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Current State of Funded National Cancer Institute Grants That Include Economic Analyses

Current State of Funded National Cancer Institute Grants That Include Economic Analyses Abstract Background Health economics research is an integral part of the transdisciplinary research supported by the National Cancer Institute (NCI). To better understand NCI activities in this area, we conducted a portfolio analysis of funded NCI grants including health economics research. Methods We examined all competitive grants funded by NCI from fiscal years 2015 to 2020 that included economic analyses or outcomes. Grant titles, abstracts, and specific aims were independently reviewed by 2 study team members; content of included grants was then coded for analysis. Results A total 212 grants were identified from searches; 146 of these included economic analyses and were included in the portfolio analysis. These 146 grants represent approximately 0.9% of all NCI competitively funded grants awarded 2015-2020. Of these grants, 100 were R01 awards, representing approximately 2.4% of all NCI R01 grants funded 2015-2020. The most common study type was interventional randomized controlled-trial, followed by simulation or model. Screening and prevention were the most frequent grant cancer continuum topic; survivorship was included in only 16 grants (11.0%). Cost-effectiveness analysis was the most frequently listed economic outcome (97 grants, 66.4%), whereas policy impact (20 grants, 13.7%) and financial hardship (15 grants, 10.3%) were less-frequently included economic outcomes. However, economic outcomes differed by cancer control continuum topic, with financial hardship being included in a greater proportion of treatment and survivorship grants. Conclusions Although relatively small, the NCI portfolio of funded grants including economic analyses is diverse, covering a range of cancer types, methods, and economic outcomes, and increasing over time. As the largest public funder of biomedical research, the National Institutes of Health (NIH) has specified priorities for health economics research (1). As stated in these priorities, “NIH is especially interested in health economics research designed to understand how innovations in treatment, diagnosis, prevention, and implementation strategies can be most effectively deployed to improve health and well-being” (1). That is, NIH is most interested in “applications involving health economics research in which health outcomes and health-related behaviors are the primary focus, and the connection between the subject(s) of the study and improved understanding of health are clear and explicit” (1). For example, this could include studies focused on: Determining the impact of financial and nonfinancial incentives on health-related behaviors, health-care use, and health outcomes; or Assessing how environmental, social, economic, and other factors affect health status, health-related behaviors, health-care use, health outcomes, health disparities, and responses to interventions. Portfolio analysis is an approach used by NIH to identify research and funding trends, recognize gaps, and evaluate potential opportunities for new investments (2, 3). Portfolio analysis is often performed by NIH researchers to assess the current state of funding for specific areas of interest; for example, a recently published portfolio analysis examined NIH funding of grants focused on individuals with advanced or metastatic cancers (4). The National Cancer Institute (NCI) is one of 27 institutes and centers that constitute the NIH. Given the importance of health economics research across the cancer control continuum and the need to better understand NCI activities related to this area, we conducted a portfolio analysis of funded NCI grants including health economics research. Methods This portfolio analysis examined all competitive grants funded by NCI from fiscal years 2015-2020 that included economic analyses or outcomes. Funded grants were identified using the NIH Query/View/Report (QVR) system. Only competitively reviewed grants (either new grant submissions or competitive renewals) for which NCI was the primary funding institute were examined. QVR System The QVR System was developed to enable the NIH extramural staff to search and view detailed information about NIH extramural applications and awards. Public (non-NIH) users have access to the NIH Research Portfolio Online Reporting Tools to access and search reports, data, and analyses of NIH research activities (https://reporter.nih.gov/). For this portfolio analysis, QVR was chosen as the grants search tool because of its capabilities for research coding and classification searches and keyword text searches in both the (public) abstract and (nonpublic) specific aims. Grant Search Strategy We identified funded grants including economic analyses, with economic analyses defined as either 1) economic outcomes (eg, costs, cost-effectiveness, financial hardship); 2) studies related to the economics of cancer care delivery (eg, who pays for cancer care, how much is paid, and who receives payment); or 3) studies of impacts of health economic policies, insurance, and health-care reforms. Using QVR, we were able to search funded NCI grants using either words or phrases in grant titles, abstracts, and specific aims section and using NIH Research, Condition, and Disease Categorization (RCDC) terms. RCDC is a computerized process used by NIH to categorize funding in medical research; more information on RCDC is available at https://era.nih.gov/about-era/nih-and-grantor/other/rcdc.htm. We performed several initial iterative test searches and reviews to inform keywords and text fields to use for final search parameters. The final search criteria included 24 RCDC terms and 27 text words or phrases searched for in grant titles, abstracts, and specific aims. The included RCDC terms were: Economic impact; cost effectiveness; cost-effectiveness evaluation; economic evaluation; comparative cost effectiveness; economic outcome; cost effectiveness analysis; cost savings; cost-benefit analysis; financial support; financial hardship; financial toxicity; uninsured medical expense; willingness to pay; cost analysis; medical care cost; economic impact; economic implications; costs and benefits; policy analysis; cost benefit economics; economic cost; economic policy; economic value. The included text words/phrases were: Cost-effectiveness; incremental cost; budget impact; cost-benefit analysis; out of pocket expenses; out-of-pocket payments; out-of-pocket costs; cost and effectiveness; cost and outcomes; costs and outcomes; direct medical costs; willingness-to-pay; cost drivers; cost trajectory; cost trajectories; financial hardship; financial toxicity; economic analysis; payment; payments; econometric; econometrics; health economics; accountable care; all payer claims; financial navigation; value of information. All competitively funded NCI grants from 2015-2020 with 1 or more of the RCDC terms or text phrases were identified. Grant titles, abstracts, and specific aims sections were independently reviewed by 2 members of the study team (the authors of this manuscript) to assess whether they included economic analyses. Any disagreements regarding grant inclusion or exclusion were discussed with a third member of the study team and resolved. Grant Coding and Curation NIH systems automatically coded certain grant attributes such as fiscal year of funding initiation and type of funding mechanism. To better understand and analyze research trends in funded cancer health economics grants, the study team developed additional curation codes classifying identified grants using the category options listed below. These codes were developed and refined through an iterative process based on trends that emerged from reviews of the identified grants: Cancer continuum: prevention; screening; treatment; survivorship; end of life; not specified. Screening-focused grants were not coded as prevention unless separate prevention activities were also included in the grant. Study type: interventional randomized controlled trial (RCT); interventional non-RCT; observational; cohort; retrospective; simulation or model; other. Study cancer population: noncancer patients; breast; cervical; colorectal; lung; prostate; other; multiple; not specified. “Noncancer patients” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer or are not being screened for a specific type of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. For example, the cancer population of grants examining fecal immunochemical testing or colonoscopy was classified as colorectal cancer. Age range: pediatric; adolescent or young adult; adult (40-65 years); older adult (>65 years); not specified; not applicable. Minority or underserved population: Black or African American; Hispanic or Latinx; Asian or Asian American; American Indian or Native American; low socioeconomic status; person with HIV; sexual identity or sexual orientation; “medically underserved” (individuals from an officially designated medically underserved area); other; not specified. Clinical outcome: behavior change; caregiver outcome; incidence or prevalence; quality of care; quality of life or well-being; patient knowledge; screening or diagnosis; survival; survivorship care; symptoms; treatment; other; none. Economic outcome: cost-benefit; cost-effectiveness; financial hardship; medical care costs; implementation costs; patient costs; other or unspecified costs; policy impact; value of information; economic analysis (unspecified); other. Regarding study type, both cohort and observational studies involved prospective data collection in noninterventional studies. Cohort studies were defined as focusing on a specified initial population at the start of the study, and no new individuals entered this population during the study. In contrast, observational studies involved individuals who entered the study population over time. Retrospective studies did not include prospective data collection but analyzed data that were already available at study initiation. All grants were coded independently by 2 members of the study team; differences in coding were resolved in discussions with a third member of the team. Except for fiscal year and funding mechanism, coding options were not mutually exclusive; that is, grants could be coded with more than 1 option. Results A total of 212 grants were identified using text word or phrase and RCDC term searches. Following review of grant titles, abstracts, and specific aims sections, 148 of these grants (69.8%) were identified as including economic analyses. On closer examination, 2 of these grants were loan repayment request proposals (L30 awards); because these did not describe proposed research, they were excluded from the portfolio analysis, leaving 146 grants for the analysis. The number of grants identified and screened at each stage of this portfolio analysis are highlighted in Supplemental Figure 1 (available online). The 146 grants represent approximately 0.9% of all competitively funded grants awarded by NCI during the 2015-2020 time period. Of these grants, 100 were R01 awards (also known as Research Project Grants). These 100 R01 awards represent approximately 2.4% of all R01 grants funded by NCI during the 2015-2020 time period. Characteristics of Funded NCI Grants Including Economic Analyses Table 1 lists the funding mechanism and fiscal year for the 146 included grants. A majority of grants (100, 68.5%) were R01 awards. The next largest category was training and career development awards (F and K mechanisms), corresponding to 16 grants (11%). Other funding mechanisms for economic analysis grants were U01 (9 grants); R21 or R03 (6 grants); R42, R43, or R44 small business awards (6 grants); R37 (MERIT) awards (5 grants); and P01 or P50 awards (4 grants). Fewer grants (16-20 per year) were funded from 2015 to 2017. The number funded increased to 23 in 2018, 33 in 2019, and 38 and 2020. One grant was based at a foreign (non-US) institution; 24 grants had a US-based primary institution but involved a collaborating foreign institution. Table 1. Fiscal year and funding mechanism of funded cancer health economics research grants Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) aK awards: Research Career Development Awards. F awards: Individuals Research Fellowships. bMERIT = Method to Extend Research in Time Award. Open in new tab Table 1. Fiscal year and funding mechanism of funded cancer health economics research grants Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) aK awards: Research Career Development Awards. F awards: Individuals Research Fellowships. bMERIT = Method to Extend Research in Time Award. Open in new tab Table 2 provides information on total funding (direct plus indirect) of the 146 grants including economic analyses by year, total funding for all NCI new and competing awards by year (as reported by the NCI Research Portfolio Online Reporting Tools; https://reporter.nih.gov/search/PCXPeHy9JEKDVTHptqZaqA/projects/charts?shared=true) and the proportion of total funding attributable to the 146 grants including economic analyses. Overall, the 146 grants including economic analyses represented slightly less than 1% of all funding for NCI new and competing awards in the 2015-2020 period. However, the total for all NCI new and competing award funding (the “denominator”) includes awards that were excluded from the portfolio analysis such as L30 loan repayment awards. Therefore, the proportion of funding attributable to these 146 grants is slightly greater than is shown in this table. Table 2. Funding for NCI-funded grants including economic analysis and for all NCI new and competing awards by fiscal yeara Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% a NCI = National Cancer Institute. Open in new tab Table 2. Funding for NCI-funded grants including economic analysis and for all NCI new and competing awards by fiscal yeara Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% a NCI = National Cancer Institute. Open in new tab Characteristics of Studies Figure 1 presents information on the study type(s) of the 146 grants including economic analyses. Study types (and other characteristics presented in this article) are not mutually exclusive; funded grants may have included and been classified as having more than one study type. The most common study type was interventional RCT, seen in 67 (45.9%) grants. Simulation or model was the next most frequently observed study type (39 grants), followed by retrospective (23), observational (18), interventional non-RCT (11), and cohort studies (2). Four grants included other or undefined study types. Figure 2 illustrates the topics of the cancer control continuum addressed by the identified grants. Prevention was the most frequently noted continuum topic, with 55 grants (37.7%). Screening was included in a similar number of grants (48), followed by treatment (43), whereas survivorship was included in only 16 grants (11.0%) and end-of-life care in only 2 grants (1.4%). Three grants did not specify the cancer continuum topic. Figure 1. Open in new tabDownload slide Study type(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized in each study type. Grants may have been categorized in more than 1 study type. Figure 1. Open in new tabDownload slide Study type(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized in each study type. Grants may have been categorized in more than 1 study type. Figure 2. Open in new tabDownload slide Cancer control continuum area(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on prevention, screening, treatment, survivorship, or end of life care. Grants may have been categorized in more than 1 cancer control continuum area. Figure 2. Open in new tabDownload slide Cancer control continuum area(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on prevention, screening, treatment, survivorship, or end of life care. Grants may have been categorized in more than 1 cancer control continuum area. Characteristics of Study Cancer Populations Figure 3 presents the cancer population(s) included in identified grants. For grants that examined prevention strategies targeting multiple cancer types (eg, smoking cessation or prevention, dietary or physical activity interventions) among individuals who had not been diagnosed with cancer, the study population type was classified as “noncancer patients.” This was the largest single category, corresponding to 44 grants (30.1%). Breast cancer was the next largest group (22 grants), which included both grants including individuals diagnosed with breast cancer and grants focused on screening for breast cancer. The cancer population of study was not specified in the title, abstract, or specific aims section for 22 grants, and other cancer types (ie, cancer types beyond those specified in the coding choices, such as head and neck cancers) were specified in 21 grants. Other cancer populations included cervical cancer (16 grants), colorectal cancer (15), lung cancer (12), prostate cancer (8), and multiple cancer types (6). Figure 3. Open in new tabDownload slide Population(s) included in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on the specified population or individual diagnosed with the specified cancer. “Noncancer population” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer and are not being screened for a specific types of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. Grants may have been categorized in more than 1 population category. Figure 3. Open in new tabDownload slide Population(s) included in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on the specified population or individual diagnosed with the specified cancer. “Noncancer population” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer and are not being screened for a specific types of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. Grants may have been categorized in more than 1 population category. Table 3 presents information on the proportion of grants specifying age group and underserved or minority populations. The age group of the study population was not specified in 128 grants (87.7%). Among the grants in which the age groups of the study population were specified, age groups included adolescent or young adult (11 grants), pediatric (age 0-17 years, 7 grants), adults (age 40-65 years, 4 grants), and older adults (age >65 years, 4 grants). Underserved or minority population status was not specified for 104 grants (71.2%). Among the grants for which this status was specified, 14 (9.6%) included a focus on low–socioeconomic status individuals. Other target populations included persons living with HIV (11 grants), Hispanic or Latinx individuals (6), Black or African American individuals (5), Asian or Asian American individuals (4), individuals in medically underserved communities (3), minority sexual identity or sexual orientation individuals (2), and American Indian or Native American individuals (1). Table 3. Funded cancer health economics grants including individuals from specified age groups or underserved populations Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Open in new tab Table 3. Funded cancer health economics grants including individuals from specified age groups or underserved populations Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Open in new tab Study Outcomes Figure 4 presents the clinical outcomes from the 146 identified grants. The most frequently identified clinical outcome was screening or diagnosis, observed in 54 grants (37.0%), followed by behavior change (eg, smoking cessation) in 51 grants (34.9%). Other clinical outcomes included quality of life or well-being (33 grants), treatment (12 grants), incidence or prevalence (10 grants), patient knowledge (10 grants), survival or mortality (10 grants), symptoms or complications (10 grants), quality of care (9 grants), caregiver-specific outcomes (4 grants), and receipt of survivorship care (3 grants). Other clinical outcomes beyond those listed were seen in 14 grants, whereas 4 grants did not include a clinical outcome and 2 grants did not specify the clinical outcome in the abstract or specific aims section. Figure 4. Open in new tabDownload slide Clinical outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified clinical outcomes. Grants may have been categorized as including more than 1 clinical outcome. QoL = quality of life. Figure 4. Open in new tabDownload slide Clinical outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified clinical outcomes. Grants may have been categorized as including more than 1 clinical outcome. QoL = quality of life. Figure 5 illustrates the economic outcomes for the grants included in the portfolio analysis. Cost-effectiveness analysis was the most frequently reported economic outcome, specified in 97 grants (66.4%). Although performing cost-effectiveness analysis requires cost analyses (eg, comparison of costs between 2 interventions), grants that indicated cost-effectiveness analysis as an economic outcome were not also coded as including medical care cost, patient cost, or other cost analyses as an economic outcome unless these other cost analyses were specifically listed in the grant’s title, abstract, or specific aims. After cost-effectiveness analysis, the next most common economic outcome was other or unspecified cost analysis (36 grants). This economic outcome corresponds to grants that indicated comparisons of costs but did not specify the nature of these costs, that is, whether the costs represented economic value from the patient, health-care system, society, or some other perspective. Other identified economic outcomes were medical care cost analysis, also described as cost-of-care analysis (23 grants); policy impact, assessments of the effects government or private sector policies on clinical and/or economic outcomes (20 grants); financial hardship, assessments of the adverse impacts of cost resulting from care on patients, their families, and/or caregivers (15 grants); patient cost analysis, also described as out-of-pocket cost analysis (11 grants); cost-benefit analysis (4 grants); implementation costs, that is, the costs to implement or scale-up a program or intervention (3 grants); and value of information analysis (3 grants). Six grants included other economic outcomes. Figure 5. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified economic outcomes. Grants may have been categorized as including more than 1 economic outcome. Figure 5. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified economic outcomes. Grants may have been categorized as including more than 1 economic outcome. Relationship Between Cancer Control Continuum Topic and Economic Outcome Studies involving different topics in the cancer control continuum may focus on different types of economic questions and therefore may include different economic outcomes. Figure 6 illustrates the most frequently included economic outcomes for grants stratified by cancer continuum topic. Prevention and screening grants showed similar patterns, with a predominance of cost-effectiveness analysis followed by medical or other cost analysis (which included unspecified cost analysis and patient cost analysis). Prevention and screening grants included a small number of policy analysis studies, and, as expected, neither included any studies examining financial hardship because this outcome is associated with cancer treatment and survivorship. Among cancer treatment grants, there were approximately equal numbers focused on cost-effectiveness and medical or other cost analysis and greater proportions of policy impact studies and financial hardship studies than observed for prevention or screening grants. Finally, medical or other cost analysis were the most frequent economic outcome in survivorship studies, with equal numbers of studies including cost-effectiveness analysis and financial hardship. Figure 6. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants stratified by cancer continuum topic. Among the 146 funded National Cancer Institute grants including economic analyses, the percent of grants categorized as focusing on each cancer control continuum area (prevention, screening, treatment, or survivorship) that included cost-effectiveness, medical or other costs, policy impacts, or financial hardship as an economic outcome. Grants may have been categorized in more than one cancer control continuum area and may have been categorized as including more than 1 economic outcome. Solid bars: cost-effectivenss grants; horizontal line bars: medical or other cost grants; vertical line bars: policy impact grants; dotted bars: financial hardship grants. Figure 6. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants stratified by cancer continuum topic. Among the 146 funded National Cancer Institute grants including economic analyses, the percent of grants categorized as focusing on each cancer control continuum area (prevention, screening, treatment, or survivorship) that included cost-effectiveness, medical or other costs, policy impacts, or financial hardship as an economic outcome. Grants may have been categorized in more than one cancer control continuum area and may have been categorized as including more than 1 economic outcome. Solid bars: cost-effectivenss grants; horizontal line bars: medical or other cost grants; vertical line bars: policy impact grants; dotted bars: financial hardship grants. Discussion This portfolio analysis provides detailed information on grants funded by NCI in the time period 2015-2020 that included economic analyses. Several conclusions can be drawn from the portfolio analysis. First, relatively few funded grants during this time included economic analyses; we identified economic analyses in only 0.9% of all funded NCI grants and 2.4% of funded R01 grants. In addition, grants that included economic analyses focused differentially on specific topics of the cancer control continuum. For example, the identified grants were more likely to focus on cancer prevention or screening, whereas few cancer survivorship or end-of-life studies included economic analyses (Figure 2). In general, there is much less published literature focused on economic aspects of cancer survivorship or end-of-life care than on the economics of other part of the cancer control continuum. In addition, this portfolio analysis included only NCI-funded grants; some NIH grants in these areas may be funded by the National Institute of Nursing Research, which has an Office of End-of-Life and Palliative Care Research. However, although relatively small, the NCI portfolio of funded grants including economic analyses is diverse, covering a range of cancer types, methods, and economic outcomes, including analyses of policy impacts and financial hardship. Another manuscript included in this Supplement providing an overview of recently published cancer health economics review articles found that the largest group of included reviews focused on cancer treatment (5). This difference from the results of this portfolio analysis, which found that a majority of funded NCI grants including economic analyses focused on cancer prevention and screening, may reflect the nature of review articles and motivations for publishing economic analyses. That is, review articles tend to be prepared when there is new literature to be summarized. Published literature related to new oncology agents or other treatment modalities may be more likely to include economic analyses for coverage or pricing objectives (regardless of whether such analyses were NCI grant-funded); there may not be the same focus on including economic analyses in published studies of cancer prevention or screening interventions. Thus, there may be less literature for review articles on the economics of cancer prevention or screening despite the greater proportion of NCI grants with economic analyses that focused on these areas of the cancer control continuum. During the portfolio analysis period, all funded NCI research grants including economic analyses were funded through parent mechanisms (eg, the Modular R01s in Cancer Control and Population Science, PAR-21-190). There were no major NCI funding opportunity initiatives during this time focused on cancer health economics research other than a P30 supplement opportunity related to financial hardship. In 2021, NCI released a Notice of Special Interest administrative supplement funding opportunity specifically focused on cancer health economics research, titled “Modifiable Factors Potentially affecting the Cost of Cancer Treatment” (NOT-CA-21-055, https://grants.nih.gov/grants/guide/notice-files/NOT-CA-21-055.html). Although NCI may provide other funding opportunities with a cancer health economics research focus in the future, it is clear that parent funding mechanisms have been used to fund research in this area. The largest group of grants including economic analyses were R01s; this is not unexpected, because this is one of the main types of research funding from NCI. However, the second largest group, comprising 11% of funded grants with economic analyses, were training and career development awards (K and F grants). At the NCI-hosted “Future of Cancer Health Economics Research” virtual conference held in December 2020 (6), which is the basis for this Supplement, there was considerable interest in future training opportunities related to cancer health economics research. Results from the portfolio analysis suggest that the available F and K mechanism can be used to fund training or career development in this field. Trainees and mentors interested in these opportunities may want to contact the NCI Center for Cancer Training (https://www.cancer.gov/grants-training/training/funding) for more information. There are a number of limitations in this portfolio analysis. First, we analyzed only grant proposals that were funded by NCI. We did not include information on grant proposals that were submitted to NCI but not funded or grant proposals potentially relevant to cancer health economics research that were funded and administered by other NIH institutes or centers outside of the NCI. In addition, we may not have identified all funded NCI grants that included economic analyses. Although the set of text phrases and RCDC terms listed in the Methods section is fairly comprehensive (and was iteratively tested), we may have missed certain terms that would have yielded additional relevant results. Finally, we were able to search only grant titles, abstracts, and specific aims sections to identify those grants including economic analyses. It is possible that some grants included economic analyses but did not specify this in their abstracts or specific aims. However, if an economic analysis was not mentioned in the abstract or specific aims, it is unlikely to be a major (or even moderate) component of the study. Despite these limitations, this portfolio analysis suggests important steps to support the future of cancer health economics research. The NCI and other NIH institutes fund health economic research in keeping with the stated NIH priorities as part of scientifically rigorous, high-quality, and innovative proposals (1). Investigators are encouraged to discuss ideas for studies including cancer health economics research with colleagues and with NCI program directors and to participate in the proposal development and submission process. Information on NCI Research Program Contacts can be found at https://www.cancer.gov/grants-training/grants-funding/contacts. In addition, it is critical that NIH study sections include reviewers with expertise in health economics research and related fields. Interested researchers are encouraged to volunteer to serve as reviewers (https://public.csr.nih.gov/ForReviewers/BecomeAReviewer). Finally, cancer health economic analyses tend to be small components of funded NCI grants. Some health economics researchers may not feel comfortable leading or coleading grant proposals. These researchers may want to explore information available from NIH on grant proposal development and submission and partner with colleagues who have more experience in this area. Notes Role of the funder: No funding was received for this study and the authors indicate no conflicts of interest. Disclosures: None. Author contributions: All authors participated in the conceptualization, data curation, formal analysis, investigation, validation, and writing of this study. MTH and PT participate in visualization. Disclaimer: The views expressed here are those of the authors and do not necessarily represent any official position of the National Cancer Institute or National Institutes of Health. Prior presentations: A version of this study was presented at the 2020 “Future of Cancer Health Economics Research” virtual conference and as a poster at the 2020 ASCO Annual Meeting. References 1 National Institutes of Health. Clarifying NIH priorities for health economics research. https://grants.nih.gov/grants/guide/notice-files/not-od-16-025.html. Accessed July 9, 2021 . 2 Singer D. Portfolio analysis—an experimental space. https://dpcpsi.nih.gov/pdf/CoC-111609-Singer-PortfolioAnalysis.pdf. Accessed July 9, 2021 . 3 National Institutes of Health Division of Program Coordination, Planning, and Strategic Initiatives, Office of Portfolio Analysis. Portfolio Analysis FAQs. https://dpcpsi.nih.gov/opa/portfolio-analysis-faqs. Accessed July 9, 2021. 4 Mollica MA , Tesauro G, Tonorezos ES, et al. Current state of funded National Institutes of Health grants focused on individuals living with advanced and metastatic cancers: a portfolio analysis . J Cancer Surviv . 2021 ; 15 ( 3 ): 370 – 374 . Google Scholar Crossref Search ADS PubMed WorldCat 5 Davidoff AJ , Akif K, Halpern MT. Research on the economics of cancer-related care: an overview of the review literature . J Natl Cancer Inst . 2022 . Google Scholar OpenURL Placeholder Text WorldCat 6 National Cancer Institute. Future of Cancer Health Economics Research Virtual Conference, December 2020. https://healthcaredelivery.cancer.gov/heroic/conference.html. Accessed July 9, 2021. Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JNCI Monographs Oxford University Press

Current State of Funded National Cancer Institute Grants That Include Economic Analyses

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Oxford University Press
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Copyright © 2022 Oxford University Press
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1052-6773
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1745-6614
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10.1093/jncimonographs/lgac002
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Abstract

Abstract Background Health economics research is an integral part of the transdisciplinary research supported by the National Cancer Institute (NCI). To better understand NCI activities in this area, we conducted a portfolio analysis of funded NCI grants including health economics research. Methods We examined all competitive grants funded by NCI from fiscal years 2015 to 2020 that included economic analyses or outcomes. Grant titles, abstracts, and specific aims were independently reviewed by 2 study team members; content of included grants was then coded for analysis. Results A total 212 grants were identified from searches; 146 of these included economic analyses and were included in the portfolio analysis. These 146 grants represent approximately 0.9% of all NCI competitively funded grants awarded 2015-2020. Of these grants, 100 were R01 awards, representing approximately 2.4% of all NCI R01 grants funded 2015-2020. The most common study type was interventional randomized controlled-trial, followed by simulation or model. Screening and prevention were the most frequent grant cancer continuum topic; survivorship was included in only 16 grants (11.0%). Cost-effectiveness analysis was the most frequently listed economic outcome (97 grants, 66.4%), whereas policy impact (20 grants, 13.7%) and financial hardship (15 grants, 10.3%) were less-frequently included economic outcomes. However, economic outcomes differed by cancer control continuum topic, with financial hardship being included in a greater proportion of treatment and survivorship grants. Conclusions Although relatively small, the NCI portfolio of funded grants including economic analyses is diverse, covering a range of cancer types, methods, and economic outcomes, and increasing over time. As the largest public funder of biomedical research, the National Institutes of Health (NIH) has specified priorities for health economics research (1). As stated in these priorities, “NIH is especially interested in health economics research designed to understand how innovations in treatment, diagnosis, prevention, and implementation strategies can be most effectively deployed to improve health and well-being” (1). That is, NIH is most interested in “applications involving health economics research in which health outcomes and health-related behaviors are the primary focus, and the connection between the subject(s) of the study and improved understanding of health are clear and explicit” (1). For example, this could include studies focused on: Determining the impact of financial and nonfinancial incentives on health-related behaviors, health-care use, and health outcomes; or Assessing how environmental, social, economic, and other factors affect health status, health-related behaviors, health-care use, health outcomes, health disparities, and responses to interventions. Portfolio analysis is an approach used by NIH to identify research and funding trends, recognize gaps, and evaluate potential opportunities for new investments (2, 3). Portfolio analysis is often performed by NIH researchers to assess the current state of funding for specific areas of interest; for example, a recently published portfolio analysis examined NIH funding of grants focused on individuals with advanced or metastatic cancers (4). The National Cancer Institute (NCI) is one of 27 institutes and centers that constitute the NIH. Given the importance of health economics research across the cancer control continuum and the need to better understand NCI activities related to this area, we conducted a portfolio analysis of funded NCI grants including health economics research. Methods This portfolio analysis examined all competitive grants funded by NCI from fiscal years 2015-2020 that included economic analyses or outcomes. Funded grants were identified using the NIH Query/View/Report (QVR) system. Only competitively reviewed grants (either new grant submissions or competitive renewals) for which NCI was the primary funding institute were examined. QVR System The QVR System was developed to enable the NIH extramural staff to search and view detailed information about NIH extramural applications and awards. Public (non-NIH) users have access to the NIH Research Portfolio Online Reporting Tools to access and search reports, data, and analyses of NIH research activities (https://reporter.nih.gov/). For this portfolio analysis, QVR was chosen as the grants search tool because of its capabilities for research coding and classification searches and keyword text searches in both the (public) abstract and (nonpublic) specific aims. Grant Search Strategy We identified funded grants including economic analyses, with economic analyses defined as either 1) economic outcomes (eg, costs, cost-effectiveness, financial hardship); 2) studies related to the economics of cancer care delivery (eg, who pays for cancer care, how much is paid, and who receives payment); or 3) studies of impacts of health economic policies, insurance, and health-care reforms. Using QVR, we were able to search funded NCI grants using either words or phrases in grant titles, abstracts, and specific aims section and using NIH Research, Condition, and Disease Categorization (RCDC) terms. RCDC is a computerized process used by NIH to categorize funding in medical research; more information on RCDC is available at https://era.nih.gov/about-era/nih-and-grantor/other/rcdc.htm. We performed several initial iterative test searches and reviews to inform keywords and text fields to use for final search parameters. The final search criteria included 24 RCDC terms and 27 text words or phrases searched for in grant titles, abstracts, and specific aims. The included RCDC terms were: Economic impact; cost effectiveness; cost-effectiveness evaluation; economic evaluation; comparative cost effectiveness; economic outcome; cost effectiveness analysis; cost savings; cost-benefit analysis; financial support; financial hardship; financial toxicity; uninsured medical expense; willingness to pay; cost analysis; medical care cost; economic impact; economic implications; costs and benefits; policy analysis; cost benefit economics; economic cost; economic policy; economic value. The included text words/phrases were: Cost-effectiveness; incremental cost; budget impact; cost-benefit analysis; out of pocket expenses; out-of-pocket payments; out-of-pocket costs; cost and effectiveness; cost and outcomes; costs and outcomes; direct medical costs; willingness-to-pay; cost drivers; cost trajectory; cost trajectories; financial hardship; financial toxicity; economic analysis; payment; payments; econometric; econometrics; health economics; accountable care; all payer claims; financial navigation; value of information. All competitively funded NCI grants from 2015-2020 with 1 or more of the RCDC terms or text phrases were identified. Grant titles, abstracts, and specific aims sections were independently reviewed by 2 members of the study team (the authors of this manuscript) to assess whether they included economic analyses. Any disagreements regarding grant inclusion or exclusion were discussed with a third member of the study team and resolved. Grant Coding and Curation NIH systems automatically coded certain grant attributes such as fiscal year of funding initiation and type of funding mechanism. To better understand and analyze research trends in funded cancer health economics grants, the study team developed additional curation codes classifying identified grants using the category options listed below. These codes were developed and refined through an iterative process based on trends that emerged from reviews of the identified grants: Cancer continuum: prevention; screening; treatment; survivorship; end of life; not specified. Screening-focused grants were not coded as prevention unless separate prevention activities were also included in the grant. Study type: interventional randomized controlled trial (RCT); interventional non-RCT; observational; cohort; retrospective; simulation or model; other. Study cancer population: noncancer patients; breast; cervical; colorectal; lung; prostate; other; multiple; not specified. “Noncancer patients” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer or are not being screened for a specific type of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. For example, the cancer population of grants examining fecal immunochemical testing or colonoscopy was classified as colorectal cancer. Age range: pediatric; adolescent or young adult; adult (40-65 years); older adult (>65 years); not specified; not applicable. Minority or underserved population: Black or African American; Hispanic or Latinx; Asian or Asian American; American Indian or Native American; low socioeconomic status; person with HIV; sexual identity or sexual orientation; “medically underserved” (individuals from an officially designated medically underserved area); other; not specified. Clinical outcome: behavior change; caregiver outcome; incidence or prevalence; quality of care; quality of life or well-being; patient knowledge; screening or diagnosis; survival; survivorship care; symptoms; treatment; other; none. Economic outcome: cost-benefit; cost-effectiveness; financial hardship; medical care costs; implementation costs; patient costs; other or unspecified costs; policy impact; value of information; economic analysis (unspecified); other. Regarding study type, both cohort and observational studies involved prospective data collection in noninterventional studies. Cohort studies were defined as focusing on a specified initial population at the start of the study, and no new individuals entered this population during the study. In contrast, observational studies involved individuals who entered the study population over time. Retrospective studies did not include prospective data collection but analyzed data that were already available at study initiation. All grants were coded independently by 2 members of the study team; differences in coding were resolved in discussions with a third member of the team. Except for fiscal year and funding mechanism, coding options were not mutually exclusive; that is, grants could be coded with more than 1 option. Results A total of 212 grants were identified using text word or phrase and RCDC term searches. Following review of grant titles, abstracts, and specific aims sections, 148 of these grants (69.8%) were identified as including economic analyses. On closer examination, 2 of these grants were loan repayment request proposals (L30 awards); because these did not describe proposed research, they were excluded from the portfolio analysis, leaving 146 grants for the analysis. The number of grants identified and screened at each stage of this portfolio analysis are highlighted in Supplemental Figure 1 (available online). The 146 grants represent approximately 0.9% of all competitively funded grants awarded by NCI during the 2015-2020 time period. Of these grants, 100 were R01 awards (also known as Research Project Grants). These 100 R01 awards represent approximately 2.4% of all R01 grants funded by NCI during the 2015-2020 time period. Characteristics of Funded NCI Grants Including Economic Analyses Table 1 lists the funding mechanism and fiscal year for the 146 included grants. A majority of grants (100, 68.5%) were R01 awards. The next largest category was training and career development awards (F and K mechanisms), corresponding to 16 grants (11%). Other funding mechanisms for economic analysis grants were U01 (9 grants); R21 or R03 (6 grants); R42, R43, or R44 small business awards (6 grants); R37 (MERIT) awards (5 grants); and P01 or P50 awards (4 grants). Fewer grants (16-20 per year) were funded from 2015 to 2017. The number funded increased to 23 in 2018, 33 in 2019, and 38 and 2020. One grant was based at a foreign (non-US) institution; 24 grants had a US-based primary institution but involved a collaborating foreign institution. Table 1. Fiscal year and funding mechanism of funded cancer health economics research grants Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) aK awards: Research Career Development Awards. F awards: Individuals Research Fellowships. bMERIT = Method to Extend Research in Time Award. Open in new tab Table 1. Fiscal year and funding mechanism of funded cancer health economics research grants Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) Fiscal year of grant funding . No. of grants .  2015 16 (11.0%)  2016 20 (13.7%)  2017 16 (11.0%)  2018 23 (15.8%)  2019 33 (22.6%)  2020 38 (26.0%) Funding mechanism  R01 100 (68.5%)  Training or career (K & F)a 16 (11.0%)  U01 9 (6.2%)  R21 or R03 6 (4.1%)  Small business (R42, R43, or R44) 6 (4.1%)  R37 (MERIT)b 5 (3.4%)  P01 or P50 4 (2.8%) aK awards: Research Career Development Awards. F awards: Individuals Research Fellowships. bMERIT = Method to Extend Research in Time Award. Open in new tab Table 2 provides information on total funding (direct plus indirect) of the 146 grants including economic analyses by year, total funding for all NCI new and competing awards by year (as reported by the NCI Research Portfolio Online Reporting Tools; https://reporter.nih.gov/search/PCXPeHy9JEKDVTHptqZaqA/projects/charts?shared=true) and the proportion of total funding attributable to the 146 grants including economic analyses. Overall, the 146 grants including economic analyses represented slightly less than 1% of all funding for NCI new and competing awards in the 2015-2020 period. However, the total for all NCI new and competing award funding (the “denominator”) includes awards that were excluded from the portfolio analysis such as L30 loan repayment awards. Therefore, the proportion of funding attributable to these 146 grants is slightly greater than is shown in this table. Table 2. Funding for NCI-funded grants including economic analysis and for all NCI new and competing awards by fiscal yeara Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% a NCI = National Cancer Institute. Open in new tab Table 2. Funding for NCI-funded grants including economic analysis and for all NCI new and competing awards by fiscal yeara Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% Fiscal year . Funded grants including economic analyses . All NCI new and competing awards . Proportion of funding among grants with economic analyses . 2015 $12 341 674 $1 573 540 298 0.78% 2016 $11 494 851 $1 638 357 170 0.70% 2017 $8 082 526 $1 732 494 471 0.47% 2018 $10 042 720 $1 927 854 417 0.52% 2019 $24 533 620 $2 145 161 787 1.14% 2020 $33 509 909 $2 107 391 414 1.59% Total $100 005 300 $11 124 799 557 0.90% a NCI = National Cancer Institute. Open in new tab Characteristics of Studies Figure 1 presents information on the study type(s) of the 146 grants including economic analyses. Study types (and other characteristics presented in this article) are not mutually exclusive; funded grants may have included and been classified as having more than one study type. The most common study type was interventional RCT, seen in 67 (45.9%) grants. Simulation or model was the next most frequently observed study type (39 grants), followed by retrospective (23), observational (18), interventional non-RCT (11), and cohort studies (2). Four grants included other or undefined study types. Figure 2 illustrates the topics of the cancer control continuum addressed by the identified grants. Prevention was the most frequently noted continuum topic, with 55 grants (37.7%). Screening was included in a similar number of grants (48), followed by treatment (43), whereas survivorship was included in only 16 grants (11.0%) and end-of-life care in only 2 grants (1.4%). Three grants did not specify the cancer continuum topic. Figure 1. Open in new tabDownload slide Study type(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized in each study type. Grants may have been categorized in more than 1 study type. Figure 1. Open in new tabDownload slide Study type(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized in each study type. Grants may have been categorized in more than 1 study type. Figure 2. Open in new tabDownload slide Cancer control continuum area(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on prevention, screening, treatment, survivorship, or end of life care. Grants may have been categorized in more than 1 cancer control continuum area. Figure 2. Open in new tabDownload slide Cancer control continuum area(s) of funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on prevention, screening, treatment, survivorship, or end of life care. Grants may have been categorized in more than 1 cancer control continuum area. Characteristics of Study Cancer Populations Figure 3 presents the cancer population(s) included in identified grants. For grants that examined prevention strategies targeting multiple cancer types (eg, smoking cessation or prevention, dietary or physical activity interventions) among individuals who had not been diagnosed with cancer, the study population type was classified as “noncancer patients.” This was the largest single category, corresponding to 44 grants (30.1%). Breast cancer was the next largest group (22 grants), which included both grants including individuals diagnosed with breast cancer and grants focused on screening for breast cancer. The cancer population of study was not specified in the title, abstract, or specific aims section for 22 grants, and other cancer types (ie, cancer types beyond those specified in the coding choices, such as head and neck cancers) were specified in 21 grants. Other cancer populations included cervical cancer (16 grants), colorectal cancer (15), lung cancer (12), prostate cancer (8), and multiple cancer types (6). Figure 3. Open in new tabDownload slide Population(s) included in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on the specified population or individual diagnosed with the specified cancer. “Noncancer population” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer and are not being screened for a specific types of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. Grants may have been categorized in more than 1 population category. Figure 3. Open in new tabDownload slide Population(s) included in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as focusing on the specified population or individual diagnosed with the specified cancer. “Noncancer population” refers mainly to prevention-focused studies of individuals who have not been diagnosed with cancer and are not being screened for a specific types of cancer. Although screening studies included individuals who had not been diagnosed with cancer, the cancer population for these grants was classified based on the type of cancer that was the focus of the screening test. Grants may have been categorized in more than 1 population category. Table 3 presents information on the proportion of grants specifying age group and underserved or minority populations. The age group of the study population was not specified in 128 grants (87.7%). Among the grants in which the age groups of the study population were specified, age groups included adolescent or young adult (11 grants), pediatric (age 0-17 years, 7 grants), adults (age 40-65 years, 4 grants), and older adults (age >65 years, 4 grants). Underserved or minority population status was not specified for 104 grants (71.2%). Among the grants for which this status was specified, 14 (9.6%) included a focus on low–socioeconomic status individuals. Other target populations included persons living with HIV (11 grants), Hispanic or Latinx individuals (6), Black or African American individuals (5), Asian or Asian American individuals (4), individuals in medically underserved communities (3), minority sexual identity or sexual orientation individuals (2), and American Indian or Native American individuals (1). Table 3. Funded cancer health economics grants including individuals from specified age groups or underserved populations Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Open in new tab Table 3. Funded cancer health economics grants including individuals from specified age groups or underserved populations Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Included age groups . No. of grants (%) .  Pediatric individuals (age 0-17 y) 7 (4.8%)  Adolescent or young adult individuals (age 18-39 y) 11 (7.5%)  Adult individuals (age 40-65 y) 4 (2.7%)  Older adult individuals (age 65+ y) 4 (2.7%) Included underserved populations  Low socioeconomic status 14 (9.6%)  Persons living with HIV 11 (7.5%)  Individuals from rural communities 10 (6.8%)  American Indian or Alaskan Native individuals 1 (0.7%)  Asian or Asian American individuals 4 (2.7%)  Black or African American individuals 5 (3.4%)  Hispanic or Latinx individuals 6 (4.1%)  Individuals from “medically underserved” communities 3 (2.1%)  Minority sexual orientation or gender identity individuals 2 (1.4%) Open in new tab Study Outcomes Figure 4 presents the clinical outcomes from the 146 identified grants. The most frequently identified clinical outcome was screening or diagnosis, observed in 54 grants (37.0%), followed by behavior change (eg, smoking cessation) in 51 grants (34.9%). Other clinical outcomes included quality of life or well-being (33 grants), treatment (12 grants), incidence or prevalence (10 grants), patient knowledge (10 grants), survival or mortality (10 grants), symptoms or complications (10 grants), quality of care (9 grants), caregiver-specific outcomes (4 grants), and receipt of survivorship care (3 grants). Other clinical outcomes beyond those listed were seen in 14 grants, whereas 4 grants did not include a clinical outcome and 2 grants did not specify the clinical outcome in the abstract or specific aims section. Figure 4. Open in new tabDownload slide Clinical outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified clinical outcomes. Grants may have been categorized as including more than 1 clinical outcome. QoL = quality of life. Figure 4. Open in new tabDownload slide Clinical outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified clinical outcomes. Grants may have been categorized as including more than 1 clinical outcome. QoL = quality of life. Figure 5 illustrates the economic outcomes for the grants included in the portfolio analysis. Cost-effectiveness analysis was the most frequently reported economic outcome, specified in 97 grants (66.4%). Although performing cost-effectiveness analysis requires cost analyses (eg, comparison of costs between 2 interventions), grants that indicated cost-effectiveness analysis as an economic outcome were not also coded as including medical care cost, patient cost, or other cost analyses as an economic outcome unless these other cost analyses were specifically listed in the grant’s title, abstract, or specific aims. After cost-effectiveness analysis, the next most common economic outcome was other or unspecified cost analysis (36 grants). This economic outcome corresponds to grants that indicated comparisons of costs but did not specify the nature of these costs, that is, whether the costs represented economic value from the patient, health-care system, society, or some other perspective. Other identified economic outcomes were medical care cost analysis, also described as cost-of-care analysis (23 grants); policy impact, assessments of the effects government or private sector policies on clinical and/or economic outcomes (20 grants); financial hardship, assessments of the adverse impacts of cost resulting from care on patients, their families, and/or caregivers (15 grants); patient cost analysis, also described as out-of-pocket cost analysis (11 grants); cost-benefit analysis (4 grants); implementation costs, that is, the costs to implement or scale-up a program or intervention (3 grants); and value of information analysis (3 grants). Six grants included other economic outcomes. Figure 5. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified economic outcomes. Grants may have been categorized as including more than 1 economic outcome. Figure 5. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants. Among the 146 funded National Cancer Institute grants including economic analyses, the proportion of grants categorized as including each of the specified economic outcomes. Grants may have been categorized as including more than 1 economic outcome. Relationship Between Cancer Control Continuum Topic and Economic Outcome Studies involving different topics in the cancer control continuum may focus on different types of economic questions and therefore may include different economic outcomes. Figure 6 illustrates the most frequently included economic outcomes for grants stratified by cancer continuum topic. Prevention and screening grants showed similar patterns, with a predominance of cost-effectiveness analysis followed by medical or other cost analysis (which included unspecified cost analysis and patient cost analysis). Prevention and screening grants included a small number of policy analysis studies, and, as expected, neither included any studies examining financial hardship because this outcome is associated with cancer treatment and survivorship. Among cancer treatment grants, there were approximately equal numbers focused on cost-effectiveness and medical or other cost analysis and greater proportions of policy impact studies and financial hardship studies than observed for prevention or screening grants. Finally, medical or other cost analysis were the most frequent economic outcome in survivorship studies, with equal numbers of studies including cost-effectiveness analysis and financial hardship. Figure 6. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants stratified by cancer continuum topic. Among the 146 funded National Cancer Institute grants including economic analyses, the percent of grants categorized as focusing on each cancer control continuum area (prevention, screening, treatment, or survivorship) that included cost-effectiveness, medical or other costs, policy impacts, or financial hardship as an economic outcome. Grants may have been categorized in more than one cancer control continuum area and may have been categorized as including more than 1 economic outcome. Solid bars: cost-effectivenss grants; horizontal line bars: medical or other cost grants; vertical line bars: policy impact grants; dotted bars: financial hardship grants. Figure 6. Open in new tabDownload slide Economic outcomes in funded cancer health economics grants stratified by cancer continuum topic. Among the 146 funded National Cancer Institute grants including economic analyses, the percent of grants categorized as focusing on each cancer control continuum area (prevention, screening, treatment, or survivorship) that included cost-effectiveness, medical or other costs, policy impacts, or financial hardship as an economic outcome. Grants may have been categorized in more than one cancer control continuum area and may have been categorized as including more than 1 economic outcome. Solid bars: cost-effectivenss grants; horizontal line bars: medical or other cost grants; vertical line bars: policy impact grants; dotted bars: financial hardship grants. Discussion This portfolio analysis provides detailed information on grants funded by NCI in the time period 2015-2020 that included economic analyses. Several conclusions can be drawn from the portfolio analysis. First, relatively few funded grants during this time included economic analyses; we identified economic analyses in only 0.9% of all funded NCI grants and 2.4% of funded R01 grants. In addition, grants that included economic analyses focused differentially on specific topics of the cancer control continuum. For example, the identified grants were more likely to focus on cancer prevention or screening, whereas few cancer survivorship or end-of-life studies included economic analyses (Figure 2). In general, there is much less published literature focused on economic aspects of cancer survivorship or end-of-life care than on the economics of other part of the cancer control continuum. In addition, this portfolio analysis included only NCI-funded grants; some NIH grants in these areas may be funded by the National Institute of Nursing Research, which has an Office of End-of-Life and Palliative Care Research. However, although relatively small, the NCI portfolio of funded grants including economic analyses is diverse, covering a range of cancer types, methods, and economic outcomes, including analyses of policy impacts and financial hardship. Another manuscript included in this Supplement providing an overview of recently published cancer health economics review articles found that the largest group of included reviews focused on cancer treatment (5). This difference from the results of this portfolio analysis, which found that a majority of funded NCI grants including economic analyses focused on cancer prevention and screening, may reflect the nature of review articles and motivations for publishing economic analyses. That is, review articles tend to be prepared when there is new literature to be summarized. Published literature related to new oncology agents or other treatment modalities may be more likely to include economic analyses for coverage or pricing objectives (regardless of whether such analyses were NCI grant-funded); there may not be the same focus on including economic analyses in published studies of cancer prevention or screening interventions. Thus, there may be less literature for review articles on the economics of cancer prevention or screening despite the greater proportion of NCI grants with economic analyses that focused on these areas of the cancer control continuum. During the portfolio analysis period, all funded NCI research grants including economic analyses were funded through parent mechanisms (eg, the Modular R01s in Cancer Control and Population Science, PAR-21-190). There were no major NCI funding opportunity initiatives during this time focused on cancer health economics research other than a P30 supplement opportunity related to financial hardship. In 2021, NCI released a Notice of Special Interest administrative supplement funding opportunity specifically focused on cancer health economics research, titled “Modifiable Factors Potentially affecting the Cost of Cancer Treatment” (NOT-CA-21-055, https://grants.nih.gov/grants/guide/notice-files/NOT-CA-21-055.html). Although NCI may provide other funding opportunities with a cancer health economics research focus in the future, it is clear that parent funding mechanisms have been used to fund research in this area. The largest group of grants including economic analyses were R01s; this is not unexpected, because this is one of the main types of research funding from NCI. However, the second largest group, comprising 11% of funded grants with economic analyses, were training and career development awards (K and F grants). At the NCI-hosted “Future of Cancer Health Economics Research” virtual conference held in December 2020 (6), which is the basis for this Supplement, there was considerable interest in future training opportunities related to cancer health economics research. Results from the portfolio analysis suggest that the available F and K mechanism can be used to fund training or career development in this field. Trainees and mentors interested in these opportunities may want to contact the NCI Center for Cancer Training (https://www.cancer.gov/grants-training/training/funding) for more information. There are a number of limitations in this portfolio analysis. First, we analyzed only grant proposals that were funded by NCI. We did not include information on grant proposals that were submitted to NCI but not funded or grant proposals potentially relevant to cancer health economics research that were funded and administered by other NIH institutes or centers outside of the NCI. In addition, we may not have identified all funded NCI grants that included economic analyses. Although the set of text phrases and RCDC terms listed in the Methods section is fairly comprehensive (and was iteratively tested), we may have missed certain terms that would have yielded additional relevant results. Finally, we were able to search only grant titles, abstracts, and specific aims sections to identify those grants including economic analyses. It is possible that some grants included economic analyses but did not specify this in their abstracts or specific aims. However, if an economic analysis was not mentioned in the abstract or specific aims, it is unlikely to be a major (or even moderate) component of the study. Despite these limitations, this portfolio analysis suggests important steps to support the future of cancer health economics research. The NCI and other NIH institutes fund health economic research in keeping with the stated NIH priorities as part of scientifically rigorous, high-quality, and innovative proposals (1). Investigators are encouraged to discuss ideas for studies including cancer health economics research with colleagues and with NCI program directors and to participate in the proposal development and submission process. Information on NCI Research Program Contacts can be found at https://www.cancer.gov/grants-training/grants-funding/contacts. In addition, it is critical that NIH study sections include reviewers with expertise in health economics research and related fields. Interested researchers are encouraged to volunteer to serve as reviewers (https://public.csr.nih.gov/ForReviewers/BecomeAReviewer). Finally, cancer health economic analyses tend to be small components of funded NCI grants. Some health economics researchers may not feel comfortable leading or coleading grant proposals. These researchers may want to explore information available from NIH on grant proposal development and submission and partner with colleagues who have more experience in this area. Notes Role of the funder: No funding was received for this study and the authors indicate no conflicts of interest. Disclosures: None. Author contributions: All authors participated in the conceptualization, data curation, formal analysis, investigation, validation, and writing of this study. MTH and PT participate in visualization. Disclaimer: The views expressed here are those of the authors and do not necessarily represent any official position of the National Cancer Institute or National Institutes of Health. Prior presentations: A version of this study was presented at the 2020 “Future of Cancer Health Economics Research” virtual conference and as a poster at the 2020 ASCO Annual Meeting. References 1 National Institutes of Health. Clarifying NIH priorities for health economics research. https://grants.nih.gov/grants/guide/notice-files/not-od-16-025.html. Accessed July 9, 2021 . 2 Singer D. Portfolio analysis—an experimental space. https://dpcpsi.nih.gov/pdf/CoC-111609-Singer-PortfolioAnalysis.pdf. Accessed July 9, 2021 . 3 National Institutes of Health Division of Program Coordination, Planning, and Strategic Initiatives, Office of Portfolio Analysis. Portfolio Analysis FAQs. https://dpcpsi.nih.gov/opa/portfolio-analysis-faqs. Accessed July 9, 2021. 4 Mollica MA , Tesauro G, Tonorezos ES, et al. Current state of funded National Institutes of Health grants focused on individuals living with advanced and metastatic cancers: a portfolio analysis . J Cancer Surviv . 2021 ; 15 ( 3 ): 370 – 374 . Google Scholar Crossref Search ADS PubMed WorldCat 5 Davidoff AJ , Akif K, Halpern MT. Research on the economics of cancer-related care: an overview of the review literature . J Natl Cancer Inst . 2022 . Google Scholar OpenURL Placeholder Text WorldCat 6 National Cancer Institute. Future of Cancer Health Economics Research Virtual Conference, December 2020. https://healthcaredelivery.cancer.gov/heroic/conference.html. Accessed July 9, 2021. Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Journal

JNCI MonographsOxford University Press

Published: Jul 5, 2022

References