Cost-Effectiveness of Screening and Early Diagnosis Strategies for Cancer in the General Adult Population in Low- and Middle-Income Countries: A Systematic Review

Abstract

Cancer is one of the leading causes of morbidity and mortality worldwide, disproportionately affecting low- and middle-income countries (LMICs) due to barriers to obtaining access to health care services and screening programs. The current study aimed to synthesize evidence on cost-effective strategies for cancer screening and early diagnosis in adults (≥18 years) in LMICs. The literature search was conducted in PubMed, the Cochrane Library, Embase, EconLit, CINAHL, LILACS, Global Health, and the Web of Science Core Collection databases. The review included cost-effectiveness studies compared with standard practices in LMICs. Two reviewers independently assessed eligibility, extracted data, and evaluated methodological quality using the Drummond and Jefferson guidelines. Twelve studies conducted in nine countries across four global regions were included. The results identified that the most cost-effective strategies for cervical cancer were human papillomavirus DNA testing, visual inspection with acetic acid, and combined tests. For breast and prostate cancer, digital breast tomosynthesis and the Prostate Health Index were promising options, repectively. However, limitations were noted in the studies, such as the lack of analysis on productivity changes and the justification of variables in sensitivity analyses. Population-based cancer screening strategies exist but must be adapted to the implementation context to maximize their cost-effectiveness in LMICs.

Keywords

cost-effectiveness screening early diagnosis cancer low- and middle-income countries

More than 19 million people were diagnosed with cancer in 2022, with low- and middle-income countries (LMICs) having approximately 4 million more new cancer cases and 2 million more cancer-related deaths compared with high-income countries (HICs).¹ These alarming figures highlight a critical challenge for public health, driven by high costs, delays in diagnosis and treatment, and limited access to health care services. Screening programs in LMICs face multiple individual and systemic barriers, including low coverage, shortages of health care personnel and supplies, and delays in patient referrals to oncology centers, all of which hinder effective cancer control.²

In LMICs, cancer screening program coverage is lower compared with HICs, where such programs achieve high coverage and operate efficiently.³ A study assessing cervical cancer screening rates across 202 countries found a 36-percentage-point gap between HICs and LMICs.⁴ These disparities stem from economic constraints, which hinder the comprehensive and equitable implementation of screening programs in resource-limited settings.⁵ Moreover, screening coverage in LMICs falls short of World Health Organization (WHO) recommendations, which set a global target of at least 70% coverage for all women.⁵ This low coverage, coupled with health system limitations, poses additional challenges to the effective implementation of cancer screening and early detection programs in LMICs.

The development of effective health policies is crucial for the successful implementation of cancer screening programs, as it enables better health outcomes through the systematic evaluation of target age groups, disease prevalence, recruitment strategies, screening intervals, clinical guidelines, and diagnostic tests.⁶ For screening and early detection to be effective, tests must be highly reliable and accurate, as high false-positive or false-negative rates can result in unnecessary costs and negative health consequences.⁷ Moreover, these tests must offer real clinical value while minimizing direct risks.

Cost-effectiveness analyses are essential for shaping public health strategies in cancer screening, as they help identify cost-effective interventions and support efforts to expand screening coverage in LMICs.⁸ While systematic reviews on the cost-effectiveness of screening and early detection tests are available, they often focus on specific cancer types and primarily compare screening with a no-screening scenario.⁹ Therefore, this study aimed to synthesize the existing evidence on cost-effectiveness studies of cancer screening and early diagnosis strategies in the general adult population of LMICs.

Materials and Methods

A systematic literature review focused on adults aged 18 and older from LMICs was conducted. The intervention included cancer screening tests for all types of cancer, regardless of their incidence or mortality rates. The analysis considered routine screening and early diagnosis strategies implemented in the countries where the cost-effectiveness studies were conducted, ensuring that the most appropriate comparator was the standard local practice.¹⁰ The primary outcomes assessed were the Incremental Cost-Effectiveness Ratio (ICER), Years of Life Saved (YLS), Disability-Adjusted Life Years (DALYs), Quality-Adjusted Life Years (QALYs), and the number of cases detected.

The study followed key elements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines (S1)¹¹ and incorporated relevant principles from the Cochrane Handbook for Systematic Reviews of Interventions.¹² Moreover, the Synthesis without Meta-Analysis (SWiM) reporting guideline for systematic reviews was applied,¹³ and the protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the code CRD42024539445.

Search strategy and selection criteria

On September 26, 2024, the literature search was conducted in PubMed, the Cochrane Library, Embase (Excerpta Medica dataBASE), EconLit, CINAHL (Cumulative Index to Nursing and Allied Health Literature), LILACS (Latin American and Caribbean Health Sciences Literature), Global Health, and the Web of Science Core Collection databases. A librarian developed the search strategy, which was adapted for the other databases. No language or time restrictions were applied. The authors reviewed and selected the search terms for PubMed and other databases, with input from a health economist to ensure their relevance. All search strategies are available in Supplementary Data. Duplicate records were removed following Bramer et al,¹⁴ using EndNote X9.

The review included cost-effectiveness studies on cancer screening and early diagnosis strategies in adult populations. Moreover, studies were required to compare these strategies with the standard screening and diagnostic practices in the respective study locations. The review also included studies conducted in LMICs, defined by the historical classification of the World Bank.¹⁵ Studies focusing on broader aspects of cancer care, such as treatment and disease management, were excluded. Studies that included multiple countries with aggregated results were also excluded if at least one of the countries was not classified as an LMIC. Studies unavailable in full-text format were also not considered.

Data search and extraction

The web-based application Rayyan was used for study selection.¹⁶ Two authors (A.H.-V. and R.V.-F.) independently screened titles and abstracts. They then independently assessed the full-text articles to evaluate their eligibility. Any disagreements were resolved through consensus, and if unresolved, a third researcher was consulted.

The following data were extracted: author, publication year, study design, study setting, funding source, analysis and model type, time horizon, perspective, model assumptions, discount rate, costing year and currency, effect of intervention and comparator, data sources for the intervention effect and other relevant parameters (costs and population size), health outcomes (YLS, DALYs, QALYs, and the number of cases detected), direct and associated medical cost of the intervention and comparator, indirect costs, ICER results, cost-effectiveness threshold or decision rule, sensitivity analysis, and conflicts of interest. Two authors independently extracted data using a structured matrix in Microsoft Excel. Disagreements were resolved by a third author. A pilot study was conducted using three studies to assess the accuracy and completeness of the data extraction matrix.

Quality assessment

The quality of the studies included was assessed using the checklist proposed by Drummond and Jefferson.¹⁷ Moreover, the La Torre et al scale was applied,¹⁸ which assigns weighted scores to each checklist item to generate a total quality score. Full details of the Drummond checklist and the assigned weights are available in S3.

Data analysis

A qualitative synthesis was conducted, providing a detailed description of the evidence included and addressing the following aspects: the characteristics of the studies included, including authors, study design, language, year, country, number and characteristics of participants, details of the intervention and comparator (location, duration, and features), method and timing of outcome assessment (both primary and additional outcomes), conflict of interest declarations, and funding source; the quality assessment of the studies; and the type of cancer and cost-effectiveness, when comparisons between studies were possible.

Results

A total of 12,670 records (titles and/or abstracts) were identified through electronic databases, as defined by PRISMA 2020 terminology. After removing duplicates, 10,861 records remained and were screened based on title and abstract. Of these, 61 reports were selected for full-text assessment. Most exclusions occurred due to the lack of compliance with the criterion of including routine screening and early diagnosis strategies. Twelve studies met the inclusion criteria.^19–30 The complete selection process is detailed in Figure 1.

FIG. 1.

Flowchart of study selection according to PRISMA. Record refers to a title and/or abstract retrieved from a database.¹¹ Report denotes any document (eg, article, preprint, abstract, or government report) describing a study.¹¹ Study refers to the actual investigation involving participants and defined interventions and outcomes, which may have multiple related reports.¹¹ PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

The characteristics of each study are reported in Table 1. Eleven studies were cost-effectiveness analyses, and most were published between 2020 and 2024. Seven studies were conducted in the Americas, three in Africa, two in the Western Pacific, and two in Southeast Asia. Eight studies were conducted in upper-middle-income countries, four in lower-middle-income countries, and only two in low-income countries.

Table 1.

Summary of the Characteristics of the Studies Included

Characteristics	Number of studies^a
Total	12
Publication year
2004–2007	1
2008–2011	2
2012–2015	3
2016–2019	2
2020–2024	4
WHO region^b
Europe	0
Americas	7
Western Pacific	2
Eastern Mediterranean	0
South-East Asia	2
Africa	3
Country income level^c
Low income	2
Low-middle income	4
Upper-middle income	8
Type of cancer
Cervical	8
Breast	2
Prostate	2
Study design
Cost-effectiveness studies	11
Cost-utility studies	1
Study setting
Single-country	11
Multi-country	1

Twelve studies were included. However, in some characteristics, countries from the multicountry study were listed separately.

Information obtained from: https://www.who.int/countries/.

Information obtained from reference.¹⁵

WHO, World Health Organization.

The studies examined the cost-effectiveness of various cancer screening strategies across different populations and settings (Table 2). Eight studies reported results on cervical cancer screening, assessing human papillomavirus (HPV) testing, cytology, or visual inspection with acetic acid (VIA).^{19–22,24,25,28,29} Of these, HPV testing was the primary intervention in seven studies.^{19–22,24,25,29} Comparators included conventional methods such as cytology (Pap smear), VIA, and DNA-based screening. These studies were conducted in Mexico,^19,24 Uganda,^20,21 Nicaragua,^21,22 India,^21,27 Argentina,²⁵ and South Africa.²⁹ Two studies included results on breast cancer screening and were conducted in Brazil and Peru.^23,26 One study evaluated digital breast tomosynthesis (DBT) as the intervention,²³ while the other assessed three screening strategies: breast self-examination, clinical breast examination, and mammography.²⁶ Prostate cancer screening was assessed in two studies, both conducted in China.^28,30 One study evaluated the Prostate Health Index (PHI) as the intervention,²⁸ while the other focused on prostate-specific antigen (PSA) testing.³⁰

Table 2.

Characteristics of Economic Evaluation Studies on Cancer Screening

Author; year	Population	Intervention	Comparator	Funding source
Beal et al. 2014¹⁹	Mexican women aged 35–64 covered by the Mexican Social Security Institute or the Ministry of Health	(a) Conventional Pap; (b) HR-HPV testing followed by triage with conventional Pap test for HPV+ women; (c) HR-HPV testing with molecular triage: HR-HPV test followed by HPV-16/18 genotyping, LBC triage, and immunostaining with p16/ki67 progression biomarkers for women with abnormal LBC; (d) co-testing: LBC and HR-HPV tests, followed by HPV-16/18 genotyping and immunostaining for p16/Ki67 progression biomarkers in women negative for HPV 16/18	Conventional Pap	NR
Campos et al. 2015²⁰	Ugandan women aged 35+	HPV DNA testing in two visits	VIA in a single visit	National Cancer Institute (R01CA160744)
Campos et al. 2017²¹	Women aged 35 (one-time screening) or 30–40 (three screenings)	HPV screening in two visits	HPV screening in two visits at a clinic with VIA triage for HPV-positive women	Partly funded by the Bill & Melinda Gates Foundation, OPP1053342
Campos et al. 2017²²	Women aged 30–59	(a) HPV testing every 5 years, with cryotherapy referral for HPV+ women eligible for treatment (“HPV-Cryo”); (b) HPV testing every 5 years, with VIA triage for HPV+ women (“HPV-VIA”); (c) HPV testing every 5 years, with Pap test triage for HPV+ women (“HPV-Pap”)	Pap test every 3 years, with colposcopy referral for women with ASC-US or worse (“Pap”)	Supported by the Bill & Melinda Gates Foundation
Couto et al. 2024²³	Women aged 40–69 eligible for breast cancer screening per Brazilian supplementary health system guidelines, with scattered fibroglandular densities and heterogeneously dense breasts (BI-RADS B and C), undergoing biennial mammographic screening	Digital breast tomosynthesis combined with synthesized 2D mammograms	Digital mammography	Partial financial support from Siemens Healthineers
Flores et al. 2011²⁴	Women attending the IMSS, aged 20–80, in Morelos	Self-sampling HPV and clinician-administered HPV testing, and clinician-administered Pap + HPV	Pap test	Funded by IMSS, the National Council for Science and Technology (grant #26267 M), the National Institute of Public Health, NIH (grant # U19 AI38533), and Digene Corporation
Garay et al. 2021²⁵	Women aged 30–65	HPV test with genotyping	Cytology	Funded by Roche Diagnostics
Gutiérrez-Aguado et al; 2012²⁶	Peruvian women aged 13+ (self-exam), 30+ (clinical exam), and 40+ (mammography)	Breast self-examination, clinical breast examination, and mammography	Breast self-examination	Self-funded
Legood et al. 2005²⁷	Rural women aged 30–59	VIA, cytology, and HPV DNA testing	VIA, cytology, and HPV DNA testing	Bill & Melinda Gates Foundation via the Alliance for Cervical Cancer Prevention (ACCP)
Teoh et al. 2020²⁸	Chinese men aged 50–75 with PSA 4–10 ng/mL and normal digital rectal exam	Prostate Health Index with TRUS-PB for PHI >35	PSA-based strategy	Health Medical and Research Fund—Research Fellowship Scheme 2017/18
Vijayaraghavan et al. 2009²⁹	Hypothetical cohort of 100,000 women starting at age 30 with the intervention	Screening with conventional cytology, HPV DNA, and co-testing (cytology + HPV)	Conventional cytology	Roche Molecular Systems, Inc
Zhao et al. 2020³⁰	Hypothetical cohort of 100,000 asymptomatic men aged 50–75	Population-based PSA screening with TRUS biopsy	Standard clinical diagnosis and TRUS in a health care	NR

ASC-US, atypical squamous cells of undetermined significance; BI-RADS, breast imaging-reporting and data system; HPV, human papillomavirus; HPV-Cryo, human papillomavirus-cryotherapy; HR-HPV, high-risk human papillomavirus; LBC, liquid-based cytology; IMSS, Mexican Social Security Institute; NR, not reported; Pap, Papanicolaou; PSA, prostate-specific antigen; TRUS, transrectal ultrasound; TRUS-PB, transrectal ultrasound-guided prostate biopsy; VIA, visual inspection with acetic acid.

The target population varied across studies: women aged 30–69 years in cervical and breast cancer studies and men aged 50–75 years in prostate cancer studies. Ten studies reported funding sources.^20–29 Three studies were funded by the Bill & Melinda Gates Foundation,^21,22,27 two by Roche,^25,29 and one by Siemens Healthineers.²³ The remaining studies received funding from the US National Cancer Institute, the Mexican Institute of Social Security, and the Health Medical and Research Fund, while one study was self-funded (Table 2).

Quality assessment

Most studies met a high number of quality criteria (Table 3), reflecting robust methodological design and appropriate result presentation in line with the Drummond and Jefferson guidelines.¹⁷ However, some limitations were identified, such as the lack of reporting on productivity changes and the absence of justification for variables and ranges in sensitivity analyses. Despite these issues, incremental analysis and outcome measures remained consistent across studies. Total scores, based on the weighting system proposed by La Torre et al,¹⁸ ranged from 98 to 112. The two studies with the lowest scores were those by Campos et al (98 points)²⁰ and Gutiérrez-Aguado et al (101 points).²⁶

Table 3.

Quality Assessment of Studies

Item	Beal et al. 2014¹⁹	Campos et al. 2015²⁰	Campos et al. 2017²¹	Campos et al. 2017²²	Couto et al. 2024²³	Flores et al. 2011²⁴	Garay et al. 2021²⁵	Gutiérrez-Aguado et al. 2012²⁶	Legood et al. 2005²⁷	Teoh et al. 2020²⁸	Vijayaraghavan et al. 2009²⁹	Zhao et al. 2020³⁰
The research question is stated	1	1	1	1	1	1	1	1	1	1	1	1
The economic importance of the research question is stated	1	1	1	1	1	1	1	1	1	1	1	1
The viewpoint(s) of the analysis are clearly stated and justified	1	0	1	1	1	1	1	1	1	0	1	1
The rationale for choosing alternative programs or interventions compared is stated	1	1	1	1	1	1	1	1	1	1	1	1
The alternatives being compared are clearly described	1	1	1	1	1	1	1	1	1	1	1	1
The form of economic evaluation used is stated	1	1	1	1	1	1	1	1	1	1	1	1
The choice of form of economic evaluation is justified in relation to the questions addressed	1	1	1	1	1	1	1	1	1	1	1	1
The source(s) of effectiveness estimates used are stated	1	1	1	1	1	1	1	1	1	1	1	1
Details of the design and results of the effectiveness study are given (if based on a single study)	1	1	1	1	1	1	1	1	1	1	1	1
Details of the methods of synthesis or meta-analysis of estimates are given (if based on a synthesis of a number of effectiveness studies)	1	1	1	1	1	1	1	1	1	1	1	1
The primary outcome measure(s) for the economic evaluation are clearly stated	1	1	1	1	1	1	1	1	1	1	1	1
Methods to value benefits are stated	1	1	1	1	1	1	1	1	1	1	1	1
Details of the subjects from whom valuations were obtained were given	1	1	1	1	1	1	1	1	1	1	1	1
Productivity changes (if included) are reported separately	0	0	0	0	0	0	0	0	0	0	0	0
The relevance of productivity changes to the study question is discussed	0	0	0	0	0	0	0	0	0	0	0	0
Quantities of resource use are reported separately from their unit costs	1	1	1	1	1	1	1	1	1	1	1	1
Methods for the estimation of quantities and unit costs are described	1	1	1	1	1	1	1	1	1	1	1	1
Currency and price data are recorded	1	1	1	1	1	1	1	1	1	1	1	1
Details of currency or price adjustments for inflation or currency conversion are given	1	1	1	1	1	1	1	1	1	1	1	1
Details of any model used are given	1	1	1	1	1	1	1	1	1	1	1	1
The choice of model used and the key parameters on which it is based are justified	1	1	1	1	1	1	1	1	1	1	1	1
Time horizon of costs and benefits is stated	1	1	1	1	1	1	1	1	1	1	1	1
The discount rate(s) is stated	1	1	1	1	1	1	1	1	1	1	1	1
The choice of discount rate(s) is justified	1	1	1	1	1	1	1	1	1	1	1	1
An explanation is given if costs and benefits are not discounted	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Details of statistical tests and confidence intervals are given for stochastic data	1	1	1	1	1	1	1	1	1	1	1	1
The approach to sensitivity analysis is given	1	0	1	1	1	1	1	1	1	1	1	1
The choice of variables for sensitivity analysis is justified	1	0	1	1	1	1	1	1	1	1	1	1
The ranges over which the variables are varied are justified	1	0	1	1	1	1	1	1	1	1	1	1
Relevant alternatives are compared	1	1	1	1	1	1	1	1	1	1	1	1
Incremental analysis is reported	1	1	1	1	1	1	1	1	1	1	1	1
Major outcomes are presented in a disaggregated as well as aggregated form	1	1	1	1	1	1	1	0	1	1	1	1
The answer to the study question is given	1	1	1	1	1	1	1	1	1	1	1	1
Conclusions follow from the data reported	1	1	1	1	1	1	1	0	1	1	1	1
Conclusions are accompanied by the appropriate caveats	1	1	1	1	1	1	1	0	1	1	1	1
Total score	112	98	112	112	112	112	112	101	112	108	112	112

NA, not applicable.

Assumptions of parameters

Six studies adopted a health system perspective,^19,23–27 four applied a societal perspective,^21,22,29,30 and two did not report their perspective.^20,27 Four studies used Monte Carlo simulation to run the cost-effectiveness model,^19–22 three applied Markov models,^25,26,30 one employed a decision tree,²⁴ and one used nonparametric bootstrapping.²⁷ The time horizon varied across studies. Four studies, particularly those focusing on cervical cancer screening strategies, adopted a lifetime horizon.^20–22,29

For data sources on effectiveness and costs, the studies incorporated previous literature, specific studies (eg, START-UP, Scale-Up, To-Be, and a cluster-randomized controlled trial), cost data from National Institutes of the respective countries, and private sector sources such as Roche. Most studies used QALY as the cost-effectiveness measure.^{23,26,28–30} Other studies considered alternative measures such as YLS,^21,25 cases detected or avoided,¹⁹ and cancer incidence or risk reduction.^20,22,27 One study did not report the cost-effectiveness measure used (Table 4).²⁴

Table 4.

Parameters Used in Studies

Author; year	Type of economic evaluation	Perspective	Model type	Time horizon	Discount rate	Source of effectiveness and cost	Cost-effectiveness measure	Sensitivity analysis
Beal et al; 2014¹⁹	Cost-effectiveness	Perspective of the Mexican Social Security Institute (IMSS) and the Mexican Ministry of Health	Monte Carlo simulation	Three- or five-year period for screening a cohort of women	5% per year	Literature and information from IMSS or the Ministry of Health (SSa)	Avoided undetected cases	Probabilistic
Campos et al; 2015²⁰	Cost-effectiveness	NR	Monte Carlo simulation	Lifetime assessment from age 35	3% per year	Literature	Cancer incidence	NR
Campos et al; 2017²¹	Cost-effectiveness	Societal perspective (including direct and indirect medical costs, such as transportation and patient time)	Monte Carlo simulation	Lifetime	3% per year	START-UP study	Per YLS	For each country, the top 50 parameter sets that best fit epidemiological data were selected for analysis as a form of probabilistic sensitivity analysis
Campos et al; 2017²²	Cost-effectiveness	Societal perspective, including costs regardless of payer, to capture the opportunity cost of resources used in screening intervention	Monte Carlo simulation	Lifetime	3% per year	Literature, START-UP study, and Scale-Up	Cancer risk	Sensitivity analysis was conducted to assess the impact of independently varying uncertain parameters, including Pap test performance, triage test performance in HPV-positive women, colposcopy performance, screening coverage, adherence to visits, eligibility for cryotherapy after a positive screening and triage test, treatment effectiveness, discount rate, and cost data
Couto et al; 2024²³	Cost-effectiveness	Health care system perspective	Monte Carlo simulation and hybrid model: Markov model and decision tree	30 years	5% per year	To-Be study and the National Health Surveillance Agency	Per QALY gained and YLS	Multivariate probabilistic analysis
Flores et al; 2011²⁴	Cost-effectiveness	Health care system perspective	Decision tree	One-year time horizon for this CEA	3% per year	Literature	NR	Univariate analysis
Garay et al; 2021²⁵	Cost-effectiveness	Argentine health care system	Markov model	The reference time horizon for cost-effectiveness analysis is 10 years, but results for 5 and 20 years are also reported	Results were calculated considering discount rates of 0% and 5%, as per local recommendations	Literature, national projections from the National Institute of Statistics and Censuses, and the Institute for Clinical Effectiveness and Health Policy	Per YLS	Deterministic and probabilistic analyses
Gutiérrez-Aguado et al; 2012²⁶	Cost-utility analysis	Payer perspective (Ministry of Health—MINSA)	Markov model	40 years	5% per year	Literature and estimates from MINSA	Per QALY gained	Included a tornado analysis, identifying mammography costs as sensitive
Legood et al; 2005²⁷	Cost-effectiveness analysis	Health care system perspective	Nonparametric bootstrapping	NR	3% per year	RCT	Detected cases	Univariate analysis
Teoh et al; 2020²⁸	Cost-effectiveness analysis	NR	Markov model with decision tree	25 years	3% per year	Literature and health care system costs	Per QALY gained	Univariate and probabilistic analysis
Vijayaraghavan et al; 2009²⁹	Cost-effectiveness analysis	Societal perspective	Markov model with Monte Carlo simulation	Lifetime from age 13	3% per year	Literature, South Africa’s Uniform Patient Fee Schedule, and Roche	Per QALY gained	Univariate analysis, based on progression rates and costs
Zhao et al; 2020³⁰	Cost-effectiveness analysis	Societal perspective	Markov model	25 years	3.5% per year	Literature and local data from 16 hospitals in Shandong	Per QALY gained and YLS	Univariate analysis, key factors include primary care costs and diagnosis rates by grade

CEA, cost-effectiveness analysis; HPV, human papillomavirus; MINSA, Ministry of Health (Peru); NR, not reported; PSA, probabilistic sensitivity analysis; QALY, Quality-Adjusted Life Years; RCT, randomized controlled trial; YLS, Years of Life Saved.

Cost-effectiveness and outcomes

The studies reported costs in different currencies and cost years, reflecting heterogeneity in health care systems and economic conditions. Therefore, the cost figures presented are descriptive and not directly comparable across countries. Reported costs were expressed in US dollars (USD), international dollars (I$), or euros (€), depending on the study and economic setting. Six studies reported costs in USD.^{19,22,24,26–28} Direct medical costs varied by intervention, country, and economic context. For cervical cancer screening, high-risk human papillomavirus (HR-HPV) testing ranged from $29.91 USD (individual test) to $43.25 USD (combined tests). In Uganda, VIA costs 8.78 I$, while in South Africa, conventional cytology and HPV testing cost $6609 USD and $11,799 USD per 1000 women, respectively. For breast cancer screening, mammography costs $35.4 USD, making it more affordable than DBT, which costs €334.86. For prostate cancer screening, the PHI had the highest cost at $369.54 USD, exceeding PSA testing ($84.74 USD) (Table 5).

Table 5.

Cost-Effectiveness Results of Studies

Author; year	Costing year and currency	Direct medical cost	ICER	Cost-Effectiveness threshold	Conclusions
Beal et al; 2014¹⁹	2013, USD	HR-HPV ($29.91), Co-testing ($43.25), HR-HPV with molecular triage ($41.04)	(a) HR-HPV + Pap: −$108.99 per avoided undetected case, (b) HR-HPV + molecular triage: −$819 per avoided undetected case, (c) co-testing: −$537 per avoided undetected case	Cost-effectiveness acceptability curves considering a WTP range of $0–$3000	HR-HPV testing has advantages as a primary screening modality. Epidemiological studies and cross-sectional comparisons support its benefits, but large trials are needed to evaluate its impact on cervical cancer incidence and mortality
Campos et al; 2015²⁰	2005, I$	$10.22	When sensitivity was low (40% for VIA; 70% for HPV DNA test), VIA cost I$220 per YLS and HPV DNA test I$300 per YLS. ICERs decreased as sensitivity increased, with HPV DNA test at 90% sensitivity costing I$260 per YLS vs. VIA at 60% sensitivity (I$140 per YLS)	An ICER below the per capita GDP was “highly cost-effective,” while below three times the GDP was “cost-effective” (I$1165)	This framework highlights trade-offs and key variables influencing cervical cancer screening cost-effectiveness in resource-limited settings. Decision-makers can improve screening outcomes by considering these trade-offs during program planning and early evaluation
Campos et al; 2017²¹	2011, I$	India: $9.24, Nicaragua: $15.61, Uganda: $8.78	ICERs by country:(1) India: One-time HPV-VIA screening had the lowest ICER (I$240 per YLS). One-time HPV-only screening was more costly but more effective (I$460 per YLS). Three-time HPV-VIA screening cost I$770 per YLS, and three-time HPV-only screening cost I$840 per YLS. Both were “highly cost-effective” in India (GDP per capita: I$5750), with HPV-only reducing cancer risk by an additional 4.2%.(2) Nicaragua: One-time HPV-only screening was cost-effective, while three-time HPV-only screening cost I$200 per YLS, below Nicaragua’s GDP per capita (I$4960).(3) Uganda: One-time HPV-only screening cost I$130 per YLS, and three-time HPV-only screening cost I$410 per YLS, both “highly cost-effective” (GDP per capita: I$1690)	An ICER below the per capita GDP was “highly cost-effective”; below three times GDP was “cost-effective”	The study emphasizes the need for accessible treatment for HPV-positive women in low-resource settings. Without adequate treatment availability, HPV screening and treatment strategies are not viable. HPV triage strategies should include improved genotype restriction, biomarkers, and predictive triage tests adaptable to low-resource settings
Campos et al; 2017²²	2015, USD	(a) HPV screening every 5 years with cryotherapy referral: $18.16, (b) HPV screening every 5 years with VIA triage: $4.19, (c) HPV screening every 5 years with Pap triage: $11.96	If HPV-Cryo was unavailable, HPV-VIA was the most cost-effective and effective strategy in the base case and most sensitivity analyses, with an ICER of $550 per YLS. HPV-Cryo was both less costly and more effective than all other strategies, dominating HPV-VIA, HPV-Pap, and Pap. With an ICER of $320 per YLS, HPV-Cryo every 5 years was “highly cost-effective” given Nicaragua’s per capita GDP ($2090)	An ICER below Nicaragua’s 2015 GDP per capita ($2090) was “highly cost-effective,” and below three times GDP was “cost-effective”	HPV testing is more cost-effective than Pap in Nicaragua due to higher sensitivity and fewer required visits. Increasing compliance with follow-up will further improve health benefits and resource efficiency
Couto et al; 2024²³	2023, Euros	€334.86	DBT + s2D was dominant for YLG and QALYs compared with digital mammography	The public health system WTP threshold in Brazil is €7200 per QALY	Cost-effectiveness analysis suggests DBT + s2D screening for women aged 40–69 with scattered fibroglandular density and heterogeneously dense breasts (BI-RADS B and C) is a potentially cost-effective alternative to digital mammography alone
Flores et al; 2011²⁴	2008, USD	Self-HPV: $14.15, Clinician-HPV: $20.06, Pap + Clinician-HPV: $26.18	Three viable screening strategies: (a) Pap + Clinician-HPV in women aged 30–80, (b) Clinician-HPV in women aged 30–80, and (c) Pap + Clinician-HPV in women aged 20–80. Self-HPV, Pap alone, and no-screening were dominated in both age groups	NR	HPV testing could be a cost-effective screening alternative for large health care organizations like IMSS. Findings may help policymakers integrate HPV testing into IMSS’s cervical cancer screening program
Garay et al; 2021²⁵	2020, ARS	AR$3250	ICER: AR$329,042 per YLG (discount rate: 5%)	Cost-effectiveness threshold: 1 per capita GDP	HPV genotyping-based screening is likely the most cost-effective option compared with conventional cytology in Argentina
Gutiérrez-Aguado et al; 2012²⁶	2011, USD	Breast self-exam: No cost. Clinical breast exam: $9.60 (primary care), $24.50 (secondary/tertiary). Mammography: $35.40 per patient (including consultation and mammogram)	Mammography cost: $35.93, QALY: 0.3963	Considered cost-effective under per capita GDP threshold ($4200)	Mammography is more cost-effective than other preventive strategies
Legood et al; 2005²⁷	2002, USD	VIA: $3917 per 1000 women, Cytology: $6609, HPV: $11,799	ICERs per 1000 women: Cytology vs. IVA: $2691; HPV vs. VIA: $7881; HPV vs. Cytology: $5190	NR	Cytology is more effective but costlier than VIA. HPV is not cost-effective at current prices
Teoh et al; 2020²⁸	2019, USD	Urology clinic visit: $195.60, PSA test: $84.74, PHI test: $369.54	ICER: $13,056.56, showing PHI dominance over PSA	$138,649/QALY (three times Hong Kong’s per capita GDP)	PHI is more cost-effective than PSA for prostate cancer screening in Chinese men
Vijayaraghavan et al; 2009²⁹	2006, ZAR	Clinical visit: R163 ($24), Cytology: R65 ($10), HPV test: R200 ($30), Colposcopy/biopsy: R280 ($42)	ICERs vs. Cytology: HPV + Cytology triage: R8286; HPV + Colposcopy: R6534; HPV + Cytology co-testing: R8040	1–3× per capita GDP (R5380 in 2006) considered “highly cost-effective”	HPV screening is more effective than cytology and should be implemented
Zhao et al; 2020³⁰	2018, CNY	PSA: CNY 145.5, TRUS biopsy: CNY 720.8	14,747.11 CNY/QALY, 16,470.45 CNY/YLG	WTP threshold: 64,520 CNY/QALY (per capita GDP)	PSA-based screening is cost-effective for healthy Chinese men with life expectancy >10 years

ARS, Argentine Peso; CNY, Chinese Yuan; DBT, digital breast tomosynthesis; EUR, Euro; GDP, gross domestic product; HPV-Cryo, human papilloma virus-cryotherapy; I$, international dollars; ICER, Incremental Cost-Effectiveness Ratio; IMSS, Mexican Social Security Institute; NR, not reported; PHI, Prostate Health Index; PSA, prostate-specific antigen; QALY, Quality-Adjusted Life Year; USD, US dollar; VIA, visual inspection with acetic acid; WTP, willingness to pay; YLG, Years of Life Gained; YLS, Years of Life Saved; ZAR, South African Rand.

Cervical cancer

Eight studies assessed cervical cancer screening strategies (Table 5). Beal et al reported that HR-HPV dominated conventional Pap, with an ICER of −$108.99 USD and −$537 USD for combined strategies.¹⁹ Campos et al compared HPV testing in two visits versus HPV testing with VIA triage for HPV-positive women across India, Nicaragua, and Uganda.²¹ This study found ICERs from I$130 (one-time HPV) to I$840 (three rounds of HPV screening) per YLS, highlighting the superior cost-effectiveness of HPV over VIA. In another study, Campos et al compared various screening strategies, concluding that HPV-Cryotherapy (Cryo) every 5 years was dominant, with an ICER of $320 USD per YLS.²² Flores et al evaluated self-collected HPV, physician-administered HPV, and Pap tests, concluding that self-sampling could be a cost-effective option in Mexico.²⁴ Garay et al reported that HPV genotyping had an ICER of 329,042 AR$ per YLS, exceeding conventional cytology.²⁵ Leegod et al found ICERs of $2691 USD (cytology vs. VIA) and $7881 USD (HPV vs. VIA), concluding that HPV was not cost-effective.²⁷ Vijayaraghavan et al determined that HPV screening was more effective than cytology but less cost-effective, with ICERs ranging from R6534 to R8286.²⁹

Breast cancer

Two studies examined breast cancer screening strategies (Table 5). Couto et al evaluated DBT + synthetic 2D mammography versus digital mammography, concluding that DBT + synthetic 2D was dominant for QALYs and YLS, making it more cost-effective for women aged 40–69 with high breast density.²³ Gutiérrez-Aguado et al compared breast self-examination, clinical breast examination, and mammography, concluding that mammography was the most cost-effective ($35.93 USD per QALY, with a $4200 USD threshold).²⁶

Prostate cancer

Two studies explored prostate cancer screening strategies (Table 5). Teoh et al concluded that PHI with Transrectal Ultrasound-Guided Prostate Biopsy (TRUS-PB) was more cost-effective than PSA, with an ICER of −$13,056.56 USD per QALY.²⁸ Zhao et al compared population screening with standard diagnosis using TRUS-PB, reporting ICERs ranging from 14,747.11 to 16,470.45 CNY per QALY/YLS.³⁰ They concluded that PSA screening was cost-effective for men with a life expectancy exceeding 10 years.³⁰

Discussion

This systematic review on cost-effective strategies for cancer screening and early diagnosis in LMICs consolidates existing evidence on the cost-effectiveness of cervical, breast, and prostate cancer screening tests across nine countries in four world regions. These findings underscore the critical importance of cost-effective screening tests in controlling the cancer burden and achieving the Sustainable Development Goal 3.4, which aims to reduce premature mortality from noncommunicable diseases by one-third by 2030 through prevention strategies.³¹

Cervical cancer screening strategies were the most frequently analyzed, followed by breast and prostate cancer evaluations. This concentration is expected, as cervical cancer remains a leading cause of mortality in resource-limited settings. In 2019, cervical cancer mortality in middle-income countries was three times higher than in HICs.³² A similar pattern was observed in DALYs and years of life lost. The findings indicate that HPV DNA tests, VIA, and combined screening strategies were the most cost-effective approaches in various contexts, including Uganda, Nicaragua, India, South Africa, and Mexico, due to high sensitivity, low cost, and feasibility in low-resource settings. These results align with a previous systematic review on the cost-effectiveness of cervical cancer screening strategies in LMICs, which reported that HPV testing and VIA were more cost-effective than cytology.⁹ Another review focused on India found VIA to be the most cost-effective strategy, a conclusion consistent with the findings of the current study, in which HPV with VIA emerged as the most cost-effective strategy in this specific setting. Furthermore, systematic reviews from Europe³³ and those including studies irrespective of country income classification³⁴ reported similar findings, reinforcing the cost-effectiveness of HPV testing and VIA in both LMICs and HICs.

Studies conducted in Brazil and Peru identified DBT combined with mammography as a promising technology. However, its adoption in LMICs faces significant economic barriers. Moreover, industry funding from device manufacturers may introduce bias in study outcomes, as seen in previous DBT-related studies.³⁵ For instance, the authors reported that DBT was the new technology evaluated for breast cancer detection in the general population.³⁵ Still, despite minimal QALY gains and wide cost variations, studies assessing this strategy had conflicts of interest. In contrast, a Peruvian study concluded that annual mammography was more cost-effective compared with other screening strategies,²⁶ although evidence suggests that biennial screening is more cost-efficient.³⁵ While DBT remains a promising technology, further low-bias studies are needed to assess its feasibility in LMIC health care systems.

For prostate cancer, studies from China and Hong Kong indicated that the PHI is more cost-effective than PSA, suggesting potential optimization opportunities in clinical practice.³⁶ However, previous systematic reviews indicate that the cost-effectiveness of prostate cancer screening remains uncertain in both LMICs and HICs.³⁶ Another systematic review highlighted new screening methods, including PHI, TRUS, and urinary proteome analysis, as potentially more cost-effective than standard PSA testing.³⁷ However, that review also noted key limitations, such as lack of cancer staging, absence of sensitivity analyses, and short time horizons (≤3 years).³⁷ Although the study by Teoh et al applied a 25-year time horizon, it presented other limitations, including lack of information on the economic analysis perspective and exclusion of cancer stage, which limits the interpretability of its findings.²⁸

The results of the present study emphasize the need to tailor screening strategies to local realities. In resource-limited settings, prioritizing cost-effective interventions is crucial to maximize the impact on cancer mortality and morbidity reduction. A combination of affordable technologies (such as VIA and HPV testing), innovative approaches, and improved health care access could significantly enhance early detection and timely treatment. However, there is a marked lack of cost-effectiveness studies for other cancers in LMICs. Further research on oral, esophageal, gastric, colorectal, lung, and other high-mortality cancers is essential to address specific public health needs and to inform comprehensive policy development aimed at reducing the disease burden in LMICs.

This study has several limitations that should be considered. First, cost-effectiveness analyses are context-dependent, meaning their results are only applicable to the specific settings in which they were conducted and cannot be extrapolated to other regions. Second, the studies included exhibit heterogeneity in economic models, analytical perspectives (health care provider vs. societal), and cost-effectiveness thresholds, making direct comparisons difficult. Moreover, there is a research bias toward cervical cancer screening, while other cancers, such as colorectal and lung cancer, are underrepresented, restricting the applicability of these findings to a broader range of public health needs. Another key limitation is that some of the strategies evaluated require advanced technological infrastructure and robust health care systems, which may not be scalable across all LMICs. Furthermore, data limitations and assumptions—such as health utilities for QALY calculations—may have influenced economic outcomes in certain studies, potentially affecting result generalizability. Finally, although the studies included span a broad timeframe (2005–2024), some analyses may be outdated due to the rapid evolution of screening and diagnostic technologies.

Conclusion

This systematic review highlights that cost-effective, viable, and adaptable strategies exist for cancer screening and early diagnosis in LMICs. HPV DNA testing, VIA, and combined screening approaches are the most cost-effective interventions for cervical cancer, offering an optimal balance of low cost and high effectiveness. DBT combined with mammography for breast cancer and the PHI for prostate cancer show promising results, although they require greater investment and technical capacity. Implementation decisions must consider local infrastructure, available resources, and disease burden in each context. Prioritizing cost-effective cervical cancer interventions should remain a core strategy, given their high potential impact in LMICs.

Authors’ Contributions

Mr. Hernández-Vásquez, MSc Villar Bernaola, and Mr. Timaná Ruiz contributed to conceptualization and methodology; Mr. Hernández-Vásquez, Mr. Vargas-Fernández, and MSc Villar Bernaola performed validation; Mr. Hernández-Vásquez, Vargas-Fernández, and MSc Villar Bernaola conducted formal analysis, investigation, data curation, resource acquisition, software implementation, and visualization; Mr. Hernández-Vásquez, Mr. Vargas-Fernández, and MSc Villar Bernaola contributed to the screening of studies and quality Assessment; MSc Villar Bernaola and Mr. Timaná Ruiz supervised the study; Mr. Hernández-Vásquez and Mr. Vargas-Fernández wrote the original draft; and all authors participated in reviewing and editing the article. All authors read and approved the final version for publication. The corresponding author is the guarantor.

Footnotes

Acknowledgments

The authors thank the Universidad Científica del Sur for their support in the publication of this research as well as Donna Pringle for reviewing the language and style. To librarian Daniel Comandé for conducting the literature searches across the various databases.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this work.

Supplemental Material

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