | |
| Gamma | 0.589 (1.139) | Log-Normal | |
| Stage II | |||
| constant | −7.066 (0.934) | Log-Normal | |
| Age coefficient | −0.014 (0.011) | Log-Normal | |
| Gamma | 0.919 (1.120) | Log-Normal | |
| Stage III | |||
| constant | −6.778 (0.891) | Log-Normal | |
| Age coefficient | 0.023 (0.011) | Log-Normal | |
| Gamma | 0.675 (1.098) | Log-Normal | |
| Stage IV | |||
| constant | −3.863 (1.217) | Log-Normal | |
| Age coefficient | −0.055 (0.022) | Log-Normal | |
| Gamma | 1.004 (1.226) | Log-Normal | |
| Program Effectiveness Parameters | |||
|
| |||
| Sensitivity for pre-invasive | 0.552 (0.070) | Beta | Sritipsukho, [ |
| Specificity | 0.915 (0.013) | Beta | |
|
| |||
| Sensitivity for pre-invasive | 0.716 (0.025) | Beta | Sritipsukho, [ |
| Specificity | 0.793 (0.011) | Beta | |
|
| |||
| Relative risk of persistence HPV infection, 1-year | 0.26 (0.064) | Beta | Rambout et al. [ |
| Programme Acceptability | |||
| Pap Smear | 0.08 | University of the Philippines-Department of Health Cervical Cancer Screening Study Group, 2001 [7] | |
| Proportion of Patients with CIN 2/3 | |||
| Receiving cryosurgery | 1.000 (1.000) | Beta | Goldie et al. [ |
| Receiving cold knife conisation | 0.125 (0.125) | Beta | Goldie et al. [ |
| Receiving simple hysterectomy | 0.125 (0.125) | Beta | Goldie et al. [ |
| Incidence of OP visit for treating minor complications from cryosurgery | 0.05 (0.05) | Beta | Goldie et al. [ |
| Incidence of IP visit for treating major complications from cryosurgery | 0.01 (0.01) | Beta | Goldie et al. [ |
| Annual rate of OP visits | Praditsitthikorn et al. [ | ||
| Initial Stage | 25.48 (1.41) | Gamma | |
| Remission Stage | 7.14 (0.59) | Gamma | |
| Persistence Stage | 38.53 (7.77) | Gamma | |
| Recurrence Stage | 13.37 (2.02) | Gamma | |
| Annual rate of IP visits | Praditsitthikorn et al. [ | ||
| Initial Stage | 0.77 (0.10) | Gamma | |
| Remission Stage | 0.15(0.04) | Gamma | |
| Persistence Stage | 0.87 (0.43) | Gamma | |
| Recurrence Stage | 1.64 (0.31) | Gamma | |
| Costing Parameters (in Php) | |||
| Direct Medical Costs of Screening (per visit) | |||
| Pap smear | 965 (965) | Gamma | Primary data collected by the authors |
| VIA | 500 (500) | Gamma | Primary data collected by the authors |
| Cost of follow up for Pap screening | 500 (500) | Gamma | Primary data collected by the authors |
| Cost of HPV vaccination (three doses) | 2,736 (2,376) | Gamma | Price Offer to the government |
| Cost of HPV booster doses | 800 (800) | Gamma | Price Offer to the government |
| Cost of Vaccine delivery and administration (per dose) | 112 (112) | Gamma | DOH DPCB, 2013 |
| Unit cost of colcoscopy/ biopsy | 1,120 (1,120) | Gamma | PHIC, 2013 |
| Unit costs | |||
| Cryotherapy | 1,500 (1,500) | Gamma | Primary data collected by the authors |
| Loop Electrosurgical Extraction Procedure (LEEP) | 12,644.54 (12,644.54) | Gamma | PHIC, 2013 |
| Cold knife conisation | 8100.36 (8100.36) | Gamma | PHIC, 2013 |
| Simple hysterectomy | 41,362.67 (41,362.67) | Gamma | PHIC, 2013 |
| Cost of hospitalization day (Php per day) | 500 (500) | Gamma | Health facilities |
| Hospitalization days | |||
| Cold knife conisation | 1 | Gamma | Expert opinion |
| Simple hysterectomy | 5 | Gamma | Expert opinion/ Primary data collected by the authors |
| Medical cost of follow – up | |||
| Cryosurgery | 1,000 (255.10) | Gamma | Primary data collected by the authors |
| LEEP/ Cold knife conisation/ Simple hysterectomy | 750 (127.55) | Gamma | Primary data collected by the authors |
| Unit Cost | |||
| Cervical CA staging | 4,485 (765.31) | Gamma | Primary data collected by the authors |
| Treating complications from cryosurgery (minor) | 510.08 (510.08) | Gamma | Primary data collected by the authors |
| Treating complications from cryosurgery (major) | 512.48 (512.48) | Gamma | Primary data collected by the authors |
| Annual Costs for treatment of invasive cervical CA | |||
| Initial Stage | |||
| -Stage I | 77,873.00 (39,073.469) | PHIC 2013 | |
| -Stage II | 77,873.00 | PHIC 2013 | |
| -Stage III | 106,390.05 | PHIC 2013 | |
| -Stage IV | 106,390.05 | PHIC 2013 | |
| Remission Stage | |||
| -Stage I | 16,523 | PHIC 2013 | |
| -Stage II | 16,115 | PHIC 2013 | |
| -Stage III | 20,618 | PHIC 2013 | |
| -Stage IV | 27,310 | PHIC 2013 | |
| Persistence Stage | |||
| -Stage I | 112,093 | PHIC 2013 | |
| -Stage II | 93,256 | PHIC 2013 | |
| -Stage III | 118,350 | PHIC 2013 | |
| -Stage IV | 117,801 | PHIC 2013 | |
| Recurrence | |||
| -Stage I | 65,818 | PHIC 2013 | |
| -Stage II | 63,747 | PHIC 2013 | |
| -Stage III | 83,512 | PHIC 2013 | |
| -Stage IV | 111,233 | PHIC 2013 | |
| Utility Parameters | |||
| Healthy Stage or CIN1-3 without complication | 1.00 (1.00) | Beta | Praditsitthikorn et al. [ |
| Initial Stage | |||
| -Stage I | 0.74 (0.01) | Beta | |
| -Stage II | 0.76 (0.01) | Beta | |
| -Stage III | 0.72 (0.02) | Beta | |
| -Stage IV | 0.63 (0.03) | Beta | |
| Remission Stage | |||
| -Stage I | 0.79 (0.01) | Beta | |
| -Stage II | 0.79 (0.01) | Beta | |
| -Stage III | 0.81 (0.01) | Beta | |
| -Stage IV | 0.85 (0.05) | Beta | |
| Persistence Stage | |||
| -Stage I | 0.80 (0.20) | Beta | |
| -Stage II | 0.80 (0.04) | Beta | |
| -Stage III | 0.65 (0.05) | Beta | |
| -Stage IV | 0.45 (0.05) | Beta | |
| Recurrence | |||
| -Stage I | 0.80 (0.03) | Beta | |
| -Stage II | 0.68 (0.02) | Beta | |
| -Stage III | 0.66 (0.04) | Beta | |
| -Stage IV | 0.81 (0.08) | Beta | |
DOH - Department of Health; DPCB - Disease Prevention and Control Bureau; PHIC - Philippine Health Insurance Corporation
Fig. 1Model validation
Fig. 2Efficiency frontier curve of optimal cervical cancer prevention strategies at varying coverage scenarios
Fig. 3Costs and health outcomes of optimal strategies for the prevention of cervical cancer
Fig. 4Probabilistic sensitivity analysis of the optimal policy options at different scenarios
Budget impact of optimal choices for cervical cancer prevention in the Philippines
| Options | TARGET POPULATION (5-yearly) | 5 YEARS BUDGET in million | ANNUAL BUDGET in million | |||||
|---|---|---|---|---|---|---|---|---|
| VIA | Vaccination (3-dose) | Pap Smear | VIA | Vaccination (3-dose) | Pap Smear | Total | ||
| 8 % Pap (35–55) | - | - | 941,758 | - | - | 471 (11.13) | 909 (21.48) | 182 (4.30) |
| 8 % VIA (35–55) | 941,758 | - | - | 94 (2.22) | - | - | 471 (11.13) | 94 (2.22) |
| 80 % VIA (35–45) | 5,597,648 | - | - | 560 (13.23) | - | - | 2,799 (66.13) | 560 (13.23) |
| 80 % VIA (35–50) | 7,663,312 | - | - | 766 (18.10) | - | - | 3,832 (90.54) | 766 (18.10) |
| 80 % VIA (35–55) | 9,417,584 | - | - | 942 (22.26) | - | - | 4,709 (111.26) | 942 (22.26) |
| 80 % Vac 11 + 80 % VIA (35–45) | 5,597,648 | 4,059,120 | - | 560 (13.23) | 11,106 (262.40) | - | 13,905 (328.53) | 2,781 (65.71) |
| 80 % Vac 11 + 80 % VIA (35–50) | 7,663,312 | 4,059,120 | - | 766 (18.10) | 11,106 (262.40) | - | 14,937 (352.92) | 2,987 (70.57) |
| 80 % Vac 11 + 80 % VIA (35–55) | 9,417,584 | 4,059,120 | - | 942 (22.26) | 11,106 (262.40) | - | 15,815 (373.66) | 3,163 (74.73) |
| 80 % Vac 11 + 80 % VIA (30–55) | 15,704,480 | 4,059,120 | - | 1570 (37.09) | 11,106 (262.40) | - | 18,958 (447.92) | 3,792 (89.95) |