bluuebunny/crossref_metadata_2025 huggingface dataset:
Protein intake and breast cancer incidence and mortality.
Authors: Pan Kathy , Larson Joseph C , Chlebowski Rowan T. , Mortimer Joanne E. , Manson JoAnn E , Van Horn Linda , Rohan Thomas E , Lane Dorothy
Published: May 2020

1569

Background: Associations between dietary protein intake and breast cancer are unclear, in part due to limitations of dietary self-report. Women’s Health Initiative (WHI) investigators compared the accuracy of food frequency questionnaire (FFQ) data on energy and protein intake with objective measures of dietary intake using biomarkers (doubly labeled water for energy and urinary nitrogen for protein [n=544]). Subsequently, regression equations incorporating participant characteristics were developed acknowledging differential reporting dietary data errors based on participant characteristics (Neuhouser Am J Epidemiol). FFQ findings were then used to determine biomarker- adjusted animal vs vegetable protein ratios. Methods: We examined associations of energy and protein intake with breast cancer incidence and mortality in Women’s Health Initiative (WHI) participants 50-79 years of age at entry between1993-1998, with breast cancers verified by medical record review and survival enhanced by serial National Death Index (NDI) searches through 2016. Associations between sources of protein intake (animal versus vegetable) quintiles and breast cancer incidence and mortality were estimated using multivariable Cox proportional hazards regression. Results: With 100,024 eligible participants, after 14 years follow-up, women with higher total protein intake had greater body mass index, were more likely White, menopausal hormone therapy users with higher total energy intake and fat intake. With 6,340 incident breast cancers, 764 deaths from breast cancer and 2,059 deaths after breast cancer, higher vegetable protein intake was associated with significantly lower breast cancer incidence (P for linear trend = 0.01) while higher animal protein intake was associated with significantly higher breast cancer incidence (P for linear trend = 0.03). Higher vegetable protein intake was also associated with significantly lower risk of death after breast cancer (P <0.001) but not with lower risk of deaths from breast cancer (breast cancer followed by death attributed to breast cancer). Animal protein intake was not associated with deaths from breast cancer or deaths after breast cancer. Conclusions: Based on findings from biomarker-calibrated determination of protein intake by source, higher vegetable protein intake was associated with significantly lower risk of breast cancer incidence and of death after breast cancer while higher animal protein intake was associated with significantly higher risk of breast cancer incidence, but not mortality.
The increasing incidence of colorectal cancer in younger patients in the United States: Who, what, when, and where?
Authors: Abel Mary Kathryn , Liao Cheng-I , Van Loon Katherine , Tian Chunqiao , Darcy Kathleen M. , Mann Amandeep Kaur , Kapp Daniel Stuart , Chan John K.
Published: May 2020

1573

Background: Prior studies have shown an increase in the rate of colorectal cancer (CRC) in young individuals in the United States. However, few studies have evaluated the health disparities that exist in this population, particularly using large, national cohorts. We examined differences in age, race, stage, region, and tumor location in younger and older patients with CRC. Methods: Data were extracted from the United States Cancer Statistics (USCS) for individuals diagnosed between 2001 and 2014. CRC incidence data among individuals < 50 years old were compared to those > 50 years old. Age-specific and age-adjusted incidences and trend analyses reported as annual percent change (APC) were performed using SEER*Stat and Joinpoint regression. Results: Of 1,886,441 individuals, the overall age-adjusted incidence of CRC decreased from 52.59 (per 100,000) in 2001 to 35.22 in 2014, with an APC of -3.24. Although over 35% cases were diagnosed in the Southern United States, the Northeast had the highest age-adjusted incidence at 45.26 per 100,000 patients. Younger patients were diagnosed with distant disease at 25.8% compared to only 18.4% in older patients. Younger patients were also more likely to have sigmoid or rectal cancers compared to older patients (64.3% vs. 45.7%). Of the 170,244 individuals < 50 years, 90,855 (53.4%) were men and 79,389 (46.6%) were women. The age-specific incidence in this younger cohort increased from 5.63 to 6.48 between 2001-2014, with an APC of +1.24 in 2001-2008 compared to +2.55 in 2012-2014. The incidence of CRC in patients aged 0-29, 30-39, and 40-49 years was 0.41 (per 100,000), 6.08, and 21.09, respectively. Black individuals < 50 years had the highest age-specific incidence of CRC (7.16 per 100,000) compared to Asian (6.43), White (6.07), or Hispanic (4.76) individuals. Conclusions: Our data suggests that CRC is increasing in young patients, particularly for those between 40-49 years and Black individuals. In our younger cohort, CRC was more commonly found in the sigmoid colon and rectum compared to older patients. Further research is warranted to direct resources towards improved colonoscopy or sigmoidoscopy screening for younger patients at risk.
Hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC): Genotype and phenotype characteristics in a cohort of 197 patients.
Authors: Sanchez-Heras Ana Beatriz , Castillejo Adela , García-Diaz Juan de Dios , Robledo Mercedes , Teule Alex , Sánchez Rosario , Zuñiga Angel , Lastra Enrique , Duran Dominguez Mercedes , Llort Gemma , Yague Carmen , Ramon Y Cajal Teresa , Lopez Consol , Lopez Adria , Balmana Gelpi Judith , Robles Luis , Fonfria Esparza María , Chirivella Isabel , Gomez Luis , Soto José Luís
Published: May 2020

1580

Background: HLRCC is a hereditary condition with autosomal dominant inheritance due to germline mutations in the fumarate-hydratase gene ( FH). It is characterized by skin leiomyomas (SLM) in 48-84% of individuals, uterine leiomyomas (ULM) in 30-72%, renal cysts (RCy) and renal cell cancer (RCC) in 15-34%. We aimed to describe the genetics, the clinical features and the potential genotype-phenotype associations in the largest cohort of FH mutation carriers from Spain. Methods: We performed a multicenter, observational, retrospective study of individuals with genetic or clinical diagnosis of HLRCC. We collected clinical information from medical records. We analyzed genetic variants and looked for genotype-phenotype associations. Statistical analyses were performed by IBM-SPSS Statistics-v.22. Results: We included 197 individuals (113 women, 84 men), 74 index cases and 123 relatives. Twenty-seven different variants were detected, 26 pathogenic (12 missense, 5 frameshift, 4 large-deletions, 3 splice-site and 2 nonsense) and 1 variant of unknown significance (missense). Of 182 patients with full skin examination, 64.8% presented SLM (median age 36 years; range 8-85). ULM were diagnosed in 90.3% of 103 women with gynecologic exam (median age 30 years; range 17- 55). Hysterectomy was performed in 62.9% (median age 34 years; range 21-54). Of 153 patients with radiological records, 37.3 % presented RCy. Nineteen patients (10.9%) presented RCC, 11 males and 8 females (median age 37 years; range 10-67). The histological diagnoses were: 14 papillary, of which 10 were type 2; 3 clear cell carcinoma and 2 unclassified carcinoma. Six tumors had stage I, 2 stage II, 3 stage III, 4 stage IV, and 4 not available. The median overall survival among patients at stages 3-4 was 2.9 years [1.3-4.5]. Patients with missense pathogenic variants showed higher risk of developing SLM (p = 0.043) and ULM (p = 0.002) than those with loss of function variants. Conclusions: In our cohort, the frequency of RCC (10.9%) is lower than that published in cohorts of similar sample size. The most frequent histology was the papillary type-2; however, other histological patterns do not exclude HLRCC. Individuals with missense pathogenic variants show higher incidence of SLM and ULM.
Value of multigene panel retesting of families with BRCA1/2 mutation-negative hereditary breast and ovarian cancer (HBOC).
Authors: Meshoulam Nikolaeva Ekaterina , Terés Raul , Camacho Daniela , Bujosa Aida , Borrell Maria , Gallardo Pablo , Martin Berta , Calvo Nuria , Lopez Consol , Alfonso Rosa , Sola Carla , Cornet Monia , Cliville Nuria , Lasa Adriana , Tibau Ariadna , Arqueros Cristina , Barnadas Agusti , Ramon y Cajal Teresa
Published: May 2020

1582

Background: Despite the use of clinical eligibility criteria and mutation predictive models, a great proportion of families are negative for germline mutations in BRCA1/2 genes. Traditionally, risk assessment of inconclusive results included the recommendation of high-risk surveillance protocol, the update of incident cancer cases in the family and the consideration of additional testing to rule out the possibility of phenocopy. More recently, next generation sequencing multigene panels have become a standard practice in cancer genetics clinics worldwide. We addressed the value of multigene panel retesting of BRCA1/2 negative HBOC families in our institution. Methods: After genetic counseling session and informed consent, a total of 137 individuals (119 probands and 18 extra cancer-affected relatives) from distinct BRCA1/2 negative families were retested using a panel containing 11 breast and ovarian cancer susceptibility genes ( BRCA1/2, PALB2, ATM, CHEK2, PTEN, TP53, STK11, BRIP1, RAD51C, RAD51D). Results: According to the BOADICEA model, the remaining probability of mutation in BRCA1/2 or PALB2 genes in our cohort was 5.5% (0.1-61). The reasons for considering retesting were the addition of any incident cancer diagnosis in 33 cases (24%), a prior study with a low sensitivity screening technique (dHPLC) in 6 families (5%) and the expansion of the study to other putative breast and ovarian susceptibility genes in 98 families (71%). Overall, 3 pathogenic (2 BRCA2, 1 CHEK2) and 8 likely pathogenic variants (1 BRCA2, 4 CHEK2 and 3 ATM) were found. The prevalence was 8%. The detection rate among 19 families with a > 10% remaining probability of mutation in BRCA1/2 and PALB2 genes was 26%. The 3 clinically significant variants in BRCA2 were detected in 2 families and 1 updated cancer family history (BOADICEA remaining probability of 59, 61 and 12%, respectively). Cascade testing was subsequently done in 15 relatives resulting 8 in mutation carriers and 9 true negatives. Conclusions: Our results support the value of updating cancer incident cases and considering expanded panels in selected families.
Chemotherapy remote care monitoring program (CRCMP): Integration of an SMS text patient-reported outcome (PRO) in the electronic health record (EHR) to identify patients needing pharmacist intervention for chemotherapy-induced nausea and vomiting (CINV).
Authors: Hough Shannon , McDevitt Rachel , Nachar Victoria , Kraft Shawna , Brown Anna , Christen Catherine , Walters Barbara , Smerage Jeffrey B.
Published: May 2020

2001

Background: CINV is a feared side effect of cancer therapy. Despite advances in management, CINV is a common cause for emergency department (ED) evaluation and other unplanned health care utilization. The University of Michigan Rogel Cancer Center initiated the CRCMP to proactively identify patients (pts) experiencing CINV and intervene prior to the need for urgent evaluation. Methods: Pts receiving highly emetogenic chemotherapy are identified by administration of a NK1 antagonist. Once enrolled in the CRCMP, pts receive a daily text message survey for 7 days after treatment. The survey is based on the validated MASCC anti-emesis tool (MAT). Responses are stored within a flowsheet in the EHR. Responses above a set threshold trigger a message to the team pharmacist for intervention. Data presented was reviewed from EHR and claims data. Results: In 8 mo, 652 pts received a NK-1 antagonist (2244 total cycles) and 387 pts enrolled in the CRCMP (59%). Each pt enrolled for an average of 1.8 cycles of chemo (range 1-8). Of patients enrolled, 61.4% were female and 86.2% were Caucasian. Chemotherapy intent was curative for 51.7% and palliative for 48.3% of pts. Pts enrolled most commonly received cisplatin-based (29.7%) followed by carboplatin-based (22.5%), and 5-fluoruracil-based (20.9%) therapy. Text message response rate was 94% (N=18,143 responses of 19,256 total messages sent). During 861 cycles of therapy, 7% of responses noted vomiting and 33% of responses noted nausea. Since implementation of CRCMP, total hospitalization, ED, and urgent care use has decreased (p=0.029) compared to historical data. When utilization for nausea-related diagnoses was considered, the reduction was more notable (Table). Conclusions: Pts engaged in the CRCMP for CINV, allowing for rapid assessment of PROs by a pharmacist. Health care utilization related to nausea was reduced following implementation of CRCMP. While these changes were numerically small, reduction in unnecessary care utilizing PROs can contribute to high value care for cancer patients. [Table: see text]
Home-based management of cancer patients (CPs) experiencing toxicities while on anticancer treatment: The impact of a nurse-led telephone triage (NTT).
Authors: Calvetti Lorenzo , Tealdo Marta , Cimenton Roberta , Gentile Angela , Pretto Rachele , Pavan Monica , Gasparin Barbara , Pagiusco Gaetana , De Vivo Rocco , Merlini Laura , Aprile Giuseppe
Published: May 2020

2002

Background: Novel organization models are needed to ensure early management of new treatment-related toxicity of anticancer treatments. Aim of this prospective observational study was to evaluate the impact of the introduction of NTT in reducing hospitalization of CPs. Methods: CPs on active medical treatment at the Department of Oncology of San Bortolo Hospital (Vicenza, Italy) were given instructions to refer to NTT in case of treatment-related adverse events (TRAEs). The service was opened Mon to Fri from 8am to 8pm. Assessment of TRAEs was performed by trained oncology nurses according to the CTCAE scale and subsequent actions were taken according to the severity of the events. The assessment was made under supervision of a medical oncologist in charge of the service while on duty. Primary endpoint of the study was to compare the rate of hospitalization of CPs on anticancer treatment after the introduction of NTT compared to 2017-2018 period. Results: From September 2018 to September 2019 1,075 patients received systemic anticancer treatment (versus 936 patients in the equivalent 2017 – 2018 period). Total consultations at NTT were 429; 581 TRAEs were reported. 117 patients reported more than one TRAE. CTCAE were graded as G1 237 (40.8%), G2 231 (39.8%) or G3-G4 113 (19.4%). The most common grade ≥ 3 TRAE was fever (38 events (33.6%) that resulted a febrile neutropenia in 7 cases) followed by cancer pain (15 (13.3%)) and fatigue (9 (8%)). In the observation period, 109 CPs on treatment were hospitalized versus 138 in the 2017-2018 period with a normalized hospitalization rate of 10.1% versus 14.7 % (p = 0.002, chi-square) with a reduction of normalized number of hospitalizations of 44 (estimated cost savings of 380.160 euros). Conclusions: Our results provided evidence of successful implementation of the NTT system in reducing rates of hospitalization through emergency room in cancer patients receiving modern medical treatments.
Launch prices and price developments of cancer drugs in the United States and Europe.
Authors: Vokinger Kerstin Noëlle , Daniore Paola , Lee ChangWon C , Kesselheim Aaron S , Hwang Thomas J
Published: May 2020

2006

Background: Cancer drug costs are rising in the US and Europe. While drug manufacturers set prices without restriction in the US, European countries have regulations that allow national authorities to directly negotiate drug prices at launch and over time. We analyzed and compared the launch prices and price developments of cancer drugs in the US, Germany, Switzerland and England. Methods: We identified new drugs indicated to treat solid tumors in adults that were FDA-approved between 2009 and 2019 and had also been approved by the EMA and Swissmedic by 31 December 2019. Launch prices and post-launch price changes as of 1 January 2020 were extracted and adjusted to average sales prices for monthly treatment costs in the US and compared to comparable currency-adjusted ex-factory monthly treatment costs in Germany, Switzerland, and England. A cross-sectional analysis was conducted to infer yearly trends in launch prices and post-launch price changes across the countries. Results: The study cohort included 42 drugs for solid tumors, of which 40 (95%) drugs were first approved in the US compared to Germany and England, and 41 (98%) to Switzerland. Average launch prices for monthly treatment costs per patient were $15,178 in the US vs $7,049 in Germany, $7,421 in Switzerland and $8,176 in England, i.e., 215% (interquartile range [IQR] 263%-187%), 205% (IQR 202%-185%) and 186% (IQR 166%-189%) higher in the US compared to Germany, Switzerland and England respectively. Post-launch prices of 36 (86%), 40 (95%), and 38 (90%) drugs decreased over time with total savings of monthly treatment costs for all drugs in the study cohort of $86,744, $44,936, and $1744 in Germany, Switzerland, and England respectively. By contrast, prices of 8 (19%) drugs decreased, while 34 (81%) increased post-launch in the US with total additional expenses of $128,192 for monthly treatment costs. Conclusions: Launch prices for cancer drugs are far higher in the US than in Germany, Switzerland, or England. These price disparities continue to increase substantially after market entry since cancer drug prices, in general, decrease over time in Europe and increase in the US. Spending on cancer drugs could be reduced in the US if it adopted the principles used to more effectively negotiate drug prices in Europe.
Prospective validation of a machine learning algorithm to predict short-term mortality among outpatients with cancer.
Authors: Manz Chris , Chivers Corey , Liu Manqing , Regli Susan B , Changolkar Sujatha , Evans Chalanda N. , Rareshide Charles A.L. , Draugelis Michael , Braun Jennifer , Navathe Amol S. , Kumar Pallavi , Bekelman Justin E. , Patel Mitesh S. , O'Connor Nina , Schuchter Lynn Mara , Shulman Lawrence N. , Parikh Ravi Bharat
Published: May 2020

2009

Background: Oncologists accurately identify only 35% of patients with cancer who will die in six months. There is an urgent need for automated, accurate prognostic systems to inform treatment and advance care planning in oncology. We assessed the prospective performance of a previously described ML algorithm (Parikh et al, JAMA Netw Open, 2019) to predict short-term mortality in a cohort of general oncology outpatients. Methods: Our prospective cohort consisted of patients aged ≥18 years who had a medical or gynecologic oncology encounter between March 1 and April 30, 2019 in either a tertiary academic practice or one of twelve community practices within a large academic cancer system. We used a retrospectively validated gradient-boosting ML algorithm, based on 559 structured electronic health record (EHR) variables, to predict 180-day mortality prior to each oncology encounter. For patients with multiple encounters, we selected the last encounter to assess performance. We assessed several performance metrics, including area under the receiver operating curve (AUC), area under the precision-recall curve (AUPRC), scaled Brier score (sBrier; a measure of calibration ranging from 0 [random] to 1 [perfect]), and positive predictive value (PPV). Results: Of 25,537 unique patients, median age was 64.4 (interquartile range 53.3 – 73.0), 76.8% were White, 56.5% were treated at a community center, and 4.1% died within 180 days. The ML algorithm had an AUC of 0.89 (95% confidence interval [CI] 0.88-0.90), AUPRC 0.34, and sBrier 0.29. At a prespecified threshold of 40%, observed 180-day mortality was 44.5% (95% CI 40.7 – 48.4%) in the high-risk group vs. 3.0% (95% CI 2.8% – 3.3%) in the low-risk group. There was an 85-fold difference in mortality (13.6% vs. 0.16%) in the top vs. bottom risk quartiles. The model was well-calibrated for mortality risks ≤40% and slightly under-calibrated for mortality risks > 40%. Performance varied across cancer types in the tertiary hospital but did not vary by race or practice type (Table). Conclusions: In this prospective cohort study among outpatients with cancer, a ML prognostic algorithm based on EHR data had better discrimination and calibration that published cancer-specific models. This is one of the first ML prognostic models to be prospectively validated in oncology. [Table: see text]
Four distinct patient-reported outcome (PRO) trajectories in longitudinal responses collected before, during, and after chemotherapy.
Authors: Blayney Douglas W. , Azad Amee , Yilmaz Melih , Bozkurt Selen , Brooks James D. , Hernandez-Boussard Tina
Published: May 2020

2012

Background: Cancer chemotherapy, whether given with curative or palliative intent, is toxic. Toxicity is routinely captured in clinical trials by investigator observation and increasingly by PRO. The ability to capture PRO in the routine treatment workflow has been standard at Stanford since 2015 (Roy et al ASCO 2020). Analysis of longitudinally captured, real world PRO and prospectively identifying patients (pts) whose quality of life (QOL) is at risk of deteriorating either permanently or temporarily is needed. Routine serial PRO measurement should enhance precision care delivery, precision toxicity detection and management. Methods: We identified patients undergoing chemotherapy at Stanford and analyzed PROMIS (PRO Measurement Information System) responses. Pts with PROMIS survey information at three intervals—pre-treatment, during chemotherapy and post chemotherapy—were identified. We evaluated global physical health (GPH) and global mental health (GMH). Pts with a clinically significant decrease (CSD) in GPH or GMH scores were identified. A k-median cluster analysis was used to identify patient trajectory clusters and a machine-learning model was applied to identify risk factors for CSD and predict CSD. Results: We identified 670 adult oncology patients undergoing chemotherapy who completed at least one PROMIS survey in each interval. GPH scores were 48.4 ± 9.1 before, 47.1 ± 8.5 during, and 48.5 ± 8.9 after chemotherapy and GMH scores were 50.5 ± 8.2, 49.1 ± 8.5, and 50.7 ± 9.0, respectively. The majority of patients did not have a CSD in GPH or GMH post treatment compared to pretreatment scores. Pretreatment scores were the strongest predictor of a CSD in GPH and GMH. Trajectory clustering identified four distinct trajectories: Temporary Improver, Temporary Deteriorator, Improver, Inexorable Deteriorators. We were not able to predict any cluster based on pre-treatment features. Conclusions: Using routinely collected PROMIS surveys in a real-world setting, we are able to predict patients with post-treatment decreases in their physical and mental well-being. We further defined four novel patient trajectories during chemotherapy, which could guide personalized supportive interventions to improve patient’s chemotherapy experience. Identification of patients at risk for deterioration and the patterns of deterioration could help guide efficient deployment of toxicity mitigating and supportive care interventions to patients most in need.
Absence of optimism bias in industry-sponsored cancer trials.
Authors: Noticewala Sonal S , Patel Roshal R , Ludmir Ethan B.
Published: May 2020

2020

Background: Randomized controlled trials (RCTs) in oncology power their studies to detect expected effect sizes. Prior studies have shown that there is optimism bias, the a priori overestimation of treatment effect size among cooperative-group-supported RCTs. However, it is unknown whether such bias is present among industry-supported trials. Methods: All published phase 3 clinical oncology RCTs were identified through ClinicalTrials.gov. Only superiority-design RCTs assessing a therapeutic intervention to improve disease-related outcomes were included. We compared the ratio of observed to expected hazard ratio (OEHRR) between trial subgroups using the Mann-Whitney U-test; comparisons of median OEHRR to a hypothetical median of 1 was performed using the Wilcoxon Signed Rank test. Results: We identified 140 phase 3 trials with available hazard ratio (HR) data. Of these, 123 trials (88%) were industry-sponsored, and 38 trials (27%) were cooperative-group-supported. For all trials, the median OEHRR was 1.099 (IQR = 0.855-1.291), demonstrating evidence of optimism bias when compared to a hypothetical median OEHRR of 1 (p = 0.018). In the subgroup analysis, compared to non-industry-sponsored trials (median OEHRR 1.253, IQR 1.061-1.334), industry-supported trials (median OEHRR 1.061, IQR 0.829-1.274) had a significantly lower OEHRR (p = 0.022) and did not demonstrate optimism bias (p = 0.15). Similarly non-cooperative group trials (median OEHRR 1.208, IQR 1.019-1.317) had a significantly lower OEHRR (p = 0.005) and did not demonstrate optimism bias (p = 0.562) compared to cooperative group trials (median OEHRR 1.208, IQR 1.019-1.317), which did demonstrate optimism bias (p < 0.001). Conclusions: Cooperative group trials, which represent a minority of trials, suffer from optimism bias. In contrast, industry-funded trials, which account for the majority of trials, do not demonstrate evidence of optimism bias, and have very close concordance between observed and expected effect size. These findings suggest that the powering and design of industry-funded trials better models the outcomes eventually observed. The reasons for this are likely complex and multifactorial, but may include financial constraint considerations, as industry-supported trials may not be as financially-limited as cooperative group studies. Therefore, industry-supported studies may be able to power trials with sufficient participants to reflect the estimated effect size.
Distress screening through PROMIS at an academic cancer center and network site: Implementation of a hybrid model.
Authors: Roy Mohana , Neal Joel W. , Bugos Kelly , Sharp Christopher , Falconer Patricia , Rosenthal Eben Lloyd , Blayney Douglas W. , Modaressi Shiva , Robinson Ashley , Ramchandran Kavitha
Published: May 2020

2021

Background: The NCCN guidelines recommend routine distress screening of patients with cancer, but the implementation of such programs is inconsistent. Up to one in three such patients experience distress, however fewer than half of them are identified and referred for supportive services. Methods: We implemented a hybrid (electronic and paper) distress screening tool, using a modified version of the PROMIS-Global Health questionnaire. Patients received either an electronic or in-clinic paper questionnaire to assess overall health and distress at the Stanford Cancer Center and its associated integrated network site. Iterative changes were made including integration with the electronic health record (EHR) to trigger questionnaires for appointments every 60 days. A consensus “positive screen” threshold was defined, with data collected on responses and subsequent referrals placed to a supportive care services platform. Results: Between June 2015 and December 2017, 53,954 unique questionnaires representing 12,744 distinct patients were collected, with an average completion rate of 58%. Approximately 30% of the questionnaires were completed prior to the visit electronically through a patient portal. The number of patients meeting the positive screen threshold remained ~ 40% throughout this period. Following assessment by the clinical team, there were 3763 referrals to cancer supportive services. Among the six most common referral categories, those with a positive screen were more likely to have a referral placed (OR 6.4, 95% CI 5.8-6.9 p- < 0.0001), with a sensitivity of 80% and a specificity of 61%. However, 89% of responses with a positive screen did not have a referral to supportive care services. Conclusions: The hybrid electronic and paper use of a commonly available patient reported outcome tool, as a high throughput distress screening tool, is feasible at a multi-site academic cancer center. Our positive screen rate for referrals was sensitive and consistent, but with a low positive predictive value. This screening also resulted in variable clinical response and overall increased clinical burden. Future directions for our group have included refining the threshold for a positive screen and implementation of a real-time response system, especially to address acute concerns.
The impact of early integrated supportive care on length of stay at an NCI-designated cancer center.
Authors: Kaltman Jessica , Sun Can-Lan , Loscalzo Matthew J. , Kronstadt Erik , Goodspeed Elizabeth , Qamar Samina , Glaser Christine , Zachariah Finly , Leitner Andrew , Biller Les , Dale William
Published: May 2020

2024

Background: With movement towards value-based care, institutions seek ways to reduce costs by decreasing inpatient stays. A multidisciplinary approach to supportive care, especially when provided early, is one way to realize value-based care. We assess the impact of pre-admission versus post-admission involvement of an Integrated Supportive Care Model (ICSM) on inpatient length of stay (LOS) at a NCI-designated cancer center. Methods: Data was collected from 2014 to 2016 at City of Hope. The Integrated Supportive Care Model at City of Hope includes: palliative care, psychiatry, psychology, interventional pain, social work, child-life, distress screening, and couples program. “Pre-admission” was defined as seeing at least one service prior to hospital admission; “Post-admission” defined as seeing at least one service during admission. “Short LOS” for hematology patients was categorized as ≤ 14 days and for oncology patients as ≤ 3 days. Continuous LOS between patients receiving an ISCM intervention pre- and post-admission was compared using Kruskal-Wallis test. Univariate and multivariable logistic regression was done to examine association between involvement of ISCM pre- and post-admission and categorical LOS. P-values < 0.05 were considered statistically significant. Results: 1,627 (809 with hematologic malignancy, 818 with oncologic malignancy) patients with only one hospitalization during the study time were included. For hematology patients, involvement with the ISCM pre-admission was associated with shorter LOS ( ≤ 14 days) compared with involvement post-admission (29.3 vs 11.1%, multivariable OR = 4.08, P < 0.001). Median LOS for hematology patients who participated in the ISCM pre-admission was shorter than those who received ISCM services post-admission (21 vs. 22 days, p = 0.049). Similarly, for oncology patients, ISCM involvement pre-admission was associated with shorter LOS ( ≤ 3 days) compared to involvement post-admission (91.4% vs 8.6%, multivariable OR = 3.74, P < 0.001). Median LOS for oncology patients who received an ISCM intervention pre-admission was shorter than those who received an ISCM intervention post-admission (2 vs. 6 days, p < 0.001). Conclusions: In hematologic and oncologic malignancies, use of an ISCM prior to patient’s first hospitalization is associated with significantly shorter LOS compared with those who received ISCM services during the hospital stay. This suggests efforts should be made to include an ISCM early in the trajectory of illness, prior to first hospitalization.
Predicting the risk of VISIT emergency department (ED) in lung cancer patients using machine learning.
Authors: Rodriguez-Brazzarola Pablo , Ribelles Nuria , Jerez Jose Manuel , Trigo Jose , Cobo Manuel , Ramos Garcia Inmaculada , Gutierrez Calderon M Vanesa , Subirats Jose Luis , Galeote Miguel Ana María , Mesa Hector , Galvez Carvajal Laura , Franco Leo , Jimenez Rodriguez Begoña , Godoy Ana , Ruíz Sofía , Mesas Andres , Iglesias Campos Marcos , López Irene , Rueda Dominguez Antonio , Alba Emilio
Published: May 2020

2042

Background: Lung cancer patients commonly need unplanned visits to ED. Many of these visits could be potentially avoidable if it were possible to identify patients at risk when the previous scheduled visit takes place. At that moment, it would be possible to perform elective actions to manage patients at risk to consult the ED in the near future. Methods: Unplanned visits of patients in active cancer therapy (i.e. chemo or immunotherapy) are attended in our own ED facilities. Our Electronic Health Record (EHR) includes specific modules for first visit, scheduled visits and unplanned visits. Lung cancer patients with at least two visits were eligible. The event of interest was patient visit to ED within 21 or 28 days (d) from previous visit. Free text data collected in the three modules were obtained from EHR in order to generate a feature vector composed of the word frequencies for each visit. We evaluate five different machine learning algorithms to predict the event of interest. Area under the ROC curve (AUC), F1 (harmonic mean of precision and recall), True Positive Rate (TPR) and True Negative Rate (TNR) were assessed using 10-fold cross validation. Results: 2,682 lung cancer patients treated between March 2009 and October 2019 were included from which 819 patients were attended at ED. There were 2,237 first visits, 47,465 scheduled visits (per patient: range 1-174; median 12) and 2,125 unplanned visits (per patient: range 1-20; median 2). Mean age at diagnosis was 64 years. The majority of patients had late stage disease (34.24 % III, 51.56 % IV). The Adaptive Boosting Model yields the best results for both 21 d or 28 d prediction. Conclusions: Using unstructured data from real-world EHR enables the possibility to build an accurate predictive model of unplanned visit to an ED within the 21 or 28 following d after a scheduled visit. Such utility would be very useful in order to prevent ED visits related with cancer symptoms and to improve patients care. [Table: see text]
Driving quality improvement: How clinical decision support can facilitate compliance with evidence-based pathways.
Authors: Patt Debra A. , He Bo , Garey Jody S. , Rowan Paul , Swartz Michael D , Linder Stephen , Brooks Barry Don , Neubauer Marcus A.
Published: May 2020

2045

Background: Cancer care is changing rapidly with more detailed understanding of disease and more numerous therapeutic choices. As treatment choice is more complex, mechanisms to improve compliance with evidence based treatment can improve the quality of cancer care. Methods: A retrospective cohort study was conducted from January 2014-May 2016 evaluating the impact of a clinical decision support system (CDSS) on compliance with evidence based pathways (EBP) across 9 statewide community based oncology practices. These EBP are developed with physician input on efficacy toxicity and value and incorporated in to a CDSS that is used within the Electronic Health Record (EHR) at point of care to alter the choice architecture a clinician sees when prescribing therapy. A multi-level logistic regression model was used to adjust for group effects on physician or practice behavior. SAS 9.4 software was used and GLIMMIX was applied. Individual physician benchmark compliance was evaluated using McNemar's test. Results: Regimen compliance with EBP was measured pre- and post- implementation of the CDSS tool across a large network encompassing 9 statewide practices and 633 physicians who prescribed over 30,000 individual patient treatment regimens over a 6 month period. The CDSS that is incorporated within the EHR significantly improved compliance with EBP across the entire cohort of practices, and in individual practices (see Table). Individual oncologists reached a target of 75% compliance more often (58% vs 72%) after implementation of the tool (p < 0.001). Conclusions: CDSS is a tool that improves compliance with EBP that is effective at improving targets of compliance broadly, at the practice, and at the individual clinician level. Clinical informatics solutions that influence physician behavior can be inclusive of physicians in design, iterative in process, and nudge as opposed to force clinician behavior to drive quality improvement. These clinical informatics solutions grow in importance as the complexity of cancer care continues to increase and we seek to improve upon the quality and value of care delivery. [Table: see text]
Use of real-world data to understand barriers to interventional clinical trial enrollment in community oncology clinics (COC).
Authors: Blakely Johnetta , Gordan Lucio N. , Schwartzberg Lee S. , Gutman Jacqueline , Adamson Blythe J.S. , Bourla Ariel B. , Meropol Neal J. , Ramsey Scott David , Green Robert J.
Published: May 2020

2061

Background: Increasing enrollment in clinical trials remains a national priority, yet there are limited data from COCs on the degree to which common trial exclusion criteria (EC) and socioeconomic factors play a role in low enrollment rates. Methods: We analyzed data from the nationwide Flatiron Health electronic health record (EHR) derived de-identified database. COC were eligible if they had given a clinical trial study drug to ≥2 patients (pts)/year. We included pts with one of eight advanced or metastatic solid tumors who received ≥1 line of systemic anticancer therapy between 1/1/2014 and 11/30/2019. We defined EC as either: creatinine > 1.5 mg/dl or Ccl < 45 ml/min, Hb < 9 g/dL, ANC < 1500/ul, plts < 100,000/ul, bilirubin > 1.5 upper limit of normal (uln) or AST/ALT > 2.5 uln within 30 days or ECOG performance status (PS) ≥ 2 within 60 days prior to start of therapy. We calculated the percentage of pts with ≥1 EC relative to the group of candidate pts, stratified by therapy line (1L, 2L, 3L+). We used multivariate logistic regression models to evaluate the effect of EC and socioeconomic factors (age, race, Medicaid) on the likelihood of receiving a clinical study drug for each line of therapy. Results: In this sample of 35 COCs, 26,988 pts received ≥1 systemic therapy. Pts with ≥ 1 EC: 28.4% in 1L, 34.2% in 2L, 37.4% in 3L. Percentages of pts with an ECOG PS ≥ 2 were: 15.6% (1L), 18.2% (2L), 19.8% (3L). Pts receiving a clinical study drug: 1.7% of 26,988 in 1L, 2.0% of 12,738 in 2L, 2.9% of 5,333 in 3L+, and 3.1% in any line. Excluding pts with ≥1 EC from the denominator modestly improved overall accrual: 2.0% of 19,729 in 1L, 2.3% of 8,588 in 2L, 3.7% of 3,470 in 3L+. In multivariate logistic regression, ECOG PS ≥ 2 was strongly associated with not receiving a study drug [odds ratio (95% CI); 1L: 0.25 (0.16-0.4); 2L: 0.28 (0.17-0.49); 3L: 0.21 (0.1-0.44)]. The likelihood of receiving a clinical study drug (any line) was lower for pts who are Black [0.63 (0.48-0.82)], Latino [0.49 (0.32-0.75)], and pts older than 70 years [0.63 (0.54-0.72)]. Medicaid pts were not significantly less likely to receive study drug [0.83 (0.64-1.07)]. Conclusions: In COC, common trial EC reduce pt availability for trials by > 25%. Poor PS is highly prevalent and influential. These EC and complex trial requirements challenge COC’s ability to recruit representative pt populations. Future efforts to increase enrollment in trials must consider common EC along with well known barriers to enrollment of unrepresented groups.
A pilot study of a wearable monitoring system as an adjunct to geriatric assessment in older adults with cancer.
Authors: Wong Karlton , Shen John , Ramezani Ramin , Zhang Wenhao , Xie Zhuoer , Naeim Arash , Elashoff David
Published: May 2020

2062

Background: Advances in health technology provide potential tools that can aid in assessing and monitoring the functional status of the growing older adult population diagnosed with cancer. We piloted a novel wearable monitoring platform, Sensing in At-Risk Populations (SARP), which consists of a smartwatch, software application for health monitoring, and a central data processing and analytics engine. Methods: This is a prospective single center, single arm study, utilizing the SARP platform to risk stratify older adults with cancer and determine correlation with treatment-related adverse events and healthcare utilization. Pts age ≥60 undergoing active treatment, were offered participation. Pts were instructed to wear the smartwatch for ≥7 days. We used Kruskal-Wallis to correlate wearable data with clinical outcomes: toxicity, ED visits, hospitalizations, and mortality. We also compared SARP data to independently collected ECOG PS, CARG score, ADLs, and IADLs. Results: From 8/2016 to 8/2017, 54 older adults were consented, and 26 had wearable data available for analysis. The average age was 72 years, with 18 males and 8 females. 12 pts had ECOG PS of 0, 12 with ECOG of 1, and 2 with ECOG of 2. 4 pts had CARG score of low, 17 intermediate, and 3 high. Energy intensity was significantly correlated with ED visits, with an effect size of 0.95 (p = 0.04). Similarly, energy intensity and hospitalizations had an effect size of 0.87 (p = 0.06). The CARG scores were noted to be significantly correlated with dose delay and dose reduction with an effect size 0.45 (p = 0.05) and 0.4 (p = 0.05), respectively. Spearman correlation analysis demonstrated that walking time, active time, and energy intensity positively correlate with ADLs and IADLs, and inversely correlated with ECOG PS and CARG risk. Conclusions: Though this is a limited study due to sample size, the overall trend demonstrated that the SARP platform offers an adjunct tool in assessing and risk stratifying older patients with cancer undergoing active therapy. Additional cohorts are now enrolled with an at-home monitoring system. [Table: see text]
Physician whistle-blower’s experiences in hematology-oncology safety litigation against pharmaceutical companies.
Authors: Godwin Ashley Caitlin , Hoque Shamia , Vemula Jayanth , Ausdenmoore Henry C , Zhu Michael , Bennett Charles L.
Published: May 2020

2074

Background: Some clinicians have reported initial series of severe or fatal adverse drug reactions (ADRs) that affected large hematology-oncology patient numbers and for which pharmaceutical manufacturers subsequently paid large settlements or fines for allegedly failing to inform physicians about such ADRs. Based on their large human costs ( > 1,000 serious illnesses or deaths) and large financial costs ( > $100 million in settlements or fines), we have termed these ADRs as titanic ADRs. At a Senate hearing on one titanic, Vioxx, (a COX-2 inhibitor that was evaluated for colorectal cancer prevention), the clinician reporter was termed a “whistleblower” by a senator although this individual had not filed a formal whistleblower lawsuit. We identified physicians who would fit this characterization of whistleblowers and had published titanic hematology-oncology ADR reports in high impact journals. Methods: Hematology-oncology titanic ADRs were identified by collaborators with two NIH-funded drug safety networks (RADAR and SONAR (1998-2019)). Exclusion criteria included having also filed a whistleblower lawsuit. Qualitative research analyses evaluated content of statements made by whistleblowers to national reporters or at congressional hearings. Results: 18 physicians who reported titanic hematology/oncology-associated ADRs in peer-reviewed literature and discussed their findings in national news media outlets are included. Titanic ADRs included death, nephrogenic systemic fibrosis, coronary artery disease, and venous thromboembolism related to COX-2 inhibitors, heparin, gadolinium dye, thalidomide, lenalidomide, epoetin, and darbepoetin. Related financial settlements ranged from $100 million to $4.85 billion. Whistleblowers were from the United States, Denmark, and Germany. Primary motivations were public health and medical awareness. Whistleblowers reported having gone through lawsuits and having had executives request that the whistleblowers’ university terminate employment. One whistleblower was quoted saying “I believe that the lawsuit is an attempt to silence me.” Conclusions: Clinician whistleblowers of titanic hematology-oncology ADRs experienced reputational, financial, and personal threats. Motivations for reporting titanic ADRs were mainly public health and medical awareness focused. This differs from our previous study on clinicians publishing on non-titanic ADRs, where the primary motivation was scientific curiosity.
Annual trends in opioid prescribing for patients (Pts) with metastatic non-small cell lung cancer (mNSCLC): Cancerlinq data analysis, 2010 to 2017.
Authors: Paice Judith A. , Chen Li , Garrett-Mayer Elizabeth , Hagerty Karen S , Maletz Novick Kristina Lynne , Potter Danielle , Riffon Mark , Rhodes Whitney , Wang Liya , Bruinooge Suanna S.
Published: May 2020

2076

Background: Despite opioid misuse and abuse, opioids remain a mainstay for management of cancer pain. Government, payers, and institutions have implemented policies to reduce opioid use. The impact of these restrictions on oncologist prescriptions (Rx) of opioids and management of cancer pain in pts with cancer is not well known. Methods: A retrospective, observational analysis used deidentified EHR data from ASCO’s CLQ Discovery database. Study cohort included pts with mNSCLC diagnosis and >1 clinical encounter (including opioid Rx) from CLQ clinician during 2010-2017. Opioids included DEA schedule II and III opioid drugs prescribed for cancer pain, excluding cough suppressants. Annual Rx rates were defined as the number of mNSCLC pts who had ≥ 1 opioid Rx dated 2010-2017 per CLQ total mNSCLC pts who had ≥1 clinical encounter in the year. Annual rates demonstrate trends in opioid prescribing patterns over time. Results: 18,106 pts with mNSCLC clinical activity between 2010 and 2017 were identified. Overall, 39.8% of pts had opioid Rx in 2010-2017. Annual Rx rates increased from 2010-2015 and fell 2016-2017 (see table). Hydrocodone was the second most frequently prescribed opioid overall (N=4211 pts), but Rx rates began to decline in 2012. Tramadol and acetaminophen + codeine Rx rates gradually increased throughout the time period. DEA initially scheduled Tramadol as schedule IV in 2014. Conclusions: Opioids are commonly prescribed by oncologists for patients with mNSCLC. Rx rates have declined since 2015, likely due to increased government, payer, and institutional restrictions on access. Hydrocodone Rx declined since 2012, perhaps exacerbated by reclassification from schedule III to schedule II by the DEA (October 2014). Rxs for schedule IV and III opioids (known to be of lower potency) increased modestly, likely due to comparatively fewer prescribing restrictions. Additional research is needed to understand whether the decline continues and the impact on management of cancer pain, particularly among metastatic patients. [Table: see text]