Cost-Effectiveness Analysis of Pneumococcal Vaccines in the Pediatric Population: A Systematic Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategy
2.2. Selection Process
2.3. Data Extraction
2.4. Articles Quality Assessment
3. Results
3.1. Studies Selection Process
3.2. Characteristics of Included Studies
3.3. Quality Assessment
3.4. Cost-Effectiveness Related Data
3.4.1. Lower-Valent Pneumococcal Vaccine
3.4.2. Higher-Valent Pneumococcal Vaccine
3.5. Sensitivity Analysis
4. Discussion
5. Conclusions
6. Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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No. | Author, Year, Country | Analysis Type | Intervention | Clinical Outcome | Model | Time Horizon | Discount Rate | Currency | |
---|---|---|---|---|---|---|---|---|---|
1 | Lytle et al., 2023, Canada [45] | CEA | PCV20 vs. PCV13 | IPD | Markov | 10 years | 1.50% | 2022 CAD | |
PCV20 vs. PCV15 | Pneumonia | ||||||||
AOM | |||||||||
2 | Sevilla et al., 2022, Egypt [42] | CBA | PCV13 vs. no vaccination | IPD | Markov | 100 years | 3% | 2016 USD | |
CUA | PCV10 vs. no vaccination | Pneumonia | |||||||
PCV13 vs. PCV13 | AOM | ||||||||
3 | Dilokthornsakul et al., 2019, Thailand [46] | CEA | PCV10 vs. no vaccination | IPD | Markov | Lifetime | 3% | 2018 TBH | |
PCV10 vs. no vaccination | ACP | ||||||||
All cause-AOM | |||||||||
4 | Krishnamoorthy et al., 2019, India [51] | CEA | PCV13 vs. no vaccination | IPD | UNIVAC decision support | 10 years | 3% | 2017 USD | |
Pneumonia | |||||||||
AOM | |||||||||
5 | Shen et al., 2018, China [54] | CEA | PCV13 vs. no vaccination | IPD | Decision analytic model | 1 year | 3% | 2015 CNY | |
Pneumonia | |||||||||
AOM | |||||||||
6 | Dorji et al., 2018, Bhutan [43] | CUA | PCV13 vs. no vaccination | IPD | Markov | 100 years | 3% | 2017 USD | |
PCV10 vs. no vaccination | Pneumonia | ||||||||
PCV13 vs. PCV10 | AOM | ||||||||
7 | Huang et al., 2023, USA [47] | CEA | PCV15 vs. PCV13 | IPD | Markov | Lifetime | 3% | 2021 USD | |
Pneumonia | |||||||||
AOM | |||||||||
8 | Tajima et al., 2023, Japan [48] | CEA | PCV15 vs. PCV13 | IPD | Markov | 10 years | 2% | 2015 USD | |
NBPP | |||||||||
Pneumococcal AOM | |||||||||
9 | Li et al., 2021, China [56] | CEA | PCV13 vs. no vaccination | IPD | Decision analytic | 1 year | 5% | 2019 CNY | |
Pneumonia | |||||||||
AOM | |||||||||
10 | Wilson et al., 2022, UK [57] | CEA | PCV15 vs. PCV13 | IPD | Economic model | 5 years | 3.50% | 2021 GBP | |
PCV20 vs. PCV13 | Pneumonia | ||||||||
PCV20 vs. PCV15 | AOM | ||||||||
11 | Chen et al., 2019, 180 countries * [55] | CEA | PCV13 vs. no vaccination | IPD | Decision tree | 30 years | 3% | 2015 USD | |
Pneumonia | |||||||||
AOM | |||||||||
12 | Perdrizet et al., 2021, Philippines [52] | CEA | PCV13 vs. PCV10-GSK | IPD | Decision analytic model | 10 years | 7% | 2020 PHP | |
Pneumonia | |||||||||
AOM | |||||||||
13 | Warren et al., 2023, Greece [53] | CEA | PCV20 vs. PCV15 | IPD | Decision-analytic mode | 10 years | 3.50% | 2023 EUR | |
Pneumonia | |||||||||
AOM | |||||||||
14 | Huang et al., 2023, South Africa [44] | CUA | PCV13 vs. PCV10-GSK | IPD | Decision-analytic forecasting models | 10 years | 5% | 2022 ZAR | |
PCV13 vs. PCV10-SII | Pneumonia | ||||||||
AOM | |||||||||
15 | Rozenbaum et al., 2024, USA [49] | CEA | PCV20 vs. PCV13 | IPD | Markov | 10 years | 3% | 2022 USD | |
PCV20 vs. PCV15 | ACP | ||||||||
OM | |||||||||
16 | Ta et al., 2024, Germany [50] | CEA | PCV20 vs. PCV13 | IPD | Markov | 10 years | 3% | 2020 EUR | |
PCV20 vs. PCV15 | ACP | ||||||||
All-cause AOM | |||||||||
No. | Author, Year, Country | Analysis Type | Intervention | Clinical Outcome | Perspective | Vaccine Coverage | Funding | Health Outcome | SA |
1 | Lytle et al., 2023, Canada [45] | CEA | PCV20 vs. PCV13 PCV20 vs. PCV15 | IPD Pneumonia AOM | Payer Society | 84% | Pfizer | QALY | DSA, PSA |
2 | Sevilla et al., 2022, Egypt [42] | CBA CUA | PCV13 vs. no vaccination PCV10 vs. no vaccination PCV13 vs. PCV13 | IPD Pneumonia AOM | Society Payer | 100% | Pfizer | RoR QALY, ICER | DSA, PSA |
3 | Dilokthornsakul et al., 2019, Thailand [46] | CEA | PCV10 vs. no vaccination PCV10 vs. no vaccination | IPD ACP All cause-AOM | Society | - | Pfizer | QALY, ICER | PSA |
4 | Krishnamoorthy et al., 2019, India [51] | CEA | PCV13 vs. no vaccination | IPD Pneumonia AOM | Government | 88% | - | DALY, ICER | PSA |
5 | Shen et al., 2018, China [54] | CEA | PCV13 vs. no vaccination | IPD Pneumonia AOM | Payer | 85% | Pfizer | QALY | DSA |
6 | Dorji et al., 2018, Bhutan [43] | CUA | PCV13 vs. no vaccination PCV10 vs. no vaccination PCV13 vs. PCV10 | IPD Pneumonia AOM | Government | 97% | WHO | QALY, ICER | DSA, PSA |
7 | Huang et al., 2023, USA [47] | CEA | PCV15 vs. PCV13 | IPD Pneumonia AOM | Society | 91.9% | Merck | QALY, LY, ICER | PSA, DSA |
8 | Tajima et al., 2023, Japan [48] | CEA | PCV15 vs. PCV13 | IPD NBPP, Pneumococcal AOM | Payer Society | 100% | Merck | QALY, ICER | PSA, DSA |
9 | Li et al., 2021, China [56] | CEA | PCV13 vs. no vaccination | IPD Pneumonia AOM | Payer | 70% | - | QALY, ICER | DSA |
10 | Wilson et al., 2022, UK [57] | CEA | PCV15 vs. PCV13 PCV20 vs. PCV13 PCV20 vs. PCV15 | IPD Pneumonia AOM | Payer | 91% | Pfizer | QALY, LY, ICER | DSA |
11 | Chen et al., 2019, 180 countries * [55] | CEA | PCV13 vs. no vaccination | IPD Pneumonia AOM | Healthcare | - | WHO, Gavi, Bill & Melinda Gates Foundation | DALY, ICER | DSA, PSA |
12 | Perdrizet et al., 2021, Philipine [52] | CEA | PCV13 vs. PCV10-GSK | IPD Pneumonia AOM | Society | 90% | Pfizer | LY, QALY, ICER | - |
13 | Warren et al., 2023, Greece [53] | CEA | PCV20 vs. PCV15 | IPD Pneumonia AOM | Payer | 84.5% | Pfizer | LY, QALY, ICER | PSA |
14 | Huang et al., 2023, South Africa [44] | CUA | PCV13 vs. PCV10-GSK PCV13 vs. PCV10-SII | IPD Pneumonia AOM | Payer | 90.7% | Pfizer | LY, QALY, ICER | - |
15 | Rozenbaum et al., 2024, USA [49] | CEA | PCV20 vs. PCV13 PCV20 vs. PCV15 | IPD ACP OM | Healthcare Society | 83.5% | Pfizer | QALY, LYs | DSA, PSA |
16 | Ta et al., 2024, Germany [50] | CEA | PCV20 vs. PCV13 PCV20 vs. PCV15 | IPD ACP All-cause AOM | Society | 76.8% | Pfizer | LY, QALY, ICER | PSA, DSA |
No. | Item | Lytle et al., 2023 [45] | Sevilla et al., 2022 [42] | Dilokthornsaku et al., 2019 [46] | Krishnamoorthy et al., 2019 [51] | Shen et al., 2018 [54] | Dorji et al., 2018 [43] | Huang et al., 2023 [47] | Tajima et al., 2023 [48] |
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1 | Title | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
2 | Abstract | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
3 | Background and objective | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
4 | Health economic analysis plan | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
5 | Study population | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
6 | Setting and location | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
7 | Comparators | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
8 | Perspective | 1 | 1 | 1 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
9 | Time horizon | 1 | 1 | 1 | 0.5 | 1 | 0.5 | 0.5 | 1 |
10 | Discount rate | 1 | 1 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
11 | Selection of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
12 | Measurement of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
13 | Valuation of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
14 | Measurement and valuation of resources and costs | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
15 | Currency, price date, and conversion | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
16 | Rationale and description of model | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
17 | Analytics and assumptions | 0.5 | 1 | 1 | 1 | 1 | 1 | 0.5 | 0.5 |
18 | Characterizing heterogeneity | 0.5 | 1 | 1 | 1 | 1 | 0.5 | 1 | 1 |
19 | Characterizing distributional effect | 0.5 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
20 | Characterizing uncertainty | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
21 | Approach to engagement with patients and others affected by the study | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
22 | Study parameters | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
23 | Summary of main results | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
24 | Effect of uncertainty | 1 | 1 | 1 | 1 | 0.5 | 1 | 1 | 1 |
25 | Effect of engagement with patients and others affected by the study | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
26 | Study findings, limitations, generalizability, and current knowledge | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
27 | Source of funding | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
28 | Conflicts of interest | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Total score | 24.5 | 26 | 25.5 | 24.5 | 24.5 | 24 | 24 | 24.5 | |
Conclusion | Good | Good | Good | Good | Good | Good | Good | Good | |
No. | Item | Li et al., 2021 [56] | Wilson et al., 2022 [57] | Chen et al., 2019 [55] | Perdrizet et al., 2021 [52] | Warren et al., 2023 [53] | Huang et al., 2023 [44] | Rozenbaum et al., 2024 [49] | Ta et al., 2024 [50] |
1 | Title | 1 | 1 | 1 | 1 | 1 | 0.5 | 1 | 1 |
2 | Abstract | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
3 | Background and objective | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
4 | Health economic analysis plan | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
5 | Study population | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
6 | Setting and location | 1 | 0.5 | 1 | 0.5 | 1 | 1 | 1 | 1 |
7 | Comparators | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
8 | Perspective | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 1 | 1 | 1 |
9 | Time horizon | 1 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 1 | 1 |
10 | Discount rate | 0.5 | 0.5 | 0.5 | 1 | 0.5 | 0.5 | 1 | 1 |
11 | Selection of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
12 | Measurement of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
13 | Valuation of outcomes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
14 | Measurement and valuation of resources and costs | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
15 | Currency, price date, and conversion | 0.5 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
16 | Rationale and description of model | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
17 | Analytics and assumptions | 1 | 1 | 1 | 1 | 0.5 | 0.5 | 0.5 | 0.5 |
18 | Characterizing heterogeneity | 1 | 1 | 0.5 | 0.5 | 0 | 1 | 1 | 1 |
19 | Characterizing distributional effect | 1 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
20 | Characterizing uncertainty | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 |
21 | Approach to engagement with patients and others affected by the study | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
22 | Study parameters | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
23 | Summary of main results | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
24 | Effect of uncertainty | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 |
25 | Effect of engagement with patients and others affected by the study | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
26 | Study findings, limitations, generalizability, and current knowledge | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
27 | Source of funding | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
28 | Conflicts of interest | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Total score | 24.5 | 23.5 | 23.5 | 23.5 | 22.5 | 21.5 | 24 | 25 | |
Conclusion | Good | Good | Good | Good | Good | Good | Good | Good |
Ref., Country, Currency | Schedule | Herd Effect | Vaccination Cost | Direct Cost | Indirect Cost | Total Cost | |
---|---|---|---|---|---|---|---|
PCV13 vs. No vaccination | |||||||
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | 43.63 | −0.88 | - | 42.75 | |
Dorji et al., Bhutan, 2017 USD [43] | 2 + 1 | Yes | - | - | - | 0.03 | |
Krishnamoorthy et al., India, 2017 USD [51] | 2 + 1 | No | 35,000,000 | −16,600,000 | - | −16,600,000 | |
Dilokthornsakul et al., Thailand, 2018 TBH [46] | 2 + 1 3 + 1 | No | - - | - - | - - | 2571 3693 | |
Shen et al., China, 2015 CNY [54] | 3 + 1 | No Yes | 38,382,200,000 38,382,200,000 | 29,362,300,000 13,524,700,000 | - - | 29,362,300,000 13,524,700,000 | |
Li et al., China, 2019 CNY [56] | 3 + 1 | Yes | −323,757,862 | −28,646,835 | - | −28,646,835 | |
Chen et al., global, 2015 USD [55] | 2 + 1, 3 + 1, 3 + 0 | Yes | 15,500,000,000 | 8,420,000,000 | −2,640,000,000 | 6,670,000,000 | |
PCV10 vs. No vaccination | |||||||
Dilokthornsakul et al., Thailand, 2018 TBH [46] | 2 + 1 3 + 1 | No | - - | - - | - - | 3881 5348 | |
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | 38.43 | 38.05 | - | 38.05 | |
Dorji et al., Bhutan, 2017 USD [43] | 2 + 1 | Yes | - | - | - | 0.02 | |
PCV13 vs. PCV10 | |||||||
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | 5.198 | 4.7 | - | 4.7 | |
Perdrizet et al., Philippines, 2020 PHP [52] | 3 + 1 | No | 3,159,192,812 | −1,399,247,136 | −10,875,530,146 | −12,274,777,282 | |
Huang et al., South Africa, 2022 ZAR [44] | 2 + 1 | No | 587,690,427 | −78,825,963 | - | −78,825,963 | |
Ref., Country, Currency | Schedule | Herd Effect | LYs | Effectiveness | ICER | CE Threshold | Cost-Effective |
PCV13 vs. No vaccination | |||||||
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | - | 0.0462 QALY | 926 | GDP: 3479 | Yes |
Dorji et al., Bhutan, 2017 USD [43] | 2 + 1 | Yes | - | 0.0007 QALY | 40 | GDP: 2708 | Yes |
Krishnamoorthy et al., India, 2017 USD [51] | 2 + 1 | No | - | 920,000 DALY | 467 | GDP: 1939.6 | Yes |
Dilokthornsakul et al., Thailand, 2018 TBH [46] | 2 + 1 3 + 1 | No | 0.03 0.03 | 0.0349 QALY 0.0380 QALY | 73,674 97,269 | WTP: 160,000 | Yes |
Shen et al., China, 2015 CNY [54] | 3 + 1 | No Yes | - - | 370,300 QALY 3,580,900 QALY | 79,304 3777 | GDP: 53,976 | Yes Yes |
Li et al., China, 2019 CNY [56] | 3 + 1 | Yes | - | 14,880 QALY | Dominant | GDP: 157,300 | Yes |
Chen et al., global, 2015 USD [55] | 2 + 1, 3 + 1, 3 + 0 | Yes | - | 9,130,000 DALY | 724 | WTP: 1000 | Yes |
PCV10 vs. No vaccination | |||||||
Dilokthornsakul et al., Thailand, 2018 TBH [46] | 2 + 1 3 + 1 | No | 0.02 0.02 | 0.0228 QALY 0.0248 QALY | 170,437 215,948 | WTP: 160,000 | No No |
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | - | 0.0192 QALY | 1984.414 | GDP: 3479 | Yes |
Dorji et al., Bhutan, 2017 USD [43] | 2 + 1 | Yes | - | 0.0006 QALY | 36 | GDP: 2708 | Yes |
PCV13 vs. PCV10 | |||||||
Sevilla et al., Egypt, 2016 USD [42] | 2 + 1 | Yes | - | 0.027 QALY | 173.98 | GDP: 3479 | Yes |
Perdrizet et al., Philippines, 2020 PHP [52] | 3 + 1 | No | 156,061 | 153,349 QALY | Cost-saving | - | Yes |
Huang et al., South Africa, 2022 ZAR [44] | 2 + 1 | No | 4484 | 3191 QALY | Cost-saving | - | Yes |
Ref., Country, Currency | Schedule | Herd Effect | Vaccine Cost | Direct Cost | Indirect Cost | Total Cost | |
---|---|---|---|---|---|---|---|
PCV15 vs. PCV13 | |||||||
Huang et al., USA, 2021 USD [47] | 3 + 1 | Yes | 25,200 | −6,800,033,529 | −4,017,519,577 | −10,817,553,106 | |
Tajima et al., Japan, 2022 JPY [48] | 3 + 1 | Yes | 3091 | −235,135,797 | −130,475,159 | −365,610,955 | |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 2 + 1 vs. 1 + 1 | No | 7,900,205 212,402,154 | 1,124,922 200,554,981 | - | 1,124,922 200,554,981 | |
PCV20 vs. PCV13 | |||||||
Lytle et al., Canada, 2022 CAD [45] | 2 + 1 | Yes | 82,002,815 | −3,226,480,346 | −656,062,710 | −3,882,543,056 | |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 2 + 1 vs. 1 + 1 | No | 38,303,366 215,602,573 | −459,192,688 −403,126,911 | - | −459,192,688 −403,126,911 | |
Rozenbaum et al., USA, 2022 USD [49] | 3 + 1 | Yes | 2,338,463,867 | −19,189,701,809 | −3,726,859,511 | −20,578,097,453 | |
Ta et al., Germany, 2022 EUR [50] | 3 + 1 vs. 2 + 1 | Yes | 525,362,283 | −2,035,127,528 | −358,136,083 | −2,393,263,611 | |
PCV20 vs. PCV15 | |||||||
Lytle et al., Canada, 2022 CAD [45] | 2 + 1 | Yes | 82,083,788 | −1,484,267,884 | −307,853,576 | −1,792,121,460 | |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 1 + 1 vs. 2 + 1 2 + 1 vs. 2 + 1 2 + 1 vs. 1 + 1 | No | 30,403,161 −174,098,788 3,200,419 207,702,386 | −460,317,610 −659,747,669 −603,681,892 −404,251,833 | - | −460,317,610 −659,747,669 −603,681,892 −404,251,833 | |
Warren et al., Greece, 2023 EUR [53] | 3 + 1 | No | −4,566,825 | −58,138,419 | - | -58,138,419 | |
Rozenbaum et al., USA, 2022 USD [49] | 3 + 1 | Yes | 2,437,771,654 | −8,003,928,578 | −1,898,767,496 | − 9,902,696,074 | |
Ta et al., Germany, 2022 EUR [50] | 3 + 1 vs. 2 + 1 | Yes | 522,747,819 | −1,343,839,409 | −284,161,097 | -1,628,000,506 | |
Ref., Country, Currency | Schedule | Herd Effect | LYs | Effectiveness | ICER | CE Threshold | Cost-Effective |
PCV15 vs. PCV13 | |||||||
Huang et al., USA, 2021 USD [47] | 3 + 1 | Yes | 90,026 | 96,056 QALY | Dominant | - | Yes |
Tajima et al., Japan, 2022 JPY [48] | 3 + 1 | Yes | 7 | 24 QALY | Dominant | - | Yes |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 2 + 1 vs. 1 + 1 | No | 262 475 | 361 QALY 640 QALY | 3112 313,229 | WTP: 20,000 | Yes No |
PCV20 vs. PCV13 | |||||||
Lytle et al., Canada, 2022 CAD [45] | 2 + 1 | Yes | - | 47,056 QALY | Dominant | - | Yes |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 2 + 1 vs. 1 + 1 | No | 23,165 28,818 | 28,096 QALY 35,009 QALY | Dominant Dominant | WTP: 20,000 | Yes Yes |
Rozenbaum et al., USA, 2022 USD [49] | 3 + 1 | Yes | 515,203 | 271,414 QALY | Dominant | - | Yes |
Ta et al., Germany, 2022 EUR [50] | 3 + 1 vs. 2 + 1 | Yes | 563,014 | 904,854 QALY | Dominant | - | Yes |
PCV20 vs. PCV15 | |||||||
Lytle et al., Canada, 2022 CAD [45] | 2 + 1 | Yes | - | 21,881 QALY | Dominant | - | Yes |
Wilson et al., UK, 2021 GBP [57] | 1 + 1 vs. 1 + 1 1 + 1 vs. 2 + 1 2 + 1 vs. 2 + 1 2 + 1 vs. 1 + 1 | No | 22,903 22,690 28,343 28,556 | 27,735 QALY 27,456 QALY 34,369 QALY 34,648 QALY | Dominant Dominant Dominant Dominant | WTP: 20,000 | Yes Yes Yes Yes |
Warren et al., Greece, 2023 EUR [53] | 3 + 1 | No | 551 | 486 QALY | 110,000 | - | Yes |
Rozenbaum et al., USA, 2022 USD [49] | 3 + 1 | Yes | 279,655 | 146,168 QALY | Dominant | - | Yes |
Ta et al., Germany, 2022 EUR [50] | 3 + 1 vs. 2 + 1 | Yes | 400,731 | 646,235 QALY | Dominant | - | Yes |
Ref. | DSA | PSA | |
---|---|---|---|
The Most Impactful Parameter on ICERs | Probability | Quadrant | |
PCV13 vs. no vaccination | |||
Sevilla et al. [42] | -Base-year incidence rates -Discount rate -PCV direct and indirect effects on in-patient pneumonia -Modeling horizon length | - | - |
Dilokthornsakul et al. [46] | - | 100% | Northeast |
Krishnamoorthy et al. [51] | - | 100% | Northeast |
Shen et al. [54] | Incidence rates of inpatient pneumonia in ages 0–4 | - | - |
Dorji et al. [43] | -The variation in serotype coverage -Duration of vaccine protection -Excluding indirect vaccine effects (herd protection) -Discount rate | - | - |
Li et al. [56] | -Incidence of inpatient pneumonia 0–2 y, 2–4 y, 18–34 y -Total direct cost -Discount rate | - | - |
Chen et al. [55] | -Disease incidence -Case fatality rate -Vaccine price | 100% | Northeast |
PCV10 vs. no vaccination | |||
Sevilla et al. [42] | -Base-year incidence rates -Discount rate -PCV direct and indirect effects on inpatient pneumonia -Modeling horizon length | - | - |
Ref. | DSA | PSA | ||
---|---|---|---|---|
Interest Value | Most Impactful Parameter | Probability | Quadrant | |
PCV20 vs. PCV13 | ||||
Lytle et al. [45] | Cost | -Percentage of the indirect effect of PCV20 accrued -The steady-state indirect effects against hospitalized pneumonia -Age-specific serotype distribution of hospitalized pneumonia -The direct medical cost per hospitalized pneumonia episode | 100% | Southeast |
QALY | -Utility decrement of simple OM -Utility decrement of hospitalized pneumonia -Utility decrement of non-hospitalized pneumonia | |||
Wilson et al. [57] | NMB | -Percentage PP cases (≥65 years) -The hospitalized pneumonia incidence (≥65 years) -The direct costs for hospitalized pneumonia (≥65 years) | - | - |
Rozenbaum et al. [49] | Cost | -Vaccine serotype coverage -Indirect effect accrual for PCV20 -PCV20 and PCV13 cost per dose | 100% | Southeast |
QALY | -Indirect effect accrual for PCV20 -Vaccine serotype coverage -Maximum indirect effect for all-cause hospitalized NBP | |||
Ta et al. [50] | Cost | -Maximum indirect effect against hospitalized pneumonia (PCV20) -Serotype distribution by age -Incidence of hospitalized pneumonia -Cost per episode of hospitalized pneumonia | 100% | Southeast |
QALY | -Maximum indirect effects on hospitalized pneumonia (PCV20) -Serotype distribution by age -Baseline utilities -Hospitalized pneumonia incidence -CFR for hospitalized pneumonia | |||
PCV15 vs. PCV13 | ||||
Huang et al. [47] | ICERs | -VEs against all-cause inpatient pneumonia -Vaccine coverage rate -Indirect effects -Incidence and fatality rates of bacteremic pneumonia in the elderly | 100% | Southeast |
Tajima et al. [48] | ICERs | -PCV15 and PCV13 serotype-specific VE in in-patient pneumonia (including serotype-specific VE for V114 and PCV13) -Direct and indirect cost per episode -Baseline incidence rate -Percentage attributable to S. pneumoniae -Serotype distribution -QALY decrement | 98.7% | Southeast |
PCV20 vs. PCV15 | ||||
Warren et al. [53] | - | - | 100% | Southeast |
Rozenbaum et al. [49] | Cost | -Indirect effect accrual for PCV20 -Cost per dose of PCV20 and PCV15 -Maximum indirect effect in hospitalized pneumonia for PCV20 -Vaccine serotype coverage | 100% | Southeast |
QALY | -Indirect effect accrual for PCV20 -Maximum indirect effect in hospitalized pneumonia for PCV20 -Indirect effect accrual for PCV15 -Vaccine serotype coverage | |||
Ta et al. [50] | Cost | -Maximum indirect effect against hospitalized pneumonia (PCV20) -Serotype distribution by age -Incidence of hospitalized pneumonia -Cost per episode of hospitalized pneumonia | 98.4% | Southeast |
QALY | -Maximum indirect effects on hospitalized pneumonia (PCV20) -Serotype distribution by age -Baseline utilities -Hospitalized pneumonia incidence -Indirect effect accrual for PCV20 |
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Vo, N.X.; Pham, H.L.; Bui, U.M.; Ho, H.T.; Bui, T.T. Cost-Effectiveness Analysis of Pneumococcal Vaccines in the Pediatric Population: A Systematic Review. Healthcare 2024, 12, 1950. https://doi.org/10.3390/healthcare12191950
Vo NX, Pham HL, Bui UM, Ho HT, Bui TT. Cost-Effectiveness Analysis of Pneumococcal Vaccines in the Pediatric Population: A Systematic Review. Healthcare. 2024; 12(19):1950. https://doi.org/10.3390/healthcare12191950
Chicago/Turabian StyleVo, Nam Xuan, Huong Lai Pham, Uyen My Bui, Han Tue Ho, and Tien Thuy Bui. 2024. "Cost-Effectiveness Analysis of Pneumococcal Vaccines in the Pediatric Population: A Systematic Review" Healthcare 12, no. 19: 1950. https://doi.org/10.3390/healthcare12191950
APA StyleVo, N. X., Pham, H. L., Bui, U. M., Ho, H. T., & Bui, T. T. (2024). Cost-Effectiveness Analysis of Pneumococcal Vaccines in the Pediatric Population: A Systematic Review. Healthcare, 12(19), 1950. https://doi.org/10.3390/healthcare12191950