bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of the predictive power of survival of the Royal Marsden Score (RMS), the Gustave Rousy Immunescore (GRIM score), the MDACC score (MDAS) and the LIPI score in phase I trials patients.
Authors: Castanon Alvarez Eduardo , Resano Leyre , Barba Luis , Vidal Covadonga , Sanchez Arraez Alvaro , Gonzalez Martin Antonio , Ponz-Sarvisé Mariano 
Published: May 2020

e14094 Background: Selection of patients for enrolment in phase I trials is critical. Initial scores (RMS or MDAS) were designed to select patients with higher probability to obtain benefit in a clinical trial, followed by others such as GRIM score and the LIPI score. In this study, we have performed a comparison of the four scores in order to detect the most optimal one to select patients for immunotherapy phase I trials. Methods: We retrospectively studied 248 patients who participated in immunotherapy phase I trials in our institution from 2012-2019. We calculated high or low risk for each patient according to punctuation in RMS (number of metastasis,LDH, albumin), GRIM score (LDH, Albumin, NLR > 6), MDAS (RMS, ECOG > = 1, gastrointestinal tumors) and LIPI score (LDH, NLR > 3) at the time of screening. Overall survival (OS) was defined as the time between first dose and date of death or lost to follow up. Cox regression model was performed for predicting OS. C-Harrell index and its confidence interval were calculated for each score for measuring the power of prediction. Differences between c-Harrell indexes were calculated. All calculations were performed with STATA v16.0. Results: In terms of predicting overall survival we found that a higher punctuation in RMS (high vs low HR = 2.14 95% CI 1.47-3.10), Grim score (high vs low HR = 2.14; 95% CI1.51-3.02), MDAS (HR = 1.17 95% CI 1.04-1.31) and LIPI score (high vs low HR = 1.83; 95% CI 1.42-2.37) were all statistically significant. In terms of power of prediction, we found that LIPI score presented a c-Harrel index slightly higher (0.63; 95% CI 0.59-0.68) than GRIM score (0.62; 95% CI 0.57-0.66), MDACC score (0.55 95% CI 0.50-0.62) and RMS (0.62; 95% CI 0.59-0.66). Differences between c-index of each score were not statistically significant. In terms of predicting survival at 90 days, differences between ROC areas for LIPI score (0.64 95% CI 0.56-0.72), Grim Score (0.69 95% CI 0.61-0.76), MDAS (0.57 95% CI 0.48-0.66), and RMS (0.68 95% CI 0.62-0.73) were not statistically significant. Conclusions: Although in this study we have seen a slightly higher predictive power for LIPI score in comparison to GRIM score, MDAS or RMS, differences were not statistically significant. Nevertheless, and assuming the most parsimonious model, LIPI score seemed to be an easy and accurate model for predicting survival. These results might suggest that further prospective analysis are needed to avoid excluding patients based on these scores and who may benefit from phase I trials.
HIV status and history of prior malignancy in immunotherapy trials.
Authors: Xie John , Deshotels Leigh , Chaaya Gerard , Komiya Takefumi 
Published: May 2020

e14096 Background: Patients with human immunodeficiency virus (HIV) and history of prior malignancy have been historically excluded from clinical trials. In late 2017, ASCO and Friends of Cancer Research proposed to include patients with HIV and history of prior malignancy for which treatment has been completed for at least 2 years. We aimed to determine if these recommendations were followed. Methods: Using clinicaltrials.gov, we performed a systematic review of immunotherapy trials involving pembrolizumab, nivolumab, avelumab, atezolizumab, and durvalumab. We included all solid tumor trials in patients aged 18 years and older performed between January 1, 2016 and December 31, 2019. The following data were recorded for each trial: study period (2016-17 vs. 2018-19), drug type (pembrolizumab vs other), inclusion of HIV positive population (yes or no), and inclusion of prior malignancy per guidelines (yes or no). A Chi-square analysis was performed on the two study periods in relation to HIV status and history of prior malignancy. The same analysis was also performed on HIV status/ history of prior malignancy in relation to the drug type. Significance was set at p-value < 0.05. Results: A total of 305 studies reached final analysis, of which 123 involved pembrolizumab. For all drugs combined, there was no significant change in the two study periods in the inclusion of HIV patients (p = 0.48) or history of prior malignancy (p = 0.68). A subanalysis of the pembrolizumab trials showed a statistically significant inclusion of history of prior malignancy compared to other drugs in the entire study period of 2016-2019 (p = 0.03), but this did not hold true for HIV status (p = 0.69). Conclusions: Our study suggests that recent recommendations by ASCO and Friends of Cancer Research regarding HIV status and history of prior malignancy are not being followed. This could be due to limited awareness surrounding the recommendations or continued fears regarding treatment-related adverse events in this subset of patients. [Table: see text]
The role of an open-label non-intervention design versus a placebo-control arm in oncology randomized trials.
Authors: Kushnir Igal , Clemons Mark J. , Fergusson Dean , Bosse Dominick , Reaume M. Neil 
Published: May 2020

e14099 Background: Randomized trials are considered the gold standard when assessing the efficacy of new therapeutic agents. In settings where there is no known effective agent available, a randomised study could compare the investigational agent with either a placebo arm or an open-label non-intervention arm (i.e. best supportive care). The use of placebo arm can result in additional inconvenience and time commitments for patients, as well as increased administrative and regulatory costs. We conducted a survey among Canadian medical oncologists to assess whether an open-label non-intervention arm would be an acceptable alternative control to placebo in randomized trials. Methods: Members of the Canadian Association of Medical Oncologists were invited to participate in an anonymous online survey. Standardized case scenarios were used to determine participants’ attitudes regarding the role of open-label randomized-controlled trials instead of a placebo. Results: Eighty-six medical oncologists and trainees responded (response rate was 27%). Eighty-one (94%) of respondents worked at university-affiliated centres and 41 (48%) had been in practice for at least 10 years. Fifty-one (59%) respondents believed that it is acceptable to use an open-label design instead of a placebo arm when assessing a therapeutic agent in the adjuvant setting. Thirty-eight (49%) felt it was acceptable to compare the investigational agent to an open-label arm instead of a placebo to assess overall survival in the metastatic setting. Twenty-eight (38%) of respondents felt using an open-label design when assessing quality of life endpoints was acceptable. Most physicians (75%) were unsure whether or not the US Food and Drug Administration requires a placebo-controlled arm in cancer clinical trials. Conclusions: We report disagreement and uncertainty among Canadian medical oncologists regarding the acceptability of an open-label design in randomized-controlled trials where no standard therapy is approved. Clearer guidance from regulatory bodies on the adequacy of different trial designs could help reduce this equipoise.
Impact of organ function based standard exclusion criteria in diffuse large b-cell lymphoma (DLBCL) patients: Who gets left behind?
Authors: Khurana Arushi , Mwangi Raphael , Nowakowski Grzegorz S. , Habermann Thomas Matthew , Ansell Stephen M. , LaPlant Betsy , Link Brian K. , Cerhan James Robert , Maurer Matthew J. , Witzig Thomas E. 
Published: May 2020

e14100 Background: Only 3-5% of adult cancer patients in the US enroll in clinical trials. Patients with organ dysfunction are often excluded from clinical trials, regardless of specific drug metabolism or relative function of the organ. The ASCO and the US FDA recommend modernizing criteria related to baseline organ function and comorbidities. In hematological malignancies, often the disease itself is the reason for organ function derangement. In order to better inform clinical trial eligibility and improve participation in the future, we evaluated the impact of baseline organ function on the potential eligibility for clinical trial enrollment for real world patients with newly diagnosed DLBCL. Methods: Consecutive, newly diagnosed lymphoma patients were offered enrollment from 2002-2015 into the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence. This analysis is based on 1270 DLBCL patients receiving immunochemotherapy. Baseline organ function parameters were identified from the exclusion criteria for hemoglobin, absolute neutrophil count (ANC), platelet count, creatinine, and bilirubin reported in recent frontline trials in DLBCL (Table). Abstracted clinical labs from the MER were used to determine the percent of patients that would be excluded based on the criteria. Results: We determined that 11-23% of MER DLBCL patients receiving standard of care frontline therapy would have been excluded in the various trials utilizing baseline organ function alone (Table). Hemoglobin and renal function had the greatest impact on exclusion. Conclusions: Current national and international (phase II and III) trials are excluding up to 23% of patients from clinical trial participation based on organ function alone in DLBCL. These data will be useful in future clinical trial development to meet ASCO recommendations to increase trial accrual, while balancing the drug toxicities and patient safety. An online tool was developed based on these results to aid future trial development. [Table: see text]
Interventional multicenter study to assess the feasibility of an e-health system (ZEMY) designed to manage symptoms and treatment-related toxicities in patients with breast cancer.
Authors: Teixeira Luis , Levy Christelle , Coeffic David , Ghorbal Rim , Dupin Julien , Esposito Nazario , Derbel Olfa 
Published: May 2020

e14107 Background: There is increasing interest in using e-health systems for symptom monitoring and alert triggering. ZEMY, a new software medical device, was developed to improve symptom management and enhance patient and health care team interactions. Methods: This was a three-month open-label, interventional, single arm study conducted at five French sites. Adult women with breast cancer (BC) initiating oral and/or parenteral cancer treatment received a smartphone with ZEMY installed and verbal training. Patients started cancer treatment on Day 1 and were followed for three months. Patients entered data for ten prespecified symptoms. The ZEMY software made recommendations to patients on the self-management of symptoms and transmitted automatic messages to the health care team. Primary outcome was patient feasibility response at 3 months (completion of ≥3 symptom reports and a report completion rate of ≥60% per patient). Secondary objectives included ZEMY symptom management, usability and satisfaction, and device deficiencies (DDs). Results: Overall, 54 patients were enrolled (Jun 2018 to Jan 2019) and 52 (96.3%) completed the study. Thirty-one (57.4%) patients were responders; this was not significantly higher than the predefined cut-off and ZEMY feasibility was not demonstrated. Forty-seven (87.0%) patients had ≥3 completed symptom reports and 33 (66.0%) patients had a report completion rate of ≥60% (missing: n = 4). In subgroup analyses, 22/30 (73.3%) patients with locally advanced BC and 24/36 (66.7%) patients aged 40–60 years were responders. ZEMY patient recommendations and health care team automatic messages were considered relevant at least once in > 74% of cases for five of the six symptoms that were reported at least once by more than 1/3 of patients (diarrhea, nausea, fatigue, cutaneous and mucosal toxicities, and anxiety/depression). Using a 0–10 visual analogue scale, mean ZEMY satisfaction score was higher for patients than investigators (6.3 ±2.9 vs 4.4 ±1.5). Overall, 95 DDs were reported in 37 (68.5%) patients. Main reasons for DDs were inappropriate recommendations (n = 51) and device malfunction (n = 36). Conclusions: The primary endpoint of the study was not reached; however, higher response rates were observed in subgroups versus the overall population, indicating that ZEMY may be useful in symptom management in these patients. Generally, patients had a favorable opinion of ZEMY. The DD rate observed indicates the need for better user support in the future. Clinical trial information: NCT03558490.
Provider preferences for attributes of artificial intelligence in breast cancer screening: A discrete choice experiment.
Authors: Hendrix Nathaniel , Hauber A. Brett , Lee Christoph I. , Bansal Aasthaa , Veenstra David Leroy 
Published: May 2020

e14118 Background: One of the emerging medical applications of artificial intelligence (AI) is the interpretation of mammograms for breast cancer screening. It is uncertain what attributes would result in acceptance of AI for breast cancer screening (AI BCS) among ordering clinicians. Methods: We performed qualitative interviews to identify the most important attributes of AI BCS for ordering clinicians. We then invited US-based primary care providers (PCPs) to participate in a discrete choice experiment (DCE). The experiment featured 15 choices between radiologist alone and two AI BCS alternatives where respondents traded better metrics on some attributes for worse metrics on others. Responses were analyzed using a mixed logit model adjusting for preference heterogeneity to determine the probability of recommending AI BCS. Results: In qualitative interviews, the six most important attributes to PCPs were AI sensitivity, specificity, radiologist involvement, understandability of AI decision-making, supporting evidence, and diversity of training data. Forty PCPs completed the DCE. Sensitivity was the most important attribute: a 4 percentage point improvement in sensitivity over the average radiologist increased the probability of recommending AI by 0.41 (95% confidence interval (CI), 0.38-0.42). Specificity was approximately half as important. Respondents were indifferent to whether radiologists confirmed all or only screens likely to be abnormal. However, no radiologist involvement reduced the probability of recommendation by 0.31 (95% CI, 0.29-0.31). An AI developed using data from diverse populations increased the probability of recommendation by 0.38 (95% CI, 0.36-0.39). Lastly, an AI that is transparent in the rationale for its decisions increased the probability of recommendation by 0.41 (95% CI, 0.39-0.41). Conclusions: PCPs prefer AI BCS that improves sensitivity versus specificity, and involves radiologists in the confirmation of abnormal screens. Improving sensitivity alone, however, will likely not be sufficient to support widespread PCP acceptance – algorithms will need to be developed with diverse data and more transparent explanations of their decisions.
Role of real-world evidence for oncology product registration in the United States: A review of approvals by the U.S. Food and Drug Administration from 2015 to 2019.
Authors: Arondekar Bhakti , Bhak Rachel , DerSarkissian Maral , Huynh Lynn , Wang Kelsey , Davis Eric , Wornson Bryon , Duh Mei Sheng 
Published: May 2020

e14130 Background: There are few concrete examples of real world evidence (RWE) used to support clinical development in regulatory filings despite growing interest in this field. This study systematically reviewed FDA oncology approvals to identify use cases of RWE. Methods: FDA’s new drug application (NDA) and biologics license application (BLA) approvals for oncology products from 2015-2019 were systematically reviewed. Among cases with RWE, data characterizing the submission and RWE details (data source, study design, FDA comments) were synthesized. Results: 93 approved NDAs and BLAs were identified; 6 included RWE in support of efficacy (see Table), approved on or after 2017, and were largely retrospective studies that contextualized results to pivotal trial, with primary endpoints overall survival (OS), overall response rate (ORR), and time to treatment discontinuation (TTD). Flatiron data were used in 3 of these as database analyses, 1 was an expanded access program (EAP), 1 was a meta-analysis, and 1 was a retrospective chart review. Conclusions: In the past 5 years, few FDA decisions incorporated RWE in oncology drug approvals. When used, RWE has been a complement rather than a supplement for clinical trial data. Early engagement, a priori protocol development, and robust research design (adjusting for bias, comparability to clinical trial population) remain key determinants for successful use of RWE in FDA decision making. [Table: see text]
Optimization of screening tools in patients eligible to receive immune-checkpoint inhibitors.
Authors: Ostios-Garcia Lorena , Higuera Oliver , Martinez-Fdez Sara , Pinto Alvaro , Espinosa Enrique , Castelo Beatriz , Cruz Patricia , Yubero Paloma , Feliu Batlle Jaime 
Published: May 2020

e14139 Background: The management of immune-related adverse events (irAEs) produced by immune-checkpoint inhibitors can be challenging, considering differences with the toxicity of classical chemotherapy. In this study, we explored the limitations in the preventions and diagnosis of irAEs at our institution and developed a strategic plan to solve them according to guidelines of the European Society for Medical Oncology and the American Society of Clinical Oncology. Methods: This is a two-phase, single center, exploratory study. In the first phase, we analyzed a random sample of 20 patients (pts) treated with nivolumab or pembrolizumab in the years 2017-2018. A Pareto chart was designed to identify issues in the baseline screening, as well as potential ways to improve the management of irAEs. After that, we implemented corrective measures based on educational lectures, early identification of patients eligible for immunotherapy, standardized protocols, and a profile of screening tests in the electronic medical records. We applied the new strategy on 15 pts treated from January-April 2019. To compare the impact of the implemented measures we used a run chart, frequencies/percentages for categorical variables, and medians/ranges for continuous variables. Adverse events were assessed according to CTCAEv5.0. Results: In the first phase, 38% of the required tests were done before the start of immunotherapy. We identified a deficit in the evaluation of cardiac and pulmonary function, chronic infections, and skin disorders. 45% of pts had some irAEs (15% G1, 15% G2 and 15% G3). Due to toxicity, 33% of pts had delays in the administration of treatment, and 11% required early interruption. After applying corrective measures, 81% of tests were requested before treatment initiation. However, screening for tuberculosis infection and echocardiogram continued to be deficient. We identified irAEs in 53% of pts (16% G1, 50% G2 and 25% G3), and 37% of them presented two or more different irAEs during the period of treatment. 37,5% and 12,5% of pts had delays or early interruption of immunotherapy, respectively. All of pts with irAEs had presented any basal alterations in screening tests. The most frequent basal alterations were found in pancreatic (66%) and thyroid activity (50%). Conclusions: Simple improvement strategies such as education programs, standardized protocols, and an electronic profile can improve the basal screening for potential irAEs. The basal alterations found in some pts can be related to the development of side effects or interactions with the immunotherapy.
A template for generic asssessment of tumor response: "myRECIST".
Authors: Raskin Stephen , Kharizman Tehila , Rachutin Zalogin Tatyana , Ackerstein Aliza , Konen Eli , Berger Raanan , Amitai Michal 
Published: May 2020

e14149 Background: Oncologists often need an objective, quantitative assessment of a patient's response to therapy. Lacking a standardized format, the oncologist may request a RECIST (Response Evaluation Criteria in Solid Tumors) analysis. RECIST, however, was developed to provide standardized assessment in the context of randomized clinical trials. RECIST is based on the prospective analysis of a limited sample of tumor lesions or lymph nodes, whereas the clinician naturally makes clinical decisions retrospectively. Furthermore, RECIST has definitions, rules, and criteria for classifying responses that may not apply in the clinical setting, and it does not include consistent rules for merging or splitting lymph nodes, mixed tumor responses, lesions that may cavitate, and a wide range of individualistic responses encountered in clinical practice. Methods: To address these issues, we have modified our working Excel-based template for RECIST 1.1 assessment to include a "myRECIST" feature, so that the radiologist can enter data and examine a range of pre-defined or customizable scenarios, including RECIST1.1, iRECIST, Lugano, volumetric and other parametric protocols. With a few interactions, this template can produce exportable tables and graphs of tumor responses that can guide therapy, as shown in the attached image. Definitions are standardized and linked to RADLEX ontology for specificity and subsequent analysis. Results: This template has been developed for clinical use and is available for downloading from our institutional web-site. Conclusions: We have developed, for public use, a free, easy-to-use, down-loadable Excel template for evaluating prospective or retrospective scenarios of tumor response to therapy that avoids the restrictions of the RECIST methodology. This template may prove useful to oncologists both in and out of the context of randomized clinical trials. We call this "myRECIST."
The impact of telemedicine on patient-reported outcomes in urologic oncology.
Authors: Gadzinski Adam John , Abarro Isabelle O. , Stewart Blair , Gore John L. 
Published: May 2020

e14154 Background: Nearly 20% of Americans live in rural communities. These individuals face barriers to accessing cancer care, including prevalent poverty and substantial travel burden to seeing cancer providers. We aimed to assess the impact of a rurally focused telemedicine program on patient outcomes in our urologic oncology outpatient clinic. Methods: We prospectively identified patients from rural Washington State, or who lived outside Washington, with a known or suspected urological malignancy being evaluated at the University of Washington Urology Clinic via an in person clinic or a telemedicine appointment. Patients were invited to complete a post-visit survey that assessed satisfaction, travel time, costs, and work absenteeism. We compared patient-reported outcomes between those seen as in-person versus telemedicine visits. Results: We invited 291 eligible patients from June 2019 – February 2020 to participate, 140 patients (48%) completed the survey. One-hundred and thirty-three patients had in person visits and 7 had telemedicine visits. Median age was 68, male 86%, and 69% Caucasian. Eighty-seven patients (62%) were from rural Washington; the remainder resided out-of-state. Patients were being evaluated for prostate cancer (57%), kidney cancer (18%), urothelial cancer (24%), and testis cancer (1%). Patient-reported outcomes are displayed in Table. Seventeen patients coming for in-person visits (13%) paid ≥ $1000 in total travel costs. No differences were noted in patient satisfaction. Conclusions: Patients traveling to our clinic from out-of-state and rural Washington incur significant travel time, costs, and time away from work to receive outpatient urologic cancer care. Telemedicine provides a medium for cancer care delivery that eliminates the significant travel burden associated with in person clinic appointments. [Table: see text]