Cost of breast cancer care in low and middle-income countries: a scoping review protocol

Abstract

Objective:

This review will describe the scope of the literature on the cost of breast cancer care in low- and middle-income countries and summate the methodological characteristics and approaches of these economic evaluations.

Introduction:

In the past decade, there has been global momentum to improve capacity for breast cancer care in low- and middle-income countries, which have higher rates of breast cancer mortality compared to high-income countries. Understanding the cost of delivering breast cancer care in low- and middle-income countries is critical to guide effective cancer care delivery strategies and policy.

Inclusion criteria:

Studies that estimate the cost of breast cancer diagnosis and treatment in low- and middle-income countries will be included. Studies not available in English will be excluded.

Methods:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Review guidelines will be utilized. The search strategy has been developed in consultation with a medical librarian and will be performed in five electronic databases from their inception (MEDLINE, Embase, Web of Science, Global Health, WHO Global Index Medicus) as well as in gray literature sources. Two independent reviewers will review all abstracts and titles in the primary screen and full-text articles in the secondary screen. A third reviewer will adjudicate conflicts. One reviewer will perform data extraction. Study demographics, design, and methodological characteristics (such as costing perspective, time horizon, and included cost categories) will be summarized in narrative and tabular formats. The methodological quality of studies will be evaluated using a validated economic evaluation tool.

Introduction

Breast cancer is the most commonly diagnosed cancer among women worldwide and the leading cause of cancer death in over 100 countries.¹ In 2018, there were an estimated 2.1 million new breast cancer cases and 627,000 breast cancer deaths.¹ These deaths disproportionately occur in low- and middle-income countries (LMICs), where breast cancer mortality rates are rapidly increasing.² The regions with the highest mortality to incidence ratios are Africa (0.47), South-Central Asia (0.48), and Melanesia (0.48).² These poor outcomes reflect a large proportion of women in LMICs who present with advanced disease and have limited access to diagnosis and treatment.³

Many of the medicines used to treat early breast cancer are effective and available at low cost.⁴ If effective breast cancer diagnostics and treatments are appropriately deployed in LMICs, they could save women many life years. Cancer programs established in low-resource settings have demonstrated the feasibility of cancer care delivery in LMICs,⁵ but questions regarding the affordability of cancer care in low-resource settings continue to impede efforts to expand care. Understanding the cost drivers of delivering high-quality cancer care in LMICs is integral for strategic investment and effective cancer control policies. Accurate costing data are also necessary for cost-effectiveness and budget impact analyses, which can inform a variety of resource allocation decisions in LMICs.

Prior systematic reviews of breast cancer cost in LMICs have largely focused on screening programs and have noted a lack of strong evidence to provide specific recommendations.^6–8 Systematic reviews that capture the cost of breast cancer diagnosis or treatment in LMICs are limited, as they consider the cost-effectiveness of specific chemo- and biologic therapies or focus on specific geographic regions.^4,9–11 A recent systematic review of the cost of breast cancer care in LMICs by Zelle et al. was published in 2013.¹² Zelle et al. searched three databases and reported that breast cancer costing studies in LMICs are often underdeveloped and vary in their approach to cost estimation. The majority of economic analyses captured by this review estimated the incremental cost or cost-effectiveness of a singular diagnostic or therapeutic step (eg, cost of trastuzumab), rather than the cost of multiple steps in the breast cancer care pathway (eg, cost of multiple treatment modalities across breast cancer stages). The focus on incremental cost may limit these studies’ applicability given that the breast cancer care pathway is complex and involves multiple diagnostic and therapeutic steps.

Since 2013, LMICs have made major strides in building capacity to diagnose and treat breast cancer, including the development of cancer centers in low-resource settings as well as expanded access to inexpensive drugs and novel diagnostic technologies.^13–16 In addition, there has been a substantial increase in the number of breast cancer–costing studies in LMICs, some of which now extend beyond incremental costing of singular steps to include multiple steps in the breast cancer care pathway.^17–24 To capture these new studies, reflect the changing landscape of breast cancer care in LMICs, and guide research priorities, we aim to provide an updated summation and scoping of the literature. In addition, we aim to present a more in-depth characterization of studies that capture multiple steps in the breast cancer care pathway, as these studies offer an opportunity for more detailed cross study comparisons of cost comprehensiveness.

In this protocol we describe a scoping review of the literature on the cost of breast cancer diagnosis and treatment in LMICs. This review will help identify world regions where breast cancer costing studies are lacking, reveal gaps in the quality and cost categories included in breast cancer economic evaluations, and encourage researchers to disseminate and utilize transparent costing tools in LMICs. The availability of more comprehensive and comparable costing data may empower LMICs to develop relevant and sustainable breast cancer control policies, A preliminary search of PROSPERO, MEDLINE, the Cochrane Database of Systematic Reviews, and JBI Evidence Synthesis was conducted, and no current or in-progress scoping or systematic reviews on the topic were identified.

Review questions

1. What is the extent of the literature on costs of breast cancer care in LMICs and what are existing gaps in the literature?

2. What methodological approaches have been applied to evaluate the cost of breast cancer care in LMICs?

3. What cost categories and inputs are included in studies that estimate the cost of multiple steps in the breast cancer care pathway, and how do included categories compare across studies?

4. What is the quality of economic evaluation for studies that estimate the cost of multiple steps in the breast cancer care pathway?

Inclusion criteria

Participants

This review will consider studies that include women 18 years and older who received care for a breast malignancy of any stage (Stage I-IV) or subtype (hormone-receptor, human epidermal growth factor-2 [HER2]).

Concept

This review will characterize and evaluate the costing approaches of studies that report any economic outcome for a breast cancer diagnosis or treatment intervention in a LMIC. All interventions or comparators related to breast cancer diagnosis or treatment will be considered. Studies with any cost outcome (cost analysis, cost-minimization, cost-effectiveness, cost-utility, or cost-benefit analyses), cost category (direct medical, non-medical direct costs, indirect costs), or costing perspective (health care, patient, or societal) will also be considered. However, studies that quantify the cost of breast cancer screening, palliative care, or mortality in isolation, or studies that do not include any original cost analysis will be excluded. In addition, studies that calculate aggregate cost for several cancers or world regions, but do not stratify costs for breast cancer in LMICs will be excluded.

Context

This review will consider studies across health care settings including primary, secondary, and tertiary levels.²⁵ Studies in any LMIC, as defined by 2020 World Bank Classifications, will be considered.²⁶

Types of studies

Empirical and model-based studies with any type of economic analysis will be included. Articles published in five databases (MEDLINE [Ovid], Embase [Elsevier], Web of Science [Clarivate Analytics], Global Health [EBSCO], and WHO Global Index Medicus) as well as gray literature will be included. Reviews, conference abstracts without full manuscripts, case reports, commentaries and editorials will be excluded.

Methods

The proposed review will be conducted in accordance with the JBI methodology for scoping reviews.²⁷ The Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review (PRISMA-ScR) will also be referenced to ensure that all suggested reporting items are included.²⁸

Search strategy

The search strategy will aim to locate both published and unpublished primary studies. An initial limited search of MEDLINE was undertaken to identify articles on the topic. In consultation with a medical librarian, the text words in the titles and abstracts of relevant articles and the index terms used to describe the articles were used to develop a full search strategy. MEDLINE (Ovid), Embase (Elsevier), Web of Science (Clarivate Analytics), Global Health (EBSCO), and WHO Global Index Medicus were searched from their inception to March 19, 2020. The search employed Medical Subject Headings related to breast neoplasms, costing, and LMICs (based on 2020 World Bank classifications).²⁶ Our search of these five databases provided 6340 results, which after removal of duplicated records yielded 3854 papers. Language constraints will not be used in the search. The complete search strategy used for each database is outlined in Appendix I.

Sources of unpublished studies and gray literature, such as the Breast Global Health Initiative, Disease Control Priorities 3rd edition, and the World Health Organization, will also be searched for relevant articles. The reference lists of included articles will be also screened for additional papers.

Study selection

Following the search, all identified records will be collated and uploaded to Covidence (Veritas Health Innovation, Melbourne, Australia) and duplicates removed. Following a pilot test, titles and abstracts will then be screened by two independent reviewers for assessment against the inclusion criteria (primary screen). Non-English abstracts will be reviewed during the primary screen using automated computerized translation of their titles and abstracts. Relevant papers will be retrieved and two independent reviewers will assess the full texts in detail against the inclusion and exclusion criteria (secondary screen). Reasons for exclusion of all excluded full-text papers will be recorded and reported. Non-English, full-text articles will be excluded at this stage. The number of studies excluded in the secondary screen due to unavailability of English full text will be used to assess the review’s language bias. Any disagreements that arise between the reviewers at each stage of the selection process will be resolved through discussion or with a third reviewer. The results of the search and screening will be reported in full in the final scoping review and presented in a PRISMA-ScR flow diagram.²⁸

Data extraction

Data will be extracted from papers included in the scoping review by one reviewer using a data extraction tool developed by the research team (Appendix II). The data extraction tool will be iteratively modified as necessary during the process of extracting data from included papers. Modifications will be detailed in the full scoping review. Authors of papers will be contacted to request missing or additional data, where required. All studies will undergo data extraction for variables related to study characteristics: world region, economic status (upper-middle income, lower-middle income, low income), design (cost analysis, cost of illness, cost-effectiveness, cost-utility, cost-minimization analysis), breast cancer stage (early [stage I and II], advanced [stage III and IV]), breast cancer subtype (hormone-receptor, HER2), intervention (diagnosis, treatment, diagnosis and treatment), costing perspective (health care provider, health care payer, patient, societal), and time horizon (Appendix II).²⁶ Studies that estimated the cost of multiple steps in the breast cancer care pathway will undergo additional data extraction in order to provide a more in-depth understanding of the cost inputs and cost analysis approaches used in these studies. The additional variables related to cost estimation include: costing approach (micro-costing, gross-costing), cost categories (direct medical, direct non-medical, indirect costs), cost inputs for each cost category, data sources for cost estimation (patients, medical records, hospital data, government data, claims data, literature, expert opinion), cost disaggregation by stage, cost disaggregation by input, currency details, cost discounting, inflation adjustments, uncertainty estimation (eg, range, standard deviation, confidence interval), sensitivity analysis, and quality assessment (Appendix II).

Assessment of methodological quality

Quality assessment will be performed using an established 35-point checklist by Drummond et al.²⁹ Similar to previous reviews of economic evaluation, items not applicable to any of the included costing studies will be removed.^4,12 A three-point response scale will be used to grade the quality of each checklist item, ranging from 0 (not considered), through 1 (partially considered), to 2 (fully considered).³⁰ The sum of scores for each study will be compared with the maximum attainable score to calculate the percentage of the maximum attainable score. A study will be considered to be of high (>70%), medium (50% to 70%), or poor (<50%) quality based on these percentages.³⁰ All data collection will be performed using the data collection instrument REDCap (Vanderbilt University, Nashville, USA).³¹

Data analysis and presentation

The collected data from each study will be summarized in five tables as outlined in Appendix III. The study demographics, design, and additional study characteristics of all reviewed studies as well as their purpose and conclusions will be summarized in Table Shell 1 and 2. A comparison of these study characteristics (such as world region, economic status, economic evaluation type, costing perspective, and time horizon) will also be described in text. The extended methodological variables for studies that estimate the cost of multiple steps in the breast cancer care pathway will be summarized in Table Shell 3. The data in Table Shell 3 (such as included cost categories, cost inputs, cost sources, and costing approach) will also be described and compared across studies in text. Furthermore, the methodological appraisal of these studies and the score breakdown of the Drummond et al. checklist will be reported in Table Shell 4.²⁹ The aggregate methodological characteristics of these studies will also be presented in Table Shell 5. A narrative summary of the commonly missed components of the Drummond et al. checklist will accompany the tabulated results.²⁹

Appendix I: Search strategy

Five Electronic Databases (database inception – 3/19/20)

Total: 6340; After duplicate removal: 3854

MEDLINE (Ovid)

Ovid MEDLINE(R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Daily and Versions(R) 1946 to March 19, 2020

Date Searched: March 20, 2020; 1670 records

(exp Breast Neoplasms/ OR (breast* adj3 (cancer* OR tumor* OR tumour* OR neoplasm* OR adenocarcinoma* OR carcinoma* OR malignan* OR in situ)).ab,ti)

AND

(exp costs and cost analysis/ OR exp quality-adjusted life years/ OR exp global burden of disease/ OR economics.fs OR (cost? OR costing OR expenditure* OR economic* OR expense* OR qaly? OR daly?).ab,ti OR (burden adj2 disease*).ab,ti)

AND

(exp developing countries/ OR ((developing OR less developed OR third world OR under developed OR middle income OR low income OR underserved OR under served OR deprived OR poor*) adj1 (count* OR nation* OR state* OR population* OR area* OR economy OR economies)).ab,ti OR (lmic OR lmics).ab,ti OR (resource* adj2 (poor OR limiting OR limited OR low OR constrain*)).ab,ti OR exp africa/ OR exp asia/ OR exp south america/ OR exp latin america/ OR exp central america/ OR (africa OR asia OR south america* OR latin america* OR central america* OR afghanistan* OR albania* OR algeria* OR angola* OR argentina* OR armenia* OR azerbaijan* OR bangladesh* OR belarus* OR belize* OR benin* OR bhutan* OR bolivia* OR bosnia* OR botswana* OR brazil* OR bulgaria* OR burkin* OR burundi* OR cabo verd* OR cape verd* OR cambodia* OR cameroon* OR central african republic OR chad* OR china* OR colombia* OR comoros* OR comorian* OR congo* OR costa rica* OR cote divoire* OR ivorian* OR cuba* OR democratic peoples republic of korea OR djibouti* OR dominica* OR ecuador* OR egypt* OR el salvador* OR salvadoran* OR eritrea* OR eswatini* OR ethiopia* OR fiji* OR gabon* OR gambia* OR gaza OR georgia* OR ghana* OR grenada* OR grenadines* OR guatemala* OR guinea* OR guyana* OR haiti* OR herzegovina* OR hondura* OR india* OR indonesia* OR iran* OR iraq* OR ivory coast* OR jamaica* OR jordan* OR kazakh* OR kenya* OR kiribati* OR kosovo* OR kyrgyz* OR lao OR laoatian* OR lebanon* OR lebanese OR lesotho* OR liberia* OR libya* OR macedonia* OR madagascar* OR malawi* OR malaysia* OR maldiv* OR mali OR malian* OR marshall island* OR mauritania* OR mauriti* OR mexico OR mexican* OR micronesia* OR moldova* OR mongolia* OR montenegr* OR morocc* OR mozambi*OR myanmar* OR namibia* OR nauru* OR nepal* OR nicaragua*OR niger* OR pakistan* OR papua* OR paraguay* OR peru* OR philippines* OR philippino* OR principe OR romania* OR russia* OR rwanda* OR saint lucia* OR saint vincent* OR samoa* OR samoa* OR sao tome* OR senegal* OR serbia* OR sierra leone* OR solomon island* OR somalia* OR south africa* OR south korea* OR sri lanka* OR st lucia* OR st vincent* OR sudan* OR surinam* OR syria* OR tajik* OR tanzania* OR thai* OR timor* OR togo* OR tonga* OR tunisia* OR turk* OR tuvalu* OR uganda* OR ukraine* OR uzbek* OR vanuatu* OR venezuela* OR vietnam* OR west bank* OR yemen* OR zambia* OR zimbabw*).ab,ti)

Embase (Elsevier, 1974–)

Date searched: March 20, 2020; 1449 records

(‘breast cancer’/exp OR (breast* NEAR/3 (cancer* OR tumor* OR tumour* OR neoplasm* OR adenocarcinoma* OR carcinoma* OR malignan* OR ‘in situ’)):ab,ti)

AND

(‘cost benefit analysis’/exp OR ‘cost’/de OR ‘health care cost’/exp OR quality-adjusted life years OR (cost$ OR costing OR expenditure* OR economic* OR expense* OR qaly$ OR daly?):ab,ti OR (burden NEAR/2 disease*):ab,ti)

AND

(‘developing country’/exp OR ((developing OR ‘less developed’ OR ‘third world’ OR ‘under developed’ OR ‘middle income’ OR ‘low income’ OR underserved OR ‘under served’ OR deprived OR poor*) NEAR/1 (count* OR nation* OR state* OR population* OR area*)):ab,ti OR lmic:ab,ti OR lmics:ab,ti OR (resource* NEAR/2 (poor OR limiting OR limited OR low OR constrain*)):ab,ti OR africa/exp OR asia/exp OR ‘south and central america’/exp OR (africa OR asia OR ‘south america*’ OR ‘latin america*’ OR ‘central america*’ OR afghanistan* OR albania* OR algeria* OR angola* OR argentina* OR armenia* OR azerbaijan* OR bangladesh* OR belarus* OR belize* OR benin* OR bhutan* OR bolivia* OR bosnia* OR botswana* OR brazil* OR bulgaria* OR burkin* OR burundi* OR ‘cabo verd*’ OR ‘cape verd*’ OR cambodia* OR cameroon* OR ‘central african republic’ OR chad* OR china* OR colombia* OR comoros* OR comorian* OR congo* OR ‘costa rica*’ OR ‘cote d ivoire*’ OR ivorian* OR cuba* OR ‘democratic peoples republic of korea’ OR djibouti* OR dominica* OR ecuador* OR egypt* OR ‘el salvador*’ OR salvadoran* OR eritrea* OR eswatini* OR ethiopia* OR fiji* OR gabon* OR gambia* OR gaza OR georgia* OR ghana* OR grenada* OR grenadines* OR guatemala* OR guinea* OR guyana* OR haiti* OR herzegovina* OR hondura* OR india* OR indonesia* OR iran* OR iraq* OR ‘ivory coast*’ OR jamaica* OR jordan* OR kazakh* OR kenya* OR kiribati* OR kosovo* OR kyrgyz* OR lao OR laoatian* OR lebanon* OR lebanese OR lesotho* OR liberia* OR libya* OR macedonia* OR madagascar* OR malawi* OR malaysia* OR maldiv* OR mali OR malian* OR ‘marshall island*’ OR mauritania* OR mauriti* OR mexico OR mexican* OR micronesia* OR moldova* OR mongolia* OR montenegr* OR morocc* OR mozambi* OR myanmar* OR namibia* OR nauru* OR nepal* OR nicaragua* OR niger* OR pakistan* OR papua* OR paraguay* OR peru* OR philippines* OR philippino* OR principe OR romania* OR russia* OR rwanda* OR ‘saint lucia*’ OR ‘saint vincent*’ OR samoa* OR samoa* OR ‘sao tome*’ OR senegal* OR serbia* OR ‘sierra leone*’ OR ‘solomon island*’ OR somalia* OR ‘south africa*’ OR ‘south korea*’ OR ‘sri lanka*’ OR ‘st lucia*’ OR ‘st vincent*’ OR sudan* OR surinam* OR syria* OR tajik* OR tanzania* OR thai* OR timor* OR togo* OR tonga* OR tunisia* OR turkey* OR turk* OR tuvalu* OR uganda* OR ukraine* OR uzbek* OR vanuatu* OR venezuela* OR vietnam* OR ‘west bank*’ OR yemen* OR zambia* OR zimbabw*):ab,ti)

NOT

‘conference abstract’/it

Web of Science (Clarivate Analytics)

Indexes = *SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC Timespan = *All years

Date search March 20, 2020; 1570 records

Exclude meeting abstracts

TS = *(“breast*” NEAR/3 (“cancer*” OR “tumor*” OR “tumour*” OR “neoplasm*” OR “adenocarcinoma*” OR “carcinoma*” OR “malignan*” OR “in situ”))

AND

TS = *(“cost*” OR “costing” OR “expenditure*” OR “economic*” OR “expense*” OR “qaly*” OR “daly*” OR (“burden” NEAR/2 “disease*”))

AND

TS = *(((“developing” OR “less developed” OR “third world” OR “under developed” OR “middle income” OR “low income” OR “underserved” OR “under served” OR “deprived” OR “poor*”) NEAR/1 (“count*” OR “nation*” OR “state*” OR “population*” OR “area*))” OR “lmic” OR “lmics” OR “(resource*NEAR/ 2 (poor” OR “limiting” OR “limited” OR “low” OR “constrain*”)) OR “africa” OR “asia” OR “south america*” OR “latin america*” OR “central america*” OR “afghanistan*” OR “albania*” OR “algeria*” OR “angola*” OR “argentina*” OR “armenia*” OR “azerbaijan*” OR “bangladesh*” OR “belarus*” OR “belize*” OR “benin*” OR “bhutan*” OR “bolivia*” OR “bosnia*” OR “botswana*” OR “brazil*” OR “bulgaria*” OR “burkin*” OR “burundi*” OR “cabo verd*” OR “cape verd*” OR “cambodia*” OR “cameroon*” OR “central african republic” OR “chad*” OR “china*” OR “colombia*” OR “comoros*” OR “comorian*” OR “congo*” OR “costa rica*” OR “cote d ivoire*” OR “ivorian*” OR “cuba*” OR “democratic peoples republic of korea” OR “djibouti*” OR “dominica*” OR “ecuador*” OR “egypt*” OR “el salvador*” OR “salvadoran*” OR “eritrea*” OR “eswatini*” OR “ethiopia*” OR “fiji*” OR “gabon*” OR “gambia*” OR “gaza” OR “georgia*” OR “ghana*” OR “grenada*” OR “grenadines*” OR “guatemala*” OR “guinea*” OR “guyana*” OR “haiti*” OR “herzegovina*” OR “hondura*” OR “india*” “ OR “indonesia*” OR “iran*” OR “iraq*” OR “ivory coast*” OR “jamaica*” OR “jordan*” OR “kazakh*” OR “kenya*” OR “kiribati*” OR “kosovo*” OR “kyrgyz*” OR “lao” OR “laoatian*” OR “lebanon*” OR “lebanese” OR “lesotho*” OR “liberia*” OR “libya*” OR “macedonia*” OR “madagascar*” OR “malawi*” OR “malaysia*” OR “maldiv*” OR “mali” OR “malian*” OR “marshall island*” OR “mauritania*” OR “mauriti*” OR “mexico” OR “mexican*” OR “micronesia*” OR “moldova*” OR “mongolia*” OR “montenegr*” OR “morocc*” OR “mozambi*” OR “myanmar*” OR “namibia*” OR “nauru*” OR “nepal*” OR “nicaragua*” OR “niger*” OR “pakistan*” OR “papua*” “ OR “paraguay*” OR “peru*” OR “philippines*” OR “philippino*” OR “principe” OR “romania*” OR “russia*” OR “rwanda*” OR “saint lucia*” OR “saint vincent*” OR “samoa*” OR “samoa*” OR “sao tome*” OR “senegal*” OR “serbia*” OR “sierra leone*” OR “solomon island*” OR “somalia*” OR “south africa*” OR “south korea*” OR “sri lanka*” OR “st lucia*” OR “st vincent*” OR “sudan*” OR “surinam*” OR “syria*” OR “tajik*” OR “tanzania*” OR “thai*” OR “timor*” OR “togo*” OR “tonga*” OR “tunisia*” OR “turkey*” OR “turk*” OR “tuvalu*” OR “uganda*” OR “ukraine*” OR “uzbek*” OR “vanuatu*” OR “venezuela*” OR “vietnam*” OR “west bank*” OR “yemen*” OR “zambia*” OR “zimbabw*”)

Global Health (EBSCO)

Date searched March 23, 2020; 813 records

(DE (“breast cancer”) OR TI (breast* N3 (cancer* OR tumor* OR tumour* OR neoplasm* OR adenocarcinoma* OR carcinoma* OR malignan* OR “in situ”)) OR AB (breast* N3 (cancer* OR tumor* OR tumour* OR neoplasm* OR adenocarcinoma* OR carcinoma* OR malignan* OR “in situ”)))

AND

(DE (“economic analysis” OR “cost analysis” OR “cost benefit analysis” OR “cost effectiveness analysis” OR “valuation” OR “economics”) OR TI (cost* OR costing OR expenditure* OR economic* OR expense* OR qaly* OR daly* OR (burden N2 disease*)) OR AB (cost* OR costing OR expenditure* OR economic* OR expense* OR qaly* OR daly* OR (burden N2 disease*)))

AND

(DE (“Developing Countries” OR “Least Developed Countries” OR “Asia” OR “Caribbean” OR “Central America” OR “Latin America” OR “Africa” OR “Oceania” OR “South America” OR “Argentina” OR “Aruba” OR “Bahamas” OR “Bahrain” OR “Barbados” OR “Belize” OR “Bermuda” OR “Bolivia” OR “Bonaire” OR “Brazil” OR “British Virgin Islands” OR “Brunei Darussalam” OR “Cameroon” OR “Cayman Islands” OR “Chile” OR “China” OR “Christmas Island” OR “Cocos Islands” OR “Colombia” OR “Congo” OR “Cook Islands” OR “Costa Rica” OR “Cote d’Ivoire” OR “Crozet Islands” OR “Cuba” OR “Curacao” OR “Cyprus” OR “Dominica” OR “Dominican Republic” OR “Easter Island” OR “Ecuador” OR “Egypt” OR “El Salvador” OR “Falkland Islands” OR “Federated States of Micronesia” OR “Fiji” OR “French Guiana” OR “Gabon” OR “Gambier Islands” OR “Ghana” OR “Grenada” OR “Guadeloupe” OR “Guam” OR “Guatemala” OR “Guyana” OR “Honduras” OR “India” OR “Indonesia” OR “Iran” OR “Iraq” OR “Jamaica” OR “Jordan” OR “Kenya” OR “Kerguelen Archipelago” OR “Korea Democratic People’s Republic” OR “Korea Republic” OR “Kuwait” OR “Least Developed Countries” OR “Lebanon” OR “Libya” OR “Malaysia” OR “Marquesas Islands” OR “Marshall Islands” OR “Martinique” OR “Mauritius” OR “Mayotte” OR “Mexico” OR “Midway Islands” OR “Mongolia” OR “Montserrat” OR “Morocco” OR “Namibia” OR “New Britain” OR “New Caledonia” OR “New Ireland” OR “Nicaragua” OR “Nigeria” OR “Niue” OR “Northern Mariana Islands” OR “Oman” OR “Pakistan” OR “Panama” OR “Papua New Guinea” OR “Paraguay” OR “Peru” OR “Philippines” OR “Algeria” OR “Puerto Rico” OR “Qatar” OR “Reunion” OR “Saba” OR “Saint Helena” OR “Saint Kitts and Nevis” OR “Saint Lucia” OR “Saint Vincent and the Grenadines” OR “Saudi Arabia” OR “Senegal” OR “Seychelles” OR “Singapore” OR “South Africa” OR “Sri Lanka” OR “Suriname” OR “Swaziland” OR “Syria” OR “Tahiti” OR “Thailand” OR “Tokelau” OR “Tonga” OR “Angola” OR “Anguilla Island” OR “Trinidad and Tobago” OR “Tuamotu” OR “Tubuai Islands” OR “Tunisia” OR “Turkey” OR “Turks and Caicos Islands” OR “United Arab Emirates” OR “Uruguay” OR “Venezuela” OR “Vietnam” OR “Wallis and Futuna” OR “Western Sahara” OR “Zimbabwe” OR “Antigua and Barbuda” OR “Bangladesh” OR “Benin” OR “Bhutan” OR “Botswana” OR “Burkina Faso” OR “Burundi” OR “Cambodia” OR “Cape Verde” OR “Central African Republic” OR “Chad” OR “Comoros” OR “Congo Democratic Republic” OR “Djibouti” OR “Equatorial Guinea” OR “Eritrea” OR “Ethiopia” OR “Gambia” OR “Guinea” OR “Guinea-Bissau” OR “Haiti” OR “Kiribati” OR “Laos” OR “Lesotho” OR “Liberia” OR “Madagascar” OR “Malawi” OR “Maldives” OR “Mali” OR “Mauritania” OR “Mozambique” OR “Myanmar” OR “Nepal” OR “Afghanistan” OR “Niger” OR “Rwanda” OR “Samoa” OR “Sao Tome and Principe” OR “American Samoa” OR “Sierra Leone” OR “Solomon Islands” OR “Somalia” OR “Sudan” OR “Tanzania” OR “Togo” OR “Tuvalu” OR “Uganda” OR “Vanuatu” OR “Yemen” OR “Zambia”)

OR

TI ((developing OR “less developed” OR “third world” OR “under developed” OR “middle income” OR “low income” OR underserved OR “under served” OR deprived OR poor*) N1 (count* OR nation* OR state* OR population* OR area*)) OR lmic OR lmics OR (resource* N2 (poor OR limiting OR limited OR low OR constrain*)) OR africa OR asia OR “south america*” OR “latin america*” OR “central america*” OR afghanistan* OR albania* OR algeria* OR angola* OR argentina* OR armenia* OR azerbaijan* OR bangladesh* OR belarus* OR belize* OR benin* OR bhutan* OR Bolivia* OR bosnia* OR botswana* OR brazil* OR bulgaria* OR burkin* OR burundi* OR “cabo verd*” OR “cape verd*” OR cambodia* OR cameroon* OR “central african republic” OR chad* OR china* OR colombia* OR comoros* OR comorian* OR congo* OR “costa rica*” OR “cote d ivoire*” OR ivorian* OR cuba* OR “democratic peoples republic of korea” OR djibouti* OR dominica* OR ecuador* OR egypt* OR “el salvador*” OR salvadoran* OR eritrea* OR eswatini* OR ethiopia* OR fiji* OR gabon* OR gambia* OR gaza OR georgia* OR ghana* OR grenada* OR grenadines* OR guatemala* OR guinea* OR guyana* OR haiti* OR herzegovina* OR hondura* OR india* OR indonesia* OR iran* OR iraq* OR “ivory coast*” OR jamaica* OR jordan* OR kazakh* OR kenya* OR kiribati* OR kosovo* OR kyrgyz* OR lao OR laoatian* OR lebanon* OR lebanese OR lesotho* OR liberia* OR libya* OR macedonia* OR madagascar* OR malawi* OR malaysia* OR maldiv* OR mali OR malian* OR “marshall island*” OR mauritania* OR mauriti* OR mexico OR mexican* OR micronesia* OR moldova* OR mongolia* OR montenegr* OR morocc* OR mozambi* OR myanmar* OR namibia* OR nauru* OR nepal* OR nicaragua* OR niger* OR pakistan* OR papua* OR paraguay* OR peru* OR philippines* OR philippino* OR principe OR romania* OR russia* OR rwanda* OR “saint lucia*” OR “saint vincent*” OR samoa* OR samoa* OR “sao tome*” OR senegal* OR serbia* OR “sierra leone*” OR “solomon island*” OR somalia* OR “south africa*” OR “south korea*” OR “sri lanka*” OR “st lucia*” OR “st vincent*” OR sudan* OR surinam* OR syria* OR tajik* OR tanzania* OR thai* OR timor* OR togo* OR tonga* OR tunisia* OR turkey* OR turk* OR tuvalu* OR uganda* OR ukraine* OR uzbek* OR vanuatu* OR venezuela* OR vietnam* OR “west bank*” OR yemen* OR zambia* OR zimbabw*)

OR

AB ((developing OR “less developed” OR “third world” OR “under developed” OR “middle income” OR “low income” OR underserved OR “under served” OR deprived OR poor*) N1 (count* OR nation* OR state* OR population* OR area*)) OR lmic OR lmics OR (resource* N2 (poor OR limiting OR limited OR low OR constrain*)) OR africa OR asia OR “south america*” OR “latin america*” OR “central america*” OR afghanistan* OR albania* OR algeria* OR angola* OR argentina* OR armenia* OR azerbaijan* OR bangladesh* OR belarus* OR belize* OR benin* OR bhutan* OR bolivia* OR bosnia* OR botswana* OR brazil* OR bulgaria* OR burkin* OR burundi* OR “cabo verd*” OR “cape verd*” OR cambodia* OR cameroon* OR “central african republic” OR chad* OR china* OR colombia* OR comoros* OR comorian* OR congo* OR “costa rica*” OR “cote d ivoire*” OR ivorian* OR cuba* OR “democratic peoples republic of korea” OR djibouti* OR dominica* OR ecuador* OR egypt* OR “el salvador*” OR salvadoran* OR eritrea* OR eswatini* OR ethiopia* OR fiji* OR gabon* OR gambia* OR gaza OR georgia* OR ghana* OR grenada* OR grenadines* OR guatemala* OR guinea* OR guyana* OR haiti* OR herzegovina* OR hondura* OR india* OR indonesia* OR iran* OR iraq* OR “ivory coast*” OR jamaica* OR jordan* OR kazakh* OR kenya* OR kiribati* OR kosovo* OR kyrgyz* OR lao OR laoatian* OR lebanon* OR lebanese OR lesotho* OR liberia* OR libya* OR macedonia* OR madagascar* OR malawi* OR malaysia* OR maldiv* OR mali OR malian* OR “marshall island*” OR mauritania* OR mauriti* OR mexico OR mexican* OR micronesia* OR moldova* OR mongolia* OR montenegr* OR morocc* OR mozambi* OR myanmar* OR namibia* OR nauru* OR nepal* OR nicaragua* OR niger* OR pakistan* OR papua* OR paraguay* OR peru* OR philippines* OR philippino* OR principe OR romania* OR russia* OR rwanda* OR “saint lucia*” OR “saint vincent*” OR samoa* OR samoa* OR “sao tome*” OR senegal* OR serbia* OR “sierra leone*” OR “solomon island*” OR somalia* OR “south africa*” OR “south korea*” OR “sri lanka*” OR “st lucia*” OR “st vincent*” OR sudan* OR surinam* OR syria* OR tajik* OR tanzania* OR thai* OR timor* OR togo* OR tonga* OR tunisia* OR turkey* OR turk* OR tuvalu* OR uganda* OR ukraine* OR uzbek* OR vanuatu* OR venezuela* OR vietnam* OR “west bank*” OR yemen* OR zambia* OR zimbabw*))

WHO Regional Databases

Date searched March 23, 2020; 788 records

(“breast cancer*” OR “breast neoplasm*” OR “breast tumor*” OR “breast tumour*” OR “breast carcinoma*” OR “carcinoma of the breast” OR “carcinoma in situ”)

AND

(cost OR costs OR costing OR expenditure*OR economic*OR expense*OR qaly*OR daly*OR “burden of disease” OR “disease burden”)

Appendix II: Data extraction instrument

*Bolded variables are defined

A. Data extraction form

Study name:

Author (last name et al.):

Publication year:

Country:

World region:

• Latin America and Caribbean

• Sub-Saharan Africa

• Middle East and North Africa

• Europe and Central Asia

• South Asia

• East Asia and Pacific

Economic Status:

• Upper-middle income

• Lower-middle income

• Lower income

• Across LMICs – costs aggregated across various LMIC economic statuses

Type of economic evaluation:

• Cost analysis

• Cost of illness

• Cost-effectiveness analysis

• Cost-utility analysis

• Cost-minimization analysis

Study design:

• Observational

• Model-based

• Experimental

• Other

Study perspective:

• Health care provider

• Health care payer

• Health care (not specified)

• Patient

• Societal

Population: description of number of patients, inclusion/exclusion criteria

Breast cancer stage:

• Early (stage I and II)

• Advanced (stage III and IV)

• All (early and advanced)

• Unknown (not stated)

• Other (eg, operable, node-positive)

Breast cancer types:

• Hormone receptor-positive only

• HER2-positive only

Intervention evaluated:

• Diagnosis

• Treatment

• Diagnosis and treatment

Time Horizon: time over which the costs and/or effects are measured

Interventions compared

Objective

Conclusion

B. Extended data extraction form

Base year of cost data:

Costing approach:

• Micro – cost of each input is estimated separately (eg, ingredients approach)

• Gross – total cost is estimated across all inputs

• Micro and gross

Cost categories included (select all that apply)

• Direct medical – medical costs (eg, chemotherapy, physician visit) during care

• Direct non-medical – non-medical costs (eg, food, transportation) during care

• Indirect – costs related to lost wages during care, morbidity costs, mortality costs

Inputs for direct medical costs, if included (select all that apply):

• Medical visits

• Diagnostic studies/pathology

• Tumor-directed medications

• Supportive medications

• Surgery

• Radiotherapy

• Hospitalization

• Imaging

• Lab tests/blood services

• Palliative care

• Training

• Administrative/overhead (eg, program costs)

• Other (eg, unspecified medical cost, medical devices)

Inputs for direct non-medical, if included (select all that apply):

• Food

• Transportation/travel

• Patient accommodation

• Food, transportation, or accommodation for companion

• Other (eg, home help, child tutoring)

Inputs for indirect costs, if included (select all that apply):

• Lost wages from cancer care

• Lost wages from disability/premature mortality

• Lost wages of companion

Sources for cost estimation:

• Patients

• Medical records

• Hospital finance/administrative data

• Government data (eg, public tariffs)

• Claims/Insurance data (eg, private tariffs)

• Literature

• Expert opinion

Costs disaggregated by cost inputs:

• Yes

• No

• n/a – not applicable for studies that utilized gross costing

Cost disaggregated by stage:

• Yes

• No

Currency year reported:

• Yes

• No

Cost estimation uncertainty reported:

• Yes – uncertainty include confidence intervals, standard deviation, range etc.

• No

Sensitivity analysis for cost estimation:

• Yes

• No

Costs discounted:

• Yes

• No

• n/a – not applicable for studies that do not collect costs beyond one year

Discount rates (if costs discounted):

Costs adjusted for inflation:

• Yes

• No

• n/a – not applicable for studies that utilize costing data from only one year

Currency of cost outcome (report USD if available):

Currency year of cost outcome:

Currency conversion (if cost outcome not in local currency):

BMJ checklist (31): 0 (not considered), 1 (partially considered), 2 (fully considered), or not applicable

Study design (14 points):

• 1The research question is stated
• 2The economic importance of the research question is stated
• 3The viewpoint(s) of the analysis are clearly stated and justified
• 4The rationale for choosing the alternative programs or interventions compared is stated
• 5The alternatives being compared are clearly described
• 6The form of economic evaluation used is stated
• 7The choice of form of economic evaluation is justified in relation to the questions addressed

Cost/outcome estimation (24 points):

• 8The source(s) of effectiveness estimates used are stated
• 9Details of the design and results of effectiveness study are given (if based on a single study)
• 10Details of the method of synthesis or meta-analysis of estimates are given (if based on an overview of a number of effectiveness studies)
• 11The primary outcome measure(s) for the economic evaluation are clearly stated
• 12Methods to value health states and other benefits are stated
• 13Details of the subjects from whom valuations were obtained are given
• 14Productivity changes (if included) are reported separately
• 15The relevance of productivity changes to the study question is discussed
• 16Quantities of resources are reported separately from their unit costs
• 17Methods for the estimation of quantities and unit costs are described
• 18Currency and price data are recorded
• 19Details of currency of price adjustments for inflation or currency conversion are given

Analysis and Interpretation (28 points):

• 20Details of any model used are given
• 21The choice of model used and the key parameters on which it is based are justified
• 22Time horizon of costs and benefits is stated
• 23The discount rate(s) is stated
• 24The choice of rate(s) is justified (if discounted)
• 25An explanation is given if costs or benefits are not discounted
• 26Details of statistical tests and confidence intervals are given for stochastic data
• 27The approach to sensitivity analysis is given and justified
• 28Relevant alternatives are compared
• 29Incremental analysis is reported
• 30Major outcomes are presented in a disaggregated as well as aggregated form
• 31The answer to the study question is given
• 32Conclusions follow from the data reported
• 33Conclusions are accompanied by the appropriate caveats

Appendix III: Data presentation table shells

Table shell 1.

Characteristics of all reviewed studies

Authors, publication year	World region (country)	Economic status	Study population	Setting	Breast cancers included	Diagnostic or therapeutic Intervention	Economic evaluation type	Study design	Study perspective	Time horizon

Table shell 2.

Study objectives and main study conclusions of all reviewed studies

Authors	Study objective	Conclusion

Table shell 3.

Characteristics of reviewed studies that estimate the cost of multiple steps in the breast cancer care pathway

Authors, publication year	Costing approach	Sources for cost estimation	Cost categories included	Inputs of included cost category	Discount rate used	Inclusion of cost estimation uncertainty	Sensitivity analysis for a ssumptions

Table Shell 4.

Critical appraisal scores of reviewed studies that estimate the cost of multiple steps in the breast cancer care pathway

		Scored domains			Summary scores
Author, year		Study design	Data collection/cost estimation	Analysis and interpretation	Number of items scored	Sum of scores	Total average score
Study 1	Score granted
	% of maximum (domain) score

Table Shell 5.

Overview of the reviewed studies that estimate the cost of multiple steps in the breast cancer care pathway: frequency and percentage

Costing approach	Micro	Gross
Frequency (percentage)
Data sources for cost	Primary data collection	Secondary data collection	Literature based	Expert opinion	Unknown
Frequency (percentage)
Included cost category	Direct medical	Direct non-medical	Indirect
Frequency (percentage)
Timing issues considered (discounting cost values or used consumer price index)	Yes	No
Frequency (percentage)
Inclusion of cost estimation uncertainty	Yes	No
Frequency (percentage)