Evaluating the impact of delayed study startup on accrual in cancer studies.

Background: Drug development in cancer medicine depends on high-quality clinical trials, but these require large investments of time to design, operationalize, and complete; for oncology drugs, this can take 8-10 years. Long timelines are expensive and delay innovative therapies from reaching patients. Delays often arise from study startup, a process that can take 6 months or more. We assessed how study-specific factors affected the study startup duration and the resulting overall success of the study. Method: Data from The University of Kansas Cancer Center (KUCC) were used to analyze studies initiated from 2018 to 2022. Accrual percentage was computed based on the number of enrolled participants and the desired enrollment goal. Accrual success was determined by comparing the percentage of enrollments to predetermined threshold values (50%, 70%, or 90%). Results: Studies that achieve or surpass the 70% activation threshold typically exhibit a median activation time of 140.5 days. In contrast, studies that fall short of the accrual goal tend to have a median activation time of 187 days, demonstrating the shorter median activation times associated with successful studies. Wilcoxon rank-sum test conducted for the study phase (W=13607, p-value=0.001) indicates that late-phase projects took longer to activate compared to early-stage projects. We also conducted the study with 50% and 90% accrual thresholds; our findings remained consistent. Conclusions: Longer activation times are linked to reduced project success, and early-phase studies tend to have higher success than late-phase studies. Therefore, by reducing impediments to the approval process, we can facilitate quicker approvals, increasing the success of studies regardless of phase.

Predictors of cytomegalovirus reactivation after allogeneic hematopoietic cell transplantation: Insights from a real-world experience.

BACKGROUND: We aimed to investigate factors associated with cytomegalovirus (CMV) viremia and CMV disease and its impact on post-transplant outcomes including overall survival (OS) following allogeneic hematopoietic stem cell transplantation (Allo-SCT). METHODS: We conducted a single-center retrospective study including 452 Allo-SCT recipients (matched unrelated donor, MUD 61%; haploidentical, haplo 39%) from 2016 to 2021. Data were analyzed using SPSS v28. Descriptive (chi-square and t-test), Kaplan-Meier and regression analyses were conducted. RESULTS: The median age was 57 years. Sixty-one percent were males and 84.3% were Caucasians. CMV serostatus was positive in 59.1% of recipients. The median follow-up was 24.4 months. CMV viremia and CMV disease were observed in 181 (40%) and 32 (7%) patients, respectively. Among CMV seropositive recipients, 65% developed CMV viremia and 11% were noted to have CMV disease compared to 4% and 1% in seronegative recipients, respectively (p < 0.001). Patients with CMV disease had significantly lower OS than those without CMV disease (median 14.1 months vs. not reached, p = 0.024); however, OS was not associated with CMV viremia (median not reached in both groups, p = 0.640). Letermovir prophylaxis was used in 66% (n = 176/267) of CMV seropositive recipients, but no impact was observed on the incidence of CMV viremia or CMV disease and OS. CONCLUSIONS: CMV disease leads to significantly inferior survival after an allogeneic hematopoietic cell transplantation. Recipient CMV seropositive status was associated with the risk of CMV viremia and CMV disease, and this was not abrogated with the use of Letermovir prophylaxis.

Using Bayesian hierarchical modeling for performance evaluation of clinical trial accrual for a cancer center.

Introduction: Slow patient accrual in cancer clinical trials is always a concern. In 2021, the University of Kansas Comprehensive Cancer Center (KUCC), an NCI-designated comprehensive cancer center, implemented the Curated Cancer Clinical Outcomes Database (C3OD) to perform trial feasibility analyses using real-time electronic medical record data. In this study, we proposed a Bayesian hierarchical model to evaluate annual cancer clinical trial accrual performance. Methods: The Bayesian hierarchical model uses Poisson models to describe the accrual performance of individual cancer clinical trials and a hierarchical component to describe the variation in performance across studies. Additionally, this model evaluates the impacts of the C3OD and the COVID-19 pandemic using posterior probabilities across evaluation years. The performance metric is the ratio of the observed accrual rate to the target accrual rate. Results: Posterior medians of the annual accrual performance at the KUCC from 2018 to 2023 are 0.233, 0.246, 0.197, 0.150, 0.254, and 0.340. The COVID-19 pandemic partly explains the drop in performance in 2020 and 2021. The posterior probability that annual accrual performance is better with C3OD in 2023 than pre-pandemic (2019) is 0.935. Conclusions: This study comprehensively evaluates the annual performance of clinical trial accrual at the KUCC, revealing a negative impact of COVID-19 and an ongoing positive impact of C3OD implementation. Two sensitivity analyses further validate the robustness of our model. Evaluating annual accrual performance across clinical trials is essential for a cancer center. The performance evaluation tools described in this paper are highly recommended for monitoring clinical trial accrual.

DHA, nutrient intake, and maternal characteristics as predictors of pregnancy outcomes in a randomised clinical trial of DHA supplementation.

PURPOSE: To investigate the relationships among docosahexaenoic acid (DHA) intake, nutrient intake, and maternal characteristics on pregnancy outcomes in a phase III randomised clinical trial designed to determine the effect of a DHA dose of 1000 mg/day compared to 200 mg/day on early preterm birth (<34 weeks gestation). METHODS: A secondary aim of the phase III randomised trial was to explore the relationships among pregnancy outcomes (maternal red blood cell phospholipid (RBC-PL) DHA at delivery, preterm birth, gestational age at delivery, labor type, birth anthropometric measures, low birth weight, gestational diabetes, pre-eclampsia, and admission to a neonatal intensive care unit) in participants (n = 1100). We used Bayesian multiple imputation and linear and logistic regression models to conduct an analysis of five general classes of predictor variables collected during the trial: a) DHA intake, b) nutrient intake from food and supplements, c) environmental exposure to tobacco and alcohol, d) maternal demographics, and e) maternal medical history. RESULTS: DHA supplementation lowered the risk of preterm birth and NICU admission, and increased gestation and birth weight as observed in the primary analysis. Higher maternal RBC-PL-DHA at delivery was associated with DHA supplementation and formal education of a bachelor's degree or higher. DHA supplementation and maternal age were associated with a higher risk of gestational diabetes. Total vitamin A intake was associated with longer gestation, while fructose and intake of the long chain omega-6 fatty acid, arachidonic acid, were associated with shorter gestation. Risk of preterm birth was associated with a history of low birth weight, preterm birth, pre-eclampsia, and NICU admission. CONCLUSION: Bayesian models provide a comprehensive approach to relationships among DHA intake, nutrient intake, maternal characteristics, and pregnancy outcomes. We observed previously unreported relationships between gestation duration and fructose, vitamin A, and arachidonic acid that could be the basis for future research. TRIAL REGISTRATION NUMBER AND DATE: ClinicalTrials.gov (NCT02626299); December 10, 2015.

Patient Polypharmacy use Following a Multi-Disciplinary Dementia Care Program in a Memory Clinic: A Retrospective Cohort Study.

Introduction: Dementia increases the risk of polypharmacy. Timely detection and optimal care can stabilize or delay the progression of dementia symptoms, which may in turn reduce polypharmacy. We aimed to evaluate the change in polypharmacy use among memory clinic patients living with dementia who participated in a dementia care program compared to those who did not. We hypothesized that patients in the dementia care program would reduce their use of polypharmacy compared to those who were not in standard care. Methods: We retrospectively analyzed data extracted from electronic medical records from a university memory clinic. Data from a total of 381 patients were included in the study: 107 in the program and 274 matched patients in standard care. We used adjusted odds ratios to assess the association between enrollment in the program and polypharmacy use at follow-up (five or more concurrent medications), controlling for baseline polypharmacy use and stratified polypharmacy use by prescription and over-the-counter (OTC). Results: The two groups did not differ in the use of five or more overall and prescription medications at follow-up, controlling for the use of five or more of the respective medications at baseline and covariates. Being in the program was associated with a three-fold lower odds of using five or more OTC medications at follow-up (adjusted odds ratio = 0.30; p <0.001; 95% Confidence interval = 0.15-0.58) after controlling for using five or more OTC medications at baseline and covariates. Conclusions: Dementia care may reduce polypharmacy of OTC medications, potentially reducing risky drug-drug interactions. More research is needed to infer causality and understand how to reduce prescription medication polypharmacy.

Rurality Impacts Mammography Screening Adherence Among Mid-life Women in the Kansas Region.

OBJECTIVE: The gold standard for breast cancer screening and prevention is regular mammography; thus, understanding what impacts adherence to this standard is essential in limiting cancer-associated costs. We assessed the impact of various understudied sociodemographic factors of interest on adherence to the receipt of regular mammograms. METHODS: A total Nc = 14,553 mammography-related claims from Nw = 6,336 female Kansas aged between 45 and 54 were utilized from insurance claim databases furnished by multiple providers. Adherence to regular mammography was quantified continuously via a compliance ratio, used to capture the number of eligible years in which at least one mammogram was received, as well as categorically. The relationship between race, ethnicity, rurality, insurance (public/private), screening facility type, and distance to nearest screening facility with both continuous and categorically defined compliance were individually assessed via Kruskal-Wallis one-way ANOVAs, chi-squared tests, multiple linear regression models, and multiple logistic regression, as appropriate. Findings from these individual models were used to inform the construction of a basic, multifaceted prediction model. RESULTS: Model results demonstrated that all factors race and ethnicity had at least some bearing on compliance with screening guidelines among mid-life female Kansans. The strongest signal was observed in the rurality variable, which demonstrated a significant relationship with compliance regardless of how it was defined. CONCLUSION: Understudied factors that are associated with regular mammography adherence, such as rurality and distance to nearest facility, may serve as important considerations when developing intervention strategies for ensuring that female patients stick to prescribed screening regimens.

Evaluating Work Impairment as a Source of Financial Toxicity in Cancer Healthcare and Negative Impacts on Health Status.

How the socioeconomic factors intersect for a particular patient can determine their susceptibility to financial toxicity, what costs they will encounter during treatment, the type and quality of their care, and the potential work impairments they face. The primary goal of this study was to evaluate financial factors leading to worsening health outcomes by the cancer subtype. A logistic model predicting worsening health outcomes while assessing the most influential economic factors was constructed by the University of Michigan Health and Retirement Study. A forward stepwise regression procedure was implemented to identify the social risk factors that impact health status. Stepwise regression was done on data subsets based on the cancer types of lung, breast, prostate, and colon cancer to determine whether significant predictors of worsening health status were different or the same across cancer types. Independent covariate analysis was also conducted to cross-validate our model. On the basis of the model fit statistics, the two-factor model has the best fit, that is, the lowest AIC among potential models of 3270.56, percent concordance of 64.7, and a C-statistics of 0.65. The two-factor model used work impairment and out-of-pocket costs, significantly contributing to worsening health outcomes. Covariate analysis demonstrated that younger patients with cancer experienced more financial burdens leading to worsening health outcomes than elderly patients aged 65 years and above. Work impairment and high out-of-pocket costs were significantly associated with worsening health outcomes among cancer patients. Matching the participants who need the most financial help with appropriate resources is essential to mitigate the financial burden. Significance: Among patients with cancer, work impairment and out-of-pocket are the two primary factors contributing to adverse health outcomes. Women, African American or other races, the Hispanic population, and younger individuals have encountered higher work impairment and out-of-pocket costs due to cancer than their counterparts.

Career disruption and limitation of financial earnings due to cancer.

PURPOSE: This study investigated how cancer diagnosis and treatment lead to career disruption and, consequently, loss of income and depletion of savings. DESIGN: This study followed a qualitative descriptive design that allowed us to understand the characteristics and trends of the participants. METHOD: Patients recruited (n = 20) for this study were part of the University of Kansas Cancer Center patient advocacy research group (Patient and Investigator Voices Organizing Together). The inclusion criteria were that participants must be cancer survivors or co-survivors, be aged 18 years or older, be either employed or a student at the time of cancer diagnosis, have completed their cancer treatment, and be in remission. The responses were transcribed and coded inductively to identify themes. A thematic network was constructed based on those themes, allowing us to explore and describe the intricacies of the various themes and their impacts. RESULTS: Most patients had to quit their jobs or take extended absences from work to handle treatment challenges. Patients employed by the same employer for longer durations had the most flexibility to balance their time between cancer treatment and work. Essential, actionable items suggested by the cancer survivors included disseminating information about coping with financial burdens and ensuring that a nurse and financial navigator were assigned to every cancer patient. CONCLUSIONS: Career disruption is common among cancer patients, and the financial burden due to their career trajectory is irreparable. The financial burden is more prominent in younger cancer patients and creates a cascading effect that financially affects close family members.

Financial burden among cancer patients: A national-level perspective.

BACKGROUND: This research study aimed to evaluate the financial burden among older cancer patients and its corresponding risk factors. Factors such as increasing treatment costs and work limitations often lead cancer patients to bankruptcy and poor quality of life. These consequences, in turn, can cause higher mortality rates among these patients. METHODS: This retrospective cohort study utilized data from the Health Retirement Study (HRS), conducted by the University of Michigan (N = 18,109). Eligible participants had responses captured from years 2002 to 2016. Participants were classified according to any self-reported cancer diagnosis (yes or no) and were compared on the basis of financial, work, and health-related outcomes. Propensity score (PS) matching was applied to reduce the effects of potential confounding factors. Also only, individuals with an age ≥50 and ≤85 during Wave 6 were retained. RESULTS: Multivariate analysis with random effects revealed several indicators of financial burden when comparing participants with a cancer diagnosis to those with no history of cancer. Mean out-of-pocket costs associated with a cancer diagnosis were $1058 higher when compared to participants with no history of cancer, suggesting that even cancer patients with insurance coverage faced out-of-pocket costs. Respondents with cancer patients had higher odds of encountering financial hardship if they are facing Work Limitations (OR = 2.714), Regular use of Medications (OR = 2.518), Hospital Stays (OR = 2.858), Declining Health (OR = 2.349), or were being covered under government health insurance (OR = 5.803) than respondents who did not have cancer, or suffered from mental health issues such as Depression (OR = 0.901). CONCLUSION: Cancer patients contend with increasing financial costs during their treatment. However, most newly diagnosed patients are not aware of these costs and are given few resources to handle them.

A novel Bayesian adaptive design incorporating both primary and secondary endpoints for randomized IIB chemoprevention study of women at increased risk for breast cancer.

BACKGROUND: Our randomized controlled clinical trial will explore the potential of bazedoxifene plus conjugated estrogen to modulate breast tissue-based risk biomarkers as a surrogate for breast cancer risk reduction. This paper investigates the statistical design features of the trial and the rationale for the final choice of its design. Group sequential designs are a popular design approach to allow a trial to stop early for success or futility, potentially saving time and money over a fixed trial design. While Bayesian adaptive designs enjoy the same properties as group sequential designs, they have the added benefit of using prior information as well as inferential interpretation conditional on the data. Whether a frequentist or Bayesian trial, most adaptive designs have interim analyses that allow for early stopping, typically utilizing only the primary endpoint. A drawback to this approach is that the study may not have enough data for adequate comparisons of a single, key secondary endpoint. This can happen, for example, if the secondary endpoint has a smaller effect than the primary endpoint. METHODS: In this paper, we investigate a trial design called two-endpoint adaptive, which stops early only if a criterion is met for primary and secondary endpoints. The approach focuses the final analysis on the primary endpoint but ensures adequate data for the secondary analysis. Our study has two arms with a primary (change in mammographic fibroglandular volume) and secondary endpoint (change in mammary tissue Ki-67). RESULTS: We present operating characteristics including power, trial duration, and type I error rate and discuss the value and risks of modeling Bayesian group sequential designs with primary and secondary endpoints, comparing against alternative designs. The results indicate that the two-endpoint adaptive design has better operating characteristics than competing designs if one is concerned about having adequate information for a key secondary endpoint. DISCUSSION: Our approach balances trial speed and the need for information on the single, key secondary endpoint.

Bolstering the complex study start-up process at NCI cancer centers using technology.

Background: The study startup process for interventional clinical trials is a complex process that involves the efforts of many different teams. Each team is responsible for their startup checklist in which they verify that the necessary tasks are done before a study can move on to the next team. This regulatory process provides quality assurance and is vital for ensuring patient safety [10]. However, without having this startup process centralized and optimized, study approval can take longer than necessary as time is lost when it passes through many different hands. Objective: This manuscript highlights the process and the systems that were developed at The University of Kansas Comprehensive Cancer Center regarding the study startup process. To facilitate this process the regulatory management, site development, cancer center administration, and the Biostatistics & Informatics Shared Resources (BISR) teams came together to build a platform aimed at streamlining the startup process and providing a transparent view of where a study is in the startup process. Process: Ensuring the guidelines are clearly articulated for the review criteria of each of the three review boards, i.e., Disease Working Group (DWG), Executive Resourcing Committee (ERC), and Protocol Review and Monitoring Committee (PRMC) along with a system that can track every step and its history throughout the review process. Results: Well-defined processes and tracking methodologies have allowed the operations teams to track each study closely and ensure the 90-day and 120-day deadlines are met, this allows the operational team to dynamically prioritize their work daily. It also provides Principal investigators a transparent view of where their study stands within the study startup process and allows them to prepare for the next steps accordingly. Conclusion/future work: The current process and technology deployment has been a significant improvement to expedite the review process and minimize study startup delays. There are still a few opportunities to fine-tune the study startup process; an example of which includes automatically informing the operational managers or the study teams to act upon deadlines regarding study review rather than the current manual communication process which involves them looking it up in the system which can add delays.

Rural-Urban Disparities in Health Access Factors Over Time: Implications for Cancer Prevention and Health Equity in the Midwest.

Purpose: Population-level environmental and socioeconomic factors may influence cancer burden within communities, particularly in rural and urban areas that may be differentially impacted by factors related to health care access. Methods: The University of Kansas (KU) Cancer Center serves a geographically large diverse region with 75% of its 123 counties classified as rural. Using County Health Rankings data and joinpoint regression, we examined trends in four factors related to the socioeconomic environment and health care access from 2009 to 2017 in rural and urban counties across the KU Cancer Center catchment area. Findings: The adult health uninsurance rate declined significantly in rural and urban counties across the catchment area (rural annual percent change [APC]=-5.96; 95% CI=[-7.71 to -4.17]; urban APC=-5.72; 95% CI=[-8.03 to -3.35]). Childhood poverty significantly decreased in rural counties over time (APC=-2.94; 95% CI=[-4.52 to -1.33]); in contrast, urban childhood poverty rates did not significantly change before 2012 (APC=3.68; 95% CI=[-15.12 to 26.65]), after which rates declined (APC=-5.89; 95% CI=[-10.01 to -1.58]). The number of primary care providers increased slightly but significantly in both rural and urban counties (APC=0.54; 95% CI=[0.28 to 0.80]), although urban counties had more primary care providers than rural areas (76.1 per 100K population vs. 57.1 per 100K population, respectively; p=0.009). Unemployment declined significantly faster in urban counties (APC=-10.33; 95% CI=[-12.16 to -8.47]) compared with rural counties (APC=-6.71; 95% CI=[-8.22 to -5.18]) (p=0.02). Conclusion: Our findings reveal potential disparities in systemic factors that may contribute to differences in cancer prevention, care, and survivorship in rural and urban regions.

Barriers to Clinical Trial Participation: Comparative Study Between Rural and Urban Participants.

BACKGROUND: The National Clinical Trials Network program conducts phase 2 or phase 3 treatment trials across all National Cancer Institute's designated cancer centers. Participant accrual across these clinical trials is a critical factor in deciding their success. Cancer centers that cater to rural populations, such as The University of Kansas Cancer Center, have an additional responsibility to ensure rural residents have access and are well represented across these studies. OBJECTIVE: There are scant data available regarding the factors that act as barriers to the accrual of rural residents in these clinical trials. This study aims to use electronic screening logs that were used to gather patient data at several participating sites in The Kansas University of Cancer Center's Catchment area. METHODS: Screening log data were used to assess what clinical trial participation barriers are faced by these patients. Additionally, the differences in clinical trial participation barriers were compared between rural and urban participating sites. RESULTS: Analysis revealed that the hospital location rural urban category, defined as whether the hospital was in an urban or rural setting, had a medium effect on enrolment of patients in breast cancer and lung cancer trials (Cohen d=0.7). Additionally, the hospital location category had a medium effect on the proportion of recurrent lung cancer cases at the time of screening (d=0.6). CONCLUSIONS: In consideration of the financially hostile nature of cancer treatment as well as geographical and transportation barriers, clinical trials extended to rural communities are uniquely positioned to alleviate the burden of nonmedical costs in trial participation. However, these options can be far less feasible for patients in rural settings. Since the number of patients with cancer who are eligible for a clinical trial is already limited by the stringent eligibility criteria required of such a complex disease, improving accessibility for rural patients should be a greater focus in health policy.

Evaluation of the Durability of the Immune Humoral Response to COVID-19 Vaccines in Patients With Cancer Undergoing Treatment or Who Received a Stem Cell Transplant.

Importance: The durability of the antibody response to COVID-19 vaccines in patients with cancer undergoing treatment or who received a stem cell transplant is unknown and may be associated with infection outcomes. Objective: To evaluate anti-SARS-CoV-2 spike protein receptor binding domain (anti-RBD) and neutralizing antibody (nAb) responses to COVID-19 vaccines longitudinally over 6 months in patients with cancer undergoing treatment or who received a stem cell transplant (SCT). Design, Setting, and Participants: In this prospective, observational, longitudinal cross-sectional study of 453 patients with cancer undergoing treatment or who received an SCT at the University of Kansas Cancer Center in Kansas City, blood samples were obtained before 433 patients received a messenger RNA (mRNA) vaccine (BNT162b2 or mRNA-1273), after the first dose of the mRNA vaccine, and 1 month, 3 months, and 6 months after the second dose. Blood samples were also obtained 2, 4, and 7 months after 17 patients received the JNJ-78436735 vaccine. For patients receiving a third dose of an mRNA vaccine, blood samples were obtained 30 days after the third dose. Interventions: Blood samples and BNT162b2, mRNA-1273, or JNJ-78436735 vaccines. Main Outcomes and Measures: Geometric mean titers (GMTs) of the anti-RBD; the ratio of GMTs for analysis of demographic, disease, and treatment variables; the percentage of neutralization of anti-RBD antibodies; and the correlation between anti-RBD and nAb responses to the COVID-19 vaccines. Results: This study enrolled 453 patients (mean [SD] age, 60.4 [13,1] years; 253 [56%] were female). Of 450 patients, 273 (61%) received the BNT162b2 vaccine (Pfizer), 160 (36%) received the mRNA-1273 vaccine (Moderna), and 17 (4%) received the JNJ-7846735 vaccine (Johnson & Johnson). The GMTs of the anti-RBD for all patients were 1.70 (95% CI, 1.04-2.85) before vaccination, 18.65 (95% CI, 10.19-34.11) after the first dose, 470.38 (95% CI, 322.07-686.99) at 1 month after the second dose, 425.80 (95% CI, 322.24-562.64) at 3 months after the second dose, 447.23 (95% CI, 258.53-773.66) at 6 months after the second dose, and 9224.85 (95% CI, 2423.92-35107.55) after the third dose. The rate of threshold neutralization (≥30%) was observed in 203 of 252 patients (80%) 1 month after the second dose and in 135 of 166 patients (81%) 3 months after the second dose. Anti-RBD and nAb were highly correlated (Spearman correlation coefficient, 0.93 [0.92-0.94]; P < .001). Three months after the second dose, anti-RBD titers were lower in male vs female patients (ratio of GMTs, 0.52 [95% CI, 0.34-0.81]), patients older than 65 years vs patients 50 years or younger (ratio of GMTs, 0.38 [95% CI, 0.25-0.57]), and patients with hematologic malignant tumors vs solid tumors (ratio of GMTs, 0.40 [95% CI, 0.20-0.81]). Conclusions and Relevance: In this cross-sectional study, after 2 doses of an mRNA vaccine, anti-RBD titers peaked at 1 month and remained stable over the next 6 months. Patients older than 65 years of age, male patients, and patients with a hematologic malignant tumor had low antibody titers. Compared with the primary vaccine course, a 20-fold increase in titers from a third dose suggests a brisk B-cell anamnestic response in patients with cancer.

Accelerating Cancer Patient Recruitment Through a Mobile Application (Clinical Trial Finder).

OBJECTIVE: Participant recruitment is a challenge for any clinical trial but is especially complex in cancer specifically due to the need to initiate treatment urgently. Most participants enrolled in oncology clinical trials are identified as potential participants by the oncologist or other referring provider. Optimal clinical care for patients with cancer includes consideration of participation in a clinical trial. However, the process of finding a clinical trial that is appropriate the patient can be cumbersome and time consuming. MATERIAL AND METHODS: The University of Kansas Cancer Center has developed a mobile application (app) which streamlines the clinical trial search process for physicians, patients, and caregivers by cohesively integrating all clinical trials currently recruiting in the center and making them easy to browse. RESULTS: Key aspects of the app include simple filtering options, the ability to search for trials by name, easily accessible assistance, and in-app referral by phone or email. Initial feedback on the app has been very positive, with several suggestions already being implemented in future development. The app was designed to be used both by physicians to find trials, as well as patients in collaboration with their physicians. CONCLUSION: While long-term results will be crucial to understanding how the app can best serve our patient population, our initial results suggest that health system specific clinical trial apps can address a currently unmet need in the clinical trial recruitment process.

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area.

PURPOSE: The University of Kansas Cancer Center (KU Cancer Center) recently developed a data warehouse to Organize and Prioritize Trends to Inform KU Cancer Center (OPTIK). The OPTIK database aggregates and standardizes data collected across the bistate catchment area served by the KU Cancer Center. To improve the usability of the OPTIK database, we developed shinyOPTIK, a user-friendly, interactive web application for visualizing cancer risk factor and mortality rate data across the KU Cancer Center Catchment area. METHODS: Data in the OPTIK database were first consolidated at the county level across the KU Cancer Center catchment area. Next, the shinyOPTIK development team met with the KU Cancer Center leadership to discuss the needs and priorities of the shinyOPTIK web application. shinyOPTIK was developed under the R Shiny framework and consists of a user interface (ui.R) and a web server (server.R). At present, shinyOPTIK can be used to generate county-level geographical heatmaps; bar plots of demographic, screening, and risk factors; and line plots to visualize temporal trends at different Rural-Urban Continuum Codes (RUCCs), rural-urban status, metropolitan, or county levels across the KU Cancer Center catchment area. RESULTS: Two examples, adult obesity prevalence and lung cancer mortality, are presented to illustrate how researchers can use shinyOPTIK. Each example is accompanied by post hoc visualizations to help explain key observations in terms of rural-urban disparities. CONCLUSION: Although shinyOPTIK was developed to improve understanding of spatial and temporal trends across the population served by the KU Cancer Center, our hope is that the description of the steps involved in the creation of this tool along with open-source code for our application provided herein will serve as a guide for other research centers in the development of similar tools.

The need to study rural cancer outcome disparities at the local level: a retrospective cohort study in Kansas and Missouri.

BACKGROUND: Rural residence is commonly thought to be a risk factor for poor cancer outcomes. However, a number of studies have reported seemingly conflicting information regarding cancer outcome disparities with respect to rural residence, with some suggesting that the disparity is not present and others providing inconsistent evidence that either urban or rural residence is associated with poorer outcomes. We suggest a simple explanation for these seeming contradictions: namely that rural cancer outcome disparities are related to factors that occur differentially at a local level, such as environmental exposures, lack of access to care or screening, and socioeconomic factors, which differ by type of cancer. METHODS: We conducted a retrospective cohort study examining ten cancers treated at the University of Kansas Medical Center from 2011 to 2018, with individuals from either rural or urban residences. We defined urban residences as those in a county with a U.S. Department of Agriculture Urban Influence Code (UIC) of 1 or 2, with all other residences defines a rural. Inverse probability of treatment weighting was used to create a pseudo-sample balanced for covariates deemed likely to affect the outcomes modeled with cumulative link and weighted Cox-proportional hazards models. RESULTS: We found that rural residence is not a simple risk factor but rather appears to play a complex role in cancer outcome disparities. Specifically, rural residence is associated with higher stage at diagnosis and increased survival hazards for colon cancer but decreased risk for lung cancer compared to urban residence. CONCLUSION: Many cancers are affected by unique social and environmental factors that may vary between rural and urban residents, such as access to care, diet, and lifestyle. Our results show that rurality can increase or decrease risk, depending on cancer site, which suggests the need to consider the factors connected to rurality that influence this complex pattern. Thus, we argue that such disparities must be studied at the local level to identify and design appropriate interventions to improve cancer outcomes.

Non-cancer clinical trials start-up metrics at an academic medical center: Implications for advancing research.

The primary goal for any clinical trial after it receives a funding notification is to receive regulatory approval and initiate the trial for recruitment. Every trial must go through documentation and regulatory process before it can start recruiting participants and collecting data; this initial process of review and approval is known as the study start-up process (SSU). We evaluated the average time taken for studies to receive approvals. Using data from clinical trials conducted at the University of Kansas Medical Center, various times to reach the start of the study were calculated based on the dates of individual study. The results of this analysis showed that chart review studies and investigator-initiated trials had a shorter time to activation than other types of studies. Additionally, single-center studies had a shorter activation time than multi-center studies. The analysis also demonstrated that the overall processing time consistently had been reduced over time.

Randomized Phase II Trial of Anthracycline-free and Anthracycline-containing Neoadjuvant Carboplatin Chemotherapy Regimens in Stage I-III Triple-negative Breast Cancer (NeoSTOP).

PURPOSE: Addition of carboplatin (Cb) to anthracycline chemotherapy improves pathologic complete response (pCR), and carboplatin plus taxane regimens also yield encouraging pCR rates in triple-negative breast cancer (TNBC). Aim of the NeoSTOP multisite randomized phase II trial was to assess efficacy of anthracycline-free and anthracycline-containing neoadjuvant carboplatin regimens. PATIENTS AND METHODS: Patients aged ≥18 years with stage I-III TNBC were randomized (1:1) to receive either paclitaxel (P) weekly × 12 plus carboplatin AUC6 every 21 days × 4 followed by doxorubicin/cyclophosphamide (AC) every 14 days × 4 (CbP → AC, arm A), or carboplatin AUC6 + docetaxel (D) every 21 days × 6 (CbD, arm B). Stromal tumor-infiltrating lymphocytes (sTIL) were assessed. Primary endpoint was pCR in breast and axilla. Other endpoints included residual cancer burden (RCB), toxicity, cost, and event-free (EFS) and overall survival (OS). RESULTS: One hundred patients were randomized; arm A (n = 48) or arm B (n = 52). pCR was 54% [95% confidence interval (CI), 40%-69%] in arm A and 54% (95% CI, 40%-68%) in arm B. RCB 0+I rate was 67% in both arms. Median sTIL density was numerically higher in those with pCR compared with those with residual disease (20% vs. 5%; P = 0.25). At median follow-up of 38 months, EFS and OS were similar in the two arms. Grade 3/4 adverse events were more common in arm A compared with arm B, with the most notable differences in neutropenia (60% vs. 8%; P < 0.001) and febrile neutropenia (19% vs. 0%; P < 0.001). There was one treatment-related death (arm A) due to acute leukemia. Mean treatment cost was lower for arm B compared with arm A (P = 0.02). CONCLUSIONS: The two-drug CbD regimen yielded pCR, RCB 0+I, and survival rates similar to the four-drug regimen of CbP → AC, but with a more favorable toxicity profile and lower treatment-associated cost.