Indirect costs in patients with breast cancer: protocol for a systematic review

Background: The rising incidence of breast cancer places a nancial burden on national health services and economies. The cost of breast cancer studies is constantly increasing; however, this cost is calculated based on the currency of the country in which the study takes place, therefore limiting national and international comparisons. On the other hand, there is no common method used to conduct such studies. The objective of this review is to contribute to this knowledge pool by examining the indirect costs of breast cancer in order to provide comparable estimates. This review will consider all relevant cost of illness studies dated from the year 2000 until the year 2018. Relevant papers will be identied through a systematic search in all major medical research databases. Two independent researchers will screen selected articles. Methodological quality of the studies will be assessed using a checklist designed by Stunhldreher et al. The results will be presented in line with the PRISMA (Preferred Reporting Items for Systematic review and Meta-Analysis) While the costs of breast cancer studies are helpful in planning health interventions in terms of the severity of the and budget priorities, the results could also be of great help to policymakers and decision in health systems.

costs, indirect costs, and intangible costs. The monetary value of lost productivity, which results from illness or premature death and recognized as indirect costs, is responsible for a relatively large part of disease costs and signi cantly affects the results of economic assessments (8)(9)(10) .
Indirect costs are an important component of costs of illness studies, especially in the management of chronic diseases that may require lifelong treatment (11).
Breast cancer in many women can cause long-term disability and can signi cantly affect their nancial and social wellbeing (12,13) . In addition to medical and therapeutic expenses, women must shoulder the costs pertinent to missed work days or loss of productivity in paid employment or at home (14)(15)(16)(17)(18)(19)(20)(21) . The risk of job loss among people diagnosed with cancer is 1.3 times higher than those without cancer (12).
Even when diagnosed at an early stage, breast cancer can adversely affect an individual's ability to work for up to 5 years after the original diagnosis (22).
Factors associated with impaired productivity include adverse effects and treatments such as progression and exacerbation of disease, cognitive and neurological disorders, poor physical and mental health, chemotherapy, and the time and cost required to receive treatment (23).
In a 2016 American study, nonelderly women with breast cancer, compared with other people, signi cantly experienced job incapacity (13.6%), including reduced productivity at work (7.2 days) and at home (3.3 days) (24) .
Absenteeism can vary from a few weeks to several months. Many people may return to work, but their hours of work may be decreased due to reduced productivity or employer disagreement. For example, in a 2013 study, reduction in productivity due to adverse effects from breast cancer in the Netherlands and Sweden was 68% and 72% respectively (25). Some patients may never return to work due to disability or premature death.
Lung and female breast are the leading cancers worldwide in terms of the number of new cases diagnosed annually. For each of these cancers, approximately 2.1 million diagnoses were estimated in 2018, or 11.6% of the total cancer incidence burden (26).
A 2008 study in California, USA, showed that on average, a premature death from breast cancer can result in loss of productivity worth $272,000 and the loss of as many as 22.9 years of life (27).
Additionally, in 2002 the productivity cost of breast cancer in Sweden was estimated to be 2.1 billion SEK, and over 50% of this (1.1 billion) was due to premature death (28).
In Iran in 2010, the economic burden of breast cancer was estimated to be more than $947 million. More than 70% of this gure is due to productivity lost as a result of death from breast cancer (29).
Despite the simplicity of expressing the components of indirect costs, the proper method of measuring and evaluating the lost productivity of breast cancer can be problematic. There are several methods to measure indirect costs (29). The most accurate estimation of indirect costs requires the use of micro-costing methods; thus, it requires relatively large sample sizes, well-designed protocols, and well-trained interviewers (7,30) . In an economic evaluation, the methods used for the measurement and evaluation of lost productivity can affect the results of the studies (29). The use of different methods for calculating the lost productivity may impede the comparison of results between countries. Possible reasons for the differences in indirect costs include methodology, the value of local productivity, disease and patient characteristics, social security systems and epidemiologic environments (31). Therefore, the primary goal of this study is to systematically review the indirect costs and the monetary value of lost productivity due to breast cancer. The second goal is to examine the methods used in cost of illness studies and economic burden studies to measure and value indirect costs.

Methods:
Eligibility criteria: Indirect costs are de ned as the costs of breast cancer on labor market outcomes (absenteeism, presenteeism, short and long-term disability and premature death). Studies will be selected according to the following criteria.

Type of participants:
Female breast cancer patients Type of interventions: There will be no lters for interventions. In the majority of cost of illness studies, intervention is not a primary concern. This protocol will consider all possible treatments for breast cancer.

Types of outcome measures:
Indirect costs due to breast cancer.

Type of studies:
Cost of illness studies which include estimates of indirect costs of breast cancer at a municipal level (for example, city, state, country) or within certain organizations (for example, at employer level, or within health insurance companies).

Exclusion criteria:
Studies other than cost of illness studies Economic evaluation studies Reviews, letters, abstracts, conference papers, methodological and general commentary or perspectives Studies without English language titles and abstracts Search strategy: Mesh term and Emtree: In order to include all relevant studies, a search of Medline (via PubMed; using Mesh Terms), EMBASE (using Emtree), as well as some full text articles in this eld, will be conducted for keywords. Keywords that will be used for building the search strategy include: Indirect cost: ("Indirect cost" OR "Cost of illness" OR "Illness Cost" OR "Sickness Cost" OR (Costs AND Sickness) OR "Burden of Illness" OR "Illness Burden" OR "Cost of Disease" OR "Economic Burden of Disease" OR "Disease Cost" OR (Cost AND Disease) OR "Disease Costs" OR "Cost of Sickness" OR "Sickness Costs" OR "Costs of Disease" OR "Cost-of-illness" OR "Productivity costs" OR "Productivity lost" OR "Productivity loss" OR "Presenteeism cost" OR "Absenteeism cost" OR "Human capital" OR "Economic burden") Breast cancer: ("Breast Neoplasm" OR "Breast Tumors" OR "Breast Tumor" OR "Breast Carcinoma" OR "Breast Carcinoma" OR "Human Mammary Neoplasm" OR "Human Mammary Neoplasms" OR "Breast Cancer" OR "Mammary Cancer" OR "Mammary Cancers" OR "Malignant Neoplasm of Breast" OR "Breast Malignant Neoplasm" OR "Breast Malignant Neoplasms" OR "Malignant Tumor of Breast" OR "Breast Malignant Tumor" OR "Breast Malignant Tumors" OR "Cancer of Breast" OR "Cancer of the Breast" OR "advanced breast cancer" OR "breast cancer recurrence" OR "breast gland cancer" OR "breast gland neoplasm" OR "mamma cancer" OR "mammary gland cancer" Electronic databases: The following electronic databases will be searched: (1) The Cochrane Library; (2) PubMed; (3) Web of Science; (4) Scopus; (5) ProQuest; (6) Google scholar; (7) EMBASE.

Date of search:
Searches of electronic databases were carried out by December 31, 2018, with no starting date limitation.
Grey literature: All conference abstracts and posters written in English will be considered (by handsearching). Handsearching: Reference lists of identi ed studies will be reviewed to include all relevant studies.

Restriction of language:
Study will include all articles in English language.

Contact the authors:
If the full text of articles is not available, the authors will be contacted three times.

Data collection:
Screening of studies for eligibility (selection process): The rst step will be the import of all search results into EndNote and the subsequent removal of duplicates. Screening will then be conducted in two phases. First, title and abstract screening will be undertaken by one of the members of the research team to identify publications that do not meet the inclusion criteria. In doubtful cases, the publications will be included. Next, two reviewers will independently screen the full texts of the selected publications to match the eligibility criteria. Disagreements will be resolved through discussion and the reasons for exclusion will be recorded.
Collection data process: The following data will be extracted: the author's name, publication year, reference year for cost, region, number of patients, methodology of the study, components of indirect costs, and estimated indirect costs per patient.
Assessment of study quality: Quality will be assessed using a checklist for cost of illness (COI) designed by Stunhldreher et al (32).
The following items will be assessed: scope, general economic characteristics, and calculation of costs, study design and analysis and presentation of results. Two members of the research team will independently perform the assessment and any discrepancies and uncertainties will be resolved through consensus.
Data synthesis (analysing, interpreting and reporting results): The data will be analysed using Stata statistical Software 12.0 (Stata Crop, College Station, Texas, The USA).
Dealing with missing data: If the year of costing is missing an email will be sent to the authors of the COI study.

Assessment of heterogeneity:
Heterogeneity will be tested using Q-statistics with 95% CI. To examine the extent of heterogeneity, I 2 will be computed.

Data synthesis:
The researchers will employ appropriate analytical methods to summarize the results of the study. If applicable, a meta-analysis of resource use or cost data may be considered. In addition to reporting the characteristics of included studies, a summary table of various checklists completed to inform assessments of the methodological quality of cost of illness studies will be presented.
Costs will be presented in real currency (as of the year of study or adjusted to current year), as this will be relevant for readers in the country in which the study takes place. In addition, in order to facilitate comparisons of cost estimates collected from different studies, an international exchange rate based on purchasing power parities (PPPs) will be used to convert cost estimates into a target currencyinternational dollars. GDP de ators will be used to convert cost estimates into a xed price year.
Publication bias will be detected by funnel plot.

Subgroup analysis and investigation of heterogeneity:
Subgroup analysis will be used to explore possible sources of heterogeneity, based on the following criteria: Patient characteristic (such as age) Approach of studies (such as human capital and friction cost) Sensitivity analysis will be performed to explore the source of heterogeneity as follows: Quality components, including full-text publications versus abstracts, published versus unpublished data Risk of bias (by omitting studies that are judged to be at high risk of bias)

Summary of ndings:
Results of this review will be reported in line with the PRISMA 2009 checklist. The overall quality of evidence on outcomes will be presented using the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach, which involves consideration of within-study risk of bias (methodological quality), directness of evidence, heterogeneity, precision of effect estimates and risk of publication bias. The overall quality of evidence will be rated at four levels: high, moderate, low and very low. It is hoped that policymakers will use this document. This protocol describes a systematic review of the indirect costs of breast cancer. Eventual gaps identi ed in this systematic review could have a signi cant impact on current public health policies and will highlight areas that need additional research.
It will underline challenges that need to be accounted for in future cost of illness studies. The review will also present current data on indirect costs of breast cancer as newer studies have been carried out since the publication of previous reviews.
The ndings from this review will be submitted for publication in peer-reviewed journals. They will be shared with decision-makers and health professionals. The researchers will also disseminate the ndings through professional conferences, health economists, and public health policymakers. The results of this study will provide policy-relevant recommendations for uptake of cost of illness studies in prioritizing decisions on essential breast cancer care packages.