Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study.

BACKGROUND: Multicancer early detection (MCED) blood tests can detect a cancer signal from circulating cell-free DNA (cfDNA). PATHFINDER was a prospective cohort study investigating the feasibility of MCED testing for cancer screening. METHODS: In this prospective cohort study done in oncology and primary care outpatient clinics at seven US health networks, a convenience sample of adults aged 50 years or older without signs or symptoms of cancer consented to MCED testing. We collected blood, analysed cfDNA, and returned results to participants' doctors. If a methylation signature indicative of cancer was detected, predicted cancer signal origin(s) informed diagnostic assessment. The primary outcome was time to, and extent of, diagnostic testing required to confirm the presence or absence of cancer. This trial is registered at ClinicalTrials.gov, NCT04241796, and is completed. FINDINGS: Between Dec 12, 2019, and Dec 4, 2020, we recruited 6662 participants. 4204 (63·5%) of 6621 participants with analysable results were women, 2417 (36·5%) were men, and 6071 (91·7%) were White. A cancer signal was detected in 92 (1·4%) of 6621 participants with analysable results. 35 (38%) participants were diagnosed with cancer (true positives) and 57 (62%) had no cancer diagnosis (false positives). Excluding two participants whose diagnostic assessments began before MCED test results were reported, median time to diagnostic resolution was 79 days (IQR 37-219): 57 days (33-143) in true-positive and 162 days (44-248) in false-positive participants. Most participants had both laboratory tests (26 [79%] of 33 with true-positive results and 50 [88%] of 57 with false-positive results) and imaging (30 [91%] of 33 with true-positive results and 53 [93%] of 57 with false-positive results). Fewer procedures were done in participants with false-positive results (17 [30%] of 57) than true-positive results (27 [82%] of 33) and few had surgery (one with a false-positive result and three with a true-positive result). INTERPRETATION: This study supports the feasibility of MCED screening for cancer and underscores the need for further research investigating the test's clinical utility. FUNDING: GRAIL.

Symptom impact and health-related quality of life (HRQoL) assessment by cancer stage: a narrative literature review.

BACKGROUND: Cancer stage at diagnosis is an important prognostic indicator for patient outcomes, with detection at later stages associated with increased mortality and morbidity. The impact of cancer stage on patient-reported outcomes is poorly understood. This research aimed to understand symptom burden and health related quality of life (HRQoL) impact by cancer stage for ten cancer types: 1) ovarian, 2) lung, 3) pancreatic, 4) esophageal, 5) stomach, 6) head and neck, 7) colorectal, 8) anal, 9) cervical, and 10) liver and bile duct. METHODS: Ten narrative literature reviews were performed to identify and collate published literature on patient burden at different stages of disease progression. Literature searches were conducted using an AI-assisted platform to identify relevant articles published in the last five (2017-2022) or ten years (2012-2022) where articles were limited. Conference abstracts were searched for the last two years (2020-2022). The geographic scope was limited to the United States, Canada, Europe, and global studies, and only journal articles written in English were included. RESULTS: A total of 26 studies with results stratified by cancer stage at diagnosis (and before treatment) were selected for the cancer types of lung, pancreatic, esophageal, stomach, head and neck, colorectal, anal, and cervical cancers. Two cancer types, ovarian cancer, and liver and bile duct cancer did not return any search results with outcomes stratified by disease stage. A general trend was observed for worse patient-reported outcomes in patients with cancer diagnosed at an advanced stage of disease compared with diagnosis at an earlier stage. Advanced disease stage was associated with greater symptom impact including general physical impairments such as pain, fatigue, and interference with functioning, as well as disease/region-specific symptom burden. Poorer HRQoL was also associated with advanced disease with commonly reported symptoms including anxiety and depression. CONCLUSIONS: Overall, the general trend for greater symptom burden and poorer HRQoL seen in late stage versus early-stage disease across the included cancer types supports the importance for early diagnosis and treatment to improve patient survival and decrease negative impacts on disease burden and HRQoL.

Cancer incidence in immunocompromised patients: a single-center cohort study.

BACKGROUND: Diminished immune defense plays an important role in cancer development. Cancer risk in immunocompromised patients may differ. Identifying individuals with elevated cancer risk can inform strategies for routine cancer screening. This study aimed to understand and compare cancer incidence and risk in three patient groups: recipients of solid organ transplant (SOT) or hematopoietic stem cell transplant (HSCT); diagnosis of primary or secondary immunodeficiency disorder (PID/SID); and recipients of tumor necrosis factor inhibitor (TNF-i) therapy. METHODS: This retrospective cohort study used the University of Utah Health System database and Huntsman Cancer Institute tumor registry. Patients aged ≥18 years with SOT/HSCT, PID/SID or ≥ 3 months of TNF-i therapy were included. The date of transplant, diagnosis of PID/SID, or 1st TNF-i medication order date was defined as the index date. We calculated cumulative cancer incidence by Kaplan-Meier method. A Cox-proportional hazard regression model with a stepwise variable selection process was used to identify independent risk factors associated with the time to onset of a new primary cancer. RESULTS: In total, 13,887 patients were included which comprised of 2982 (21%) SOT/HSCT, 7542 (54%) PID/SID and 3363 (24%) patients receiving TNF-i. The mean (SD) age ranged from 46.8 (15) years - 50.4 (18.2) years. The proportion of white patients ranged from 72.3-84.8%. The estimated cumulative cancer incidence was 11.5% in the SOT/HSCT cohort, 14.3% in the PID/SID cohort, and 8.8% in the TNF-i cohort. The multivariable model adjusted for age, benign in-situ disease, Charlson Comorbidity Index, hypertension/cardiovascular disease/end stage renal disease, gender, race/ethnicity, and renal cyst as significant risk factors. The adjusted hazard ratios for cancer development in SOT/HSCT and PID/SID cohorts compared to the TNF-i cohort over the full follow-up period were 1.57 (95% CI: 1.16-2.13) and 2.14 (95% CI: 1.65-2.77), respectively. CONCLUSION: A significantly increased risk of cancer was observed in PID/SID patients and SOT/HSCT patients compared to TNF-i patients. Age ≥ 50 years, male gender, and clinical comorbidities were additional factors impacting cancer risk. PID/SID and SOT/HSCT patients may benefit from more intensive cancer screening.

Patient-reported outcomes associated with cancer screening: a systematic review.

BACKGROUND: Multi-cancer early detection tests have been developed to enable earlier detection of multiple cancer types through screening. As reflected by patient-reported outcomes (PROs), the psychosocial impact of cancer screening is not yet clear. Our aim is to evaluate the impact of cancer screening through PRO assessment. METHODS: A systematic review was conducted using MEDLINE, EMBASE, and reference lists of articles from January 2000 to August 2020 for relevant publications assessing the psychosocial impact of cancer screening before and within 1 year after screening in the general asymptomatic population, including following receipt of results. Studies focused on diagnostic evaluation or involving patients previously diagnosed with cancer were excluded. RESULTS: In total, 31 studies (12 randomized controlled trials; 19 observational studies) were included, reflecting PRO assessments associated with lung, breast, colorectal, anal, ovarian, cervical, and prostate cancer screening procedures. The most commonly assessed construct was symptoms of anxiety, using the State-Trait Anxiety Inventory. Cancer-specific distress and worry were also assessed using a broad range of measures. Overall, individuals tolerated screening procedures well with no major psychosocial effects. Of note, increases in symptoms of anxiety and levels of distress and worry were generally found prior to communication of screening results and following communication of indeterminate or positive results that required further testing. These negative psychosocial effects were, however, not long-lasting and returned to baseline relatively soon after screening. Furthermore, individuals with higher cancer risk, such as current smokers and those with a family history of cancer, tended to have higher levels of anxiety and distress throughout the screening process, including following negative or indeterminate results. CONCLUSIONS: The psychosocial impact of cancer screening is relatively low overall and short-lived, even following false-positive test results. Individuals with a higher risk of cancer tend to experience more symptoms of anxiety and distress during the screening process; thus, more attention to this group is recommended.

Increased healthcare costs by later stage cancer diagnosis.

BACKGROUND: Cancer represents a significant source of disease burden in the United States (US), both clinically and economically. Diagnosis and treatment of cancer at earlier stages may reduce this burden. To better understand potential impacts of earlier diagnosis, healthcare costs among patients with cancer were assessed by cancer type and stage at diagnosis. METHODS: A retrospective analysis was conducted using Optum's de-identified Integrated Claims-Clinical data set with Enriched Oncology, which includes data from Medicare Advantage and commercially insured members. Adult members newly diagnosed with solid tumor cancers, cancer stage at diagnosis (diagnosed 1/1/2016-6/30/2020), and continuous enrollment for at least one month post diagnosis were identified. Patients with breast, cervical, colorectal, lung, ovarian, or prostate cancer were reported. Mean standardized costs (2020 USD) were calculated in each month on an annual and cumulative basis through four years post-cancer diagnosis. In each month, costs were calculated for those with continuous enrollment and no death reported in the month. Mean annual cost per patient was estimated by summing month one to 12 mean costs and stratifying by stage at cancer diagnosis; annual year one to four costs were summed to determine cumulative costs. RESULTS: Among members diagnosed 2016-2020 with breast, cervical, colorectal, lung, ovarian, or prostate cancer, 20,422 eligible members were identified. Mean costs increased by stage of diagnosis across all cancers at the annual and cumulative level through year four post diagnosis. Cumulative mean costs grew over time at a relatively similar rate across stages I to III and more dramatically in stage IV, except for cervical and lung cancer where the rate was relatively stable or slightly fluctuated across stages and ovarian cancer where stages III and IV both increased more sharply compared to stages I and II. CONCLUSIONS: Mean annual and cumulative healthcare costs through year four post cancer diagnosis were significantly higher among those diagnosed at later versus earlier cancer stages. The steeper increase in cumulative costs among those diagnosed in stage IV for many cancer types highlights the importance of earlier cancer diagnosis. Earlier cancer diagnosis may enable more efficient treatment, improve patient outcomes and reduce healthcare costs.

Estimating the population health impact of a multi-cancer early detection genomic blood test to complement existing screening in the US and UK.

BACKGROUND: Multi-cancer early detection (MCED) next-generation-sequencing blood tests represent a potential paradigm shift in screening. METHODS: We estimated the impact of screening in the US and UK. We used country-specific parameters for uptake, and test-specific sensitivity and false-positive rates for current screening: breast, colorectal, cervical and lung (US only) cancers. For the MCED test, we used cancer-specific sensitivities by stage. Outcomes included the true-positive:false-positive (TP:FP) ratio; and the cost of diagnostic investigations among screen positives, per cancer detected (Diagcost). Outcomes were estimated for recommended screening only, and then when giving the MCED test to anyone without cancer detected by current screening plus similarly aged adults ineligible for recommended screening. RESULTS: In the US, current screening detects an estimated 189,498 breast, cervical, colorectal and lung cancers. An MCED test with 25-100% uptake detects an additional 105,526-422,105 cancers (multiple types). The estimated TP:FP (Diagcost) was 1.43 ($89,042) with current screening but only 1:1.8 ($7060) using an MCED test. For the UK the corresponding estimates were 1:18 (£10,452) for current screening, and 1:1.6 (£2175) using an MCED test. CONCLUSIONS: Adding an MCED blood test to recommended screening can potentially be an efficient strategy. Ongoing randomised studies are required for full efficacy and cost-effectiveness evaluations.

Risks associated with antiretroviral treatment for human immunodeficiency virus (HIV): qualitative analysis of social media data and health state utility valuation.

PURPOSE: Despite benefits of antiretroviral therapies (ART), people with HIV infection have increased risk of cardiovascular disease, kidney disease, and low bone mineral density. Some ARTs increase risk of these events. The purpose of this study was to examine patients' perspectives of these risks and estimate health state utilities associated with these risks for use in cost-utility models. METHODS: Qualitative thematic analysis was conducted to examine messages posted to the POZ/AIDSmeds Internet community forums, focusing on bone, kidney, and cardiovascular side effects and risks of HIV/AIDS medications. Then, health state vignettes were drafted based on this qualitative analysis, literature review, and clinician interviews. The health states (representing HIV, plus treatment-related risks) were valued in time trade-off interviews with general population participants in the UK. RESULTS: Qualitative analysis of the Internet forums documented patient concerns about ART risks, as well as treatment decisions made because of these risks. A total of 208 participants completed utility interviews (51.4% female; mean age 44.6 years). The mean utility of the HIV health state (virologically suppressed, treated with ART) was 0.86. Adding a description of risk resulted in statistically significant disutility (i.e., utility decreases): renal risk (disutility = -0.02), bone risk (-0.03), and myocardial infarction risk (-0.05). CONCLUSIONS: Patient concerns and treatment decisions were documented via qualitative analysis of Internet forum discussions, and the impact of these concerns was quantified in terms of health state utilities. The resulting disutilities may be useful for differentiating among ARTs in economic modeling of treatment for patients with HIV.

Assessing analgesic use in patients with advanced cancer: development of a new scale--the Analgesic Quantification Algorithm.

OBJECTIVE: Many patients with advanced cancer frequently use analgesic medications for their pain. Systematically assessing and quantifying changes in analgesic use remains challenging in the clinical trials setting. Currently, there is no sensitive scale for categorizing the intensity of analgesic medications to understand the reasons for changes in patient-reported pain. We assessed whether the Analgesic Quantification Algorithm (AQA) is more sensitive than the World Health Organization Analgesic Treatment Ladder (WHO-AL) for quantifying analgesic medication use among patients with advanced cancer. METHODS: An expanded equianalgesic potency conversion table was developed to establish oral morphine equivalents for use in the AQA. Categories of opioid use were selected to increase sensitivity within the higher dose range of opioids and to better capture increases in analgesic dose intensity. The resulting 8-point AQA scale corresponds to no analgesic use, non-opioid analgesics, weak opioids only, ≤75 mg, >75-150 mg, >150-300 mg, >300-600 mg, and >600 mg oral morphine equivalents per day. Baseline and 6-month analgesic data from a clinical trial of cancer patients were compared for each instrument. RESULTS: At both time points, the 4-point WHO-AL demonstrated a ceiling effect with a clustering of patients in the strong opioid category, whereas the AQA resulted in a distribution of scores throughout the eight categories, including the five strong opioid categories. CONCLUSIONS: The AQA represents a more sensitive measure of analgesic use than the WHO-AL, and may better determine whether changes in pain assessments in clinical trials are due to the intervention or changes in analgesic use.

Health State Utilities Associated with False-Positive Cancer Screening Results.

INTRODUCTION: Early cancer detection can significantly improve patient outcomes and reduce mortality rates. Novel cancer screening approaches, including multi-cancer early detection tests, have been developed. Cost-utility analyses will be needed to examine their value, and these models require health state utilities. The purpose of this study was to estimate the disutility (i.e., decrease in health state utility) associated with false-positive cancer screening results. METHODS: In composite time trade-off interviews using a 1-year time horizon, UK general population participants valued 10 health state vignettes describing cancer screening with true-negative or false-positive results. Each false-positive vignette described a common diagnostic pathway following a false-positive result suggesting lung, colorectal, breast, or pancreatic cancer. Every pathway ended with a negative result (no cancer detected). The disutility of each false positive was calculated as the difference between the true-negative and each false-positive health state, and because of the 1-year time horizon, each disutility can be interpreted as a quality-adjusted life-year decrement associated with each type of false-positive experience. RESULTS: A total of 203 participants completed interviews (49.8% male; mean age = 42.0 years). The mean (SD) utility for the health state describing a true-negative result was 0.958 (0.065). Utilities for false-positive health states ranged from 0.847 (0.145) to 0.932 (0.059). Disutilities for false positives ranged from - 0.031 to - 0.111 (- 0.041 to - 0.111 for lung cancer; - 0.079 for colorectal cancer; - 0.031 to - 0.067 for breast cancer; - 0.048 to - 0.088 for pancreatic cancer). CONCLUSION: All false-positive results were associated with a disutility. Greater disutility was associated with more invasive follow-up diagnostic procedures, longer duration of uncertainty regarding the eventual diagnosis, and perceived severity of the suspected cancer type. Utility values estimated in this study would be useful for economic modeling examining the value of cancer screening procedures.

Out-of-pocket cost by cancer stage at diagnosis in commercially insured patients in the United States.

AIMS: Out-of-pocket (OOP) costs may constitute a substantial financial burden to patients diagnosed with cancer. Earlier stage diagnosis and treatment of cancers may promote decreased morbidity and mortality, subsequently also lowering costs. To better understand costs experienced by patients with cancer, OOP costs by stage post-diagnosis were estimated. MATERIALS AND METHODS: A retrospective analysis was conducted using Optum's de-identified Integrated Claims-Clinical dataset with Enriched Oncology, which includes data from commercially insured members (June 1, 2015-July 31, 2020). Mean annual and cumulative OOP costs (co-pay + co-insurance + deductible) (2020 USD) were reported through a 3-year period post-cancer diagnosis among adult commercially insured members (not including Medicare Advantage members) diagnosed with staged breast, cervical, colorectal, lung, ovarian, or prostate cancer between January 1, 2016 and June 30, 2020 with continuous enrollment for ≥1-month post-diagnosis. RESULTS: A total of 7,494 eligible members were identified who were diagnosed with breast, cervical, colorectal, lung, ovarian, or prostate cancer. A greater proportion of OOP costs were incurred in year 1 post-diagnosis but remained relatively high through year 3 post-diagnosis. Cumulative mean OOP costs were as high as $35,243 (lung stage IV) per commercially insured patient by year 3 post-diagnosis and were generally higher among those diagnosed at later stages (III/IV) than those diagnosed at earlier stages (I/II) across all cancers. LIMITATIONS: Generalizability of these results is limited to those with commercial health insurance coverage. Additionally, cancer staging was dependent on accuracy of staging as recorded in the electronic medical record and as determined by Optum's proprietary algorithm using natural language processing. CONCLUSION: Cumulative mean OOP costs among commercially insured patients during the 3-year period post-cancer diagnosis were substantial and generally higher among those with later stage cancer diagnoses. Diagnosis of cancer at earlier stages may allow for more timely treatment and lessen patient OOP costs.

Patients diagnosed with cancer may face significant out-of-pocket costs (expenses that are not reimbursed by insurance) for care. However, lower costs may be achieved if the cancer is identified, diagnosed, and treated at earlier stages before the cancer tumor can grow or spread to other parts of the body. In this study, we examined patient out-of-pocket costs on an annual basis and over a 3-year period by cancer stage (I­IV) at diagnosis. Data were obtained from a large healthcare database (Optum's Claims-Clinical dataset with Enriched Oncology) that has administrative claims with out-of-pocket cost records as well as health records to determine cancer type and stage at diagnosis. Out-of-pocket costs recorded in the database included the co-pay, co-insurance, and deductible. Data from 7,494 adult patients with commercial insurance (not including Medicare Advantage) who were newly diagnosed with breast, cervical, colorectal, lung, ovarian, or prostate cancer between January 1, 2016 and June 30, 2020 were identified and analyzed. Patients incurred most of their out-of-pocket costs during the first year after a cancer diagnosis and these costs remained high for an additional 2 years. In general, patients diagnosed with cancer at later stages (III/IV) had a higher 3-year total out-of-pocket cost compared to those diagnosed at earlier stages (I/II) and this reached as high as $35,243 among patients diagnosed with stage IV lung cancer. Diagnosis of cancer at an earlier stage may reduce out-of-pocket costs for patients.

Patient Preferences for Multi-Cancer Early Detection (MCED) Screening Tests.

BACKGROUND: Emerging blood-based multi-cancer early detection (MCED) tests can detect a variety of cancer types across stages with a range of sensitivity, specificity, and ability to predict the origin of the cancer signal. However, little is known about the general US population's preferences for MCED tests. OBJECTIVE: To quantify preferences for MCED tests among US adults aged 50-80 years using a discrete choice experiment (DCE). METHODS: To quantify preferences for attributes of blood-based MCED tests, an online DCE was conducted with five attributes (true positives, false negatives, false positives, likelihood of the cancer type unknown, number of cancer types detected), among the US population aged 50-80 years recruited via online panels and social media. Data were analyzed using latent class multinomial logit models and relative attribute importance was obtained. RESULTS: Participants (N = 1700) were 54% female, mean age 63.3 years. Latent class modeling identified three classes with distinct preferences for MCED tests. The rank order of attribute importance based on relative attribute importance varied by latent class, but across all latent classes, participants preferred higher accuracy (fewer false negatives and false positives, more true positives) and screenings that detected more cancer types and had a lower likelihood of cancer type unknown. Overall, 72% of participants preferred to receive an MCED test in addition to currently recommended cancer screenings. CONCLUSIONS: While there is significant heterogeneity in cancer screening preferences, the majority of participants preferred MCED screening and the accuracy of these tests is important. While the majority of participants preferred adding an MCED test to complement current cancer screenings, the latent class analyses identified a small (16%) and specific subset of individuals who value attributes differently, with particular concern regarding false-negative and false-positive test results, who are significantly less likely to opt-in.

Patient-reported outcome instruments used to assess pain and functioning in studies of bisphosphonate treatment for bone metastases.

PURPOSE: When treating metastatic bone disease, relief of bone pain is often a key outcome. Because pain cannot be quantified with objective clinical measures, patient-reported outcome (PRO) measures are required to assess patients' subjective experience. The goal of the current review was to examine measures used to assess pain, as well as the impact of pain on functional status and health-related quality of life (HRQL), in trials of bisphosphonates for the treatment of bone metastases. METHODS: A literature search focused on articles published from January 1999 to April 2009. RESULTS: A total of 49 articles were located that used PROs to assess pain-related outcomes of bisphosphonate treatment for bone metastases. The Brief Pain Inventory was the most commonly used multi-item instrument. However, the most common approach for assessing pain was to administer a single-item scale such as a visual analog scale, numerical rating scale, or verbal rating scale. Of the 49 studies, 19 included a PRO assessing functional status or HRQL. CONCLUSIONS: Although pain is an important outcome of trials examining treatment for bone metastases, the current review suggests that there is little consistency in PRO measurement across studies. Furthermore, presentation of measures often lacked clear description, information on measurement properties, citations, clarity regarding method of administration, and consistent instrument names. Recommendations are provided for instrument validation within the target population, assessment of content validity, use of PRO instruments recently developed for patients with bone metastases, clear description of instruments, and implementation of measures consistent with recommendations from instrument developers.

Breast, Colorectal, Lung, Prostate, and Cervical Cancer Screening Prevalence in a Large Commercial and Medicare Advantage Plan, 2008-2020.

This study aimed to comprehensively assess breast, colorectal, cervical, lung, and prostate cancer screening rates and trends in the United States over time among individuals for whom screening is recommended by the United States Preventive Services Task Force (USPSTF). This retrospective study was conducted in two-year intervals from January 1, 2008 to February 29, 2020, using Optum's de-identified Clinformatics® Data Mart Database, which includes Medicare Advantage and commercially insured members. Screening-eligible individuals, who had not previously had the cancer being screened and met USPSTF criteria for screening, were identified at various time points within the study timeframe for relevant screening tests within five cancer types: breast, colorectal, cervical, lung, and prostate. In the 2020 analysis period, patients who were eligible for cancer screening included: breast: 1,620,588; colorectal: 2,763,736; cervical: 1,371,506; lung: 1,491,594; prostate: 1,126,249. Breast and cervical cancer screening prevalence rates were highest (64.4% and 63.8%, respectively), followed by colorectal (29.5%), prostate (11.7%), and lung (3.8%). Black/African American individuals and Hispanics had moderately low screening rates for cervical (58.6%) and breast (61.8%) cancer, respectively; Hispanics had the lowest screening rates for prostate cancer (6.1%). Those residing in the West had lower screening rates for breast (58.9%), cervical (62.1%), and prostate (5.6%) cancer. Screening rates remained stable over time for breast, colorectal, and lung cancer, and changed significantly for cervical (-9.5%, 2012-2020) and prostate (+7.3%, 2008-2020) cancer. Real-world cancer screening rates remain suboptimal and low, and efforts to increase screening uptake and reduce cancer health disparities remain critical.

Cost of cancer management by stage at diagnosis among Medicare beneficiaries.

OBJECTIVE: Estimate the annual cost of care in the 5 years following a cancer diagnosis for 17 invasive cancer types, by stage at diagnosis. METHODS: We used 2012-2016 data from the Surveillance, Epidemiology, and End Results (SEER) registry-Medicare claims database to examine cost of care among Medicare beneficiaries with a confirmed cancer diagnosis based on International Classification of Diseases for Oncology, Third Edition histology codes reported in SEER. Beneficiaries contributed to the annual cost calculations (Years 1-5) using their observed time after diagnosis. Beneficiaries were continuously enrolled in fee-for-service Medicare Parts A/B and Part D during follow-up. Total, inpatient, outpatient, and pharmacy cancer-related service costs were calculated. RESULTS: From 2012 to 2016, we identified 597,778 Medicare beneficiaries with incident cancer diagnosis within 5 years (Stage I, II, III, and IV: 32.6%, 33.4%, 15.9%, and 18.0%, respectively). In Year 1, mean (standard deviation) total costs for Stage I diagnoses varied from $7640 ($17,378) (prostate) to $94,636 ($117,636) (pancreas). Total costs increased by stage and reached $58,783 ($92,344) (prostate) to $156,982 ($175,009) (stomach) for Stage IV diagnoses in Year 1. Costs in Year 1 were significantly higher for Stage IV diagnoses than for earlier stages across all cancer types. In Years 2-5, total costs were lower than in Year 1 but continued to increase by stage. CONCLUSIONS: Beneficiaries diagnosed at later stages of cancer have higher costs of care (up to 7 times as much) than those diagnosed at earlier stages. Earlier cancer diagnosis may lead to more efficient treatment and decreased management cost.

Access to Chimeric Antigen Receptor T Cell Therapy for Diffuse Large B Cell Lymphoma.

INTRODUCTION: Geographic access to novel oncology therapies, and the extent to which it may vary by potential sites of care, regions, and population characteristics, is poorly understood. We examined how expanding access to chimeric antigen receptor (CAR) T cell therapy administration sites impacts patient travel distances and time. METHODS: We used geographic information system techniques to calculate shortest travel distance and time between patients with relapsed/refractory diffuse large B cell lymphoma (DLBCL) and the nearest CAR T cell therapy administration site in three scenarios: academic hospitals; academic and community multispecialty hospitals; and academic and community multispecialty hospitals plus nonacademic specialty oncology network centers. Main outcome measures were differences in travel distance and time among the scenarios and the relationship between travel time and socioeconomic status, race, rural-urban areas, and non-Hodgkin lymphoma clusters. Non-Hodgkin lymphoma incidence, socioeconomic status, and administration centers were derived from governmental/publicly available data sources. RESULTS: Of 3922 patients eligible for CAR T cell therapy, more than 37% had to travel more than 1 h to the nearest academic hospital. Average travel time and distance were significantly reduced by 23% and 30% (P < 0.001), respectively, when access was expanded to include community hospitals plus a broader range of oncology specialty treatment centers. Compared to academic hospitals alone, increasing access to include community hospitals decreased time and distance by 7% and 8% (P < 0.01), respectively. In addition, there would be a lower proportion of sites operating as the only care provider within 25 miles if access was expanded outside of academic hospitals only. Longer travel time was associated with lower socioeconomic status. CONCLUSION: Many patients with DLBCL have long travel times to an academic hospital that administers CAR T cell therapy. Expanding access to care through site-of-care planning will help address regional, rural-urban, and sociodemographic equity in the geographic allocation of CAR T cell therapy.

Health state utility values by cancer stage: a systematic literature review.

OBJECTIVES: Cancer diagnoses at later stages are associated with a decrease in health-related quality of life (HRQOL). Health state utility values (HSUVs) reflect preference-based HRQOL and can vary based on cancer type, stage, treatment, and disease progression. Detecting and treating cancer at earlier stages may lead to improved HRQOL, which is important for value assessments. We describe published HSUVs by cancer type and stage. METHODS: A systematic review was conducted using Embase, MEDLINE®, EconLit, and gray literature to identify studies published from January 1999 to September 2019 that reported HSUVs by cancer type and stage. Disutility values were calculated from differences in reported HSUVs across cancer stages. RESULTS: From 13,872 publications, 27 were eligible for evidence synthesis. The most frequent cancer types were breast (n = 9), lung (n = 5), colorectal (n = 4), and cervical cancer (n = 3). Mean HSUVs decreased with increased cancer stage, with consistently lower values seen in stage IV or later-stage cancer across studies (e.g., - 0.74, - 0.44, and - 0.51 for breast, colorectal, and cervical cancer, respectively). Disutility values were highest between later-stage (metastatic or stage IV) cancers compared to earlier-stage (localized or stage I-III) cancers. CONCLUSIONS: This study provides a summary of HSUVs across different cancer types and stages that can inform economic evaluations. Despite the large variation in HSUVs overall, a consistent decline in HSUVs can be seen in the later stages, including stage IV. These findings indicate substantial impairment on individuals' quality of life and suggest value in early detection and intervention.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice.

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer "signal") and a cancer signal origin (i.e., tissue of origin). Participants with a "signal detected" will undergo further diagnostic evaluation per guiding physician discretion; those with a "signal not detected" will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a "signal detected" result is expected to be 106 (87-128). Subsequent diagnostic evaluation is expected to detect 52 (39-67) cancers. The positive predictive value of the MCED test is expected to be 49% (39-58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

Economic Evaluation of Chimeric Antigen Receptor T-Cell Therapy by Site of Care Among Patients With Relapsed or Refractory Large B-Cell Lymphoma.

Importance: Chimeric antigen receptor (CAR) T-cell therapies are currently administered at a limited number of cancer centers and are primarily delivered in an inpatient setting. However, variations in total costs associated with these therapies remain unknown. Objective: To estimate the economic differences in the administration of CAR T-cell therapy by the site of care and the incidence of key adverse events. Design, Setting, and Participants: A decision-tree model was designed to capture clinical outcomes and associated costs during a predefined period (from lymphodepletion to 30 days after the receipt of CAR T-cell infusion) to account for the potential incidence of acute adverse events and to evaluate variations in total costs for the administration of CAR T-cell therapy by site of care. Cost estimates were from the health care practitioner perspective and were based on data obtained from the literature and publicly available databases, including the Healthcare Cost and Utilization Project National Inpatient Sample, the Medicare Hospital Outpatient Prospective Payment System, the Medicare physician fee schedule, the Centers for Medicare and Medicaid Services Healthcare Common Procedure Coding System, and the IBM Micromedex RED BOOK. The model evaluated an average adult patient with relapsed or refractory large B-cell lymphoma who received CAR T-cell therapy in an academic inpatient hospital or nonacademic specialty oncology network. Intervention: The administration of CAR T-cell therapy. Main Outcomes and Measures: Total cost of the administration of CAR T-cell therapy by site of care. The costs associated with lymphodepletion, acquisition and infusion of CAR T cells, and management of acute adverse events were also examined. Results: The estimated total cost of care associated with the administration of CAR T-cell therapy was $454 611 (95% CI, $452 466-$458 267) in the academic hospital inpatient setting compared with $421 624 (95% CI, $417 204-$422 325) in the nonacademic specialty oncology network setting, for a difference of $32 987. After excluding the CAR T-cell acquisition cost, hospitalization and office visit costs were $53 360 (65.3% of the total cost) in academic inpatient hospitals and $23 526 (48.4% of the total cost) in nonacademic specialty oncology networks. The administration of CAR T-cell therapy in nonacademic specialty oncology networks was associated with a $29 834 (55.9%) decrease in hospitalization and office visit costs and a $3154 (20.1%) decrease in procedure costs. Conclusions and Relevance: The potential availability of CAR T-cell therapies that are associated with a lower incidence of adverse events and are suitable for outpatient administration may reduce the total costs of care by enabling the use of these therapies in nonacademic specialty oncology networks.

The economic burden to payers of patients with diffuse large B-cell lymphoma during the treatment period by line of therapy.

We retrospectively analyzed treatment patterns and healthcare costs among patients diagnosed with diffuse large B-cell lymphoma (DLBCL) during each line of therapy (LOT) using data from the IBM® MarketScan® Commercial and Medicare Supplemental Databases from January 2011 to May 2017. Patients were included if they had a diagnosis of DLBCL, ≥12 months of disease-free continuous enrollment prediagnosis, and ≥1 month of postdiagnosis follow-up. Of 2066 eligible patients receiving first-line treatment, 17% (n = 340) received second-line treatment; of these, 23% (n = 77) received third-line treatment. Mean healthcare expenditures (treatment duration) for first, second, and third LOTs were $111,314 (124.5 days), $88,472 (80.8 days), and $103,365 (70.9 days), respectively. When adjusted to 30-day period costs, first, second, and third LOT healthcare expenditures increased to $26,825, $32,857, and $43,854, respectively. Patients with newly diagnosed and relapsed/refractory DLBCL incur a significant cost burden (for payers), and such costs increase as patients proceed through subsequent LOTs.

Health state utilities associated with treatment options for acute myeloid leukemia (AML).

Aims: Acute myeloid leukemia (AML) treatment typically involves remission induction chemotherapy followed by consolidation chemotherapy. New treatments for AML have recently been introduced, including a chemotherapy formulation called CPX-351, which is administered via less time-intensive IV infusion than the standard "7 + 3" continuous infusion regimen of cytarabine plus an anthracycline. The purpose of this study was to estimate utilities that could be used in economic modeling of AML treatment. Materials and methods: In time trade-off interviews, participants from the UK general population valued 12 health states drafted based on literature and clinician interviews. To identify disutility associated with chemotherapy, two types of induction and four types of consolidation were added to an otherwise identical health state describing AML. The decrease in utility when adding these chemotherapy regimens represents the disutility of each regimen. Five additional health states were valued to estimate utilities associated with other AML treatments. Results: Two hundred participants completed interviews. Mean (SD) utilities were 0.55 (0.31) for pre-treatment AML and 0.66 (0.29) for AML in temporary remission. Adding any chemotherapy significantly decreased utility (p < 0.0001). Induction had a mean disutility of -0.11 with CPX-351 and -0.15 with 7 + 3. Mean disutility for consolidation ranged from -0.03 with outpatient CPX-351 to -0.11 with inpatient 5 + 2. Utilities are also reported for other AML treatments (e.g. transplant, low-intensity chemotherapy). Limitations: One limitation is that the differences in adverse event profiles between the treatment regimens were based on clinician opinion. Future use of CPX-351 in clinical trials or clinical settings will provide additional information on its adverse event profile. Conclusions: While all chemotherapy regimens were associated with disutility, regimens with shorter hospitalization and less time-intensive infusion were generally perceived as preferable. These utilities may be useful in cost-utility models comparing the value of AML treatments.