bluuebunny/crossref_metadata_2025 huggingface dataset:
A noninvasive multi-analytic approach for lung cancer screening of patients with pulmonary nodules.
Authors: Zheng Hong , Han Tiancheng , Liu Quanxing , Zhou Dong , Jiang Li , Hou Bin , Lu Xiao , Li Qingyuan , Zhihua Pei , Hong Yuanyuan , Zhang Yaxi , Chen Weizhi , He Ji , Dai Jigang
Published: May 2020

1550

Background: Low-dose computed tomography (LDCT) is an effective approach for lung cancer screening of high-risk patients with pulmonary nodules, however with varying false positive rates depending on the somewhat subjective judgement of the practice professional. Artificial intelligence derived from machine learning of comprehensive patient profiles, including multi-omics and clinical data, has the potential to provide more objective assessment of patient’s risk in order to aid clinician’s decision making. We have developed a multi-analyte algorithm-based assay (MAAA) that incorporates ctDNA mutation, ctDNA methylation, and protein biomarker profiles evaluated through non-invasive blood-based testing, as well as patient’s clinical information, to improve the diagnostic efficacy of lung cancer. Methods: 98 high-risk patients with pulmonary nodules were enrolled in two independent cohorts (68 for training/testing and 30 for independent validation). The malignancy of the pulmonary nodules were established through pathology of surgical-removed nodules. Prior to surgery, each patient was also subject to cell-free DNA-based sequencing for DNA mutation and DNA methylation profiling, as well as serum protein biomarker profiling. On the training/testing patient cohort, machine-learning-based predictive models were first built for malignancy status prediction based on each type of molecular or clinical features. A final ensemble model was then constructed to incorporate the measurements based on molecular and clinical markers to provide the ultimate recommendation on the malignancy of the pulmonary nodule. The performance of each individual model and the final ensemble model was benchmarked on the training/testing cohort, and also validated on the independent validation cohort. Results: On the 30-patient independent validation cohort, individual prediction models based on clinical information, protein marker, ctDNA mutation, and ctDNA methylation profiles achieved predictive AUC of 0.59, 0.48, 0.71, and 0.84, respectively. The final ensemble model achieved predictive AUC of 0.86, which has strongly indicated that an integrative, algorithm-based approach of multi-analytic molecular and clinical profiles greatly outperforms any single-analytic profiling. Conclusions: Multi-analyte algorithm-based approach can be utilized to assist in lung cancer screening for patients with pulmonary nodules. It has demostrated a high accuracy through independent validation, and has outperformed any single-analyte testing in our study.
Green tea extract to prevent colorectal adenomas in men and women: Results of the MIRACLE trial.
Authors: Ettrich Thomas Jens , Stingl Julia , Menzler Stefan , Messmann Helmut , Kleber Gerhard , Zipprich Alexander , Frank-Gleich Stefanie , Algül Hana , Metter Klaus , Odemar Frank , Heuer Theodor , Hügle Ullrich , Behrens Rüdiger , Berger Andreas , Scholl Catharina , Schneider Katharina , Perkhofer Lukas , Rohlmann Friederike , Muche Rainer , Seufferlein Thomas
Published: May 2020

1551

Background: Prevention of colorectal adenomas (CA) can reduce colorectal cancers (CRC). Epidemiological and experimental data suggest that the green tea catechin epigallocatechingallate has an antineoplastic effect in the large bowel. MIRACLE is the largest trial so far to examine the effect of three-year daily intake of green tea extract (GTE) on the incidence of metachronous CA in a Caucasian population. Methods: Prospective, parallel group, double-blinded, placebo-controlled, randomized multicenter trial (40 German centers, recruitment 11/2011-6/2015). Patients (n = 1001, age 50-80y), polypectomy ≤ 6 months and tolerating GTE well (one-month run-in) were randomized to receive decaffeinated GTE standardized to EGCG (150 mg bid, capsules) or placebo (P) for 3 years. Primary endpoint: Incidence of metachronous CA at the 3-year follow-up colonoscopy. Secondary endpoints: Occurrence, number, localization, size, histological subtype of CA, frequency of CRC, biomarker and safety. Strata: study center, low-dose aspirin (≤100 mg/d). Results: Clinical parameters were well balanced. CA incidence at the 3-year follow-up colonoscopy was analyzed in the modified ITT set (modITT; n = 309 patients (GTE), n = 323 (placebo), timely follow up colonoscopy) and the per protocol set (PP, modITT set without major protocol violations). Incidence of CA was 55.7 % (P) and 51.1% (GTE), (modITT, adj. RR 0.905, one sided, p = 0.081), respectively 54.3 % (P) and 48.3% (GTE) (PP, adj. RR 0.883, one sided, p = 0.058). These differences did not reach statistical significance. In the preplanned exploratory analysis regarding gender incidence of CA in females was 47.9% (P) and 47.6% (GTE) in the modITT-set (adj. RR 0.989; 95%-CI: 0.753,1.299; p = 0.935), respectively 45.4% (P) and 46.9% (GTE) in the PP-set (adj. RR 1.014; 95%-CI: 0.748, 1.373; p = 0.930). In contrast, in the male population incidence of CA in the follow-up colonoscopy was 60.4% (P) and 52.9% (GTE) in the modITT-set (adj. RR 0.846; 95% CI 0.717, 0.999); p = 0.048), respectively 59.1% (P) and 49.1% (GTE) in the PP-set (RR 0.803, 95% CI: 0.666, 0.969; p = 0.022). Thus, GTE intake was associated with a significant, 12.4 relative and 7.5% absolute reduction of metachronous CA in the male modITT population. There were no differences with respect to safety between the groups. Conclusions: GTE reduced the incidence of metachronous CA. However, a significant effect was only observed in the in the male population whereas there was no effect in the female population. Clinical trial information: NCT 01360320.
3,3'-Diindolylmethane (DIM): A nutritional intervention and its impact on breast density in healthy BRCA carriers compared to non-treated carriers—A prospective clinical trial.
Authors: Yerushalmi Rinat , Bargil Sharon , Ber Yaara , Ozalvo Rachel , Sela Sivan , Rapson Yael , Pomerantz Adi , Tsoref Dalia , Sharon Eran , Caspi Opher , Grubstein Ahuva , Margel David
Published: May 2020

1556

Background: Women who carry the BRCA mutation are at high lifetime risk of breast cancer, but there is no consensus regarding an effective and safe chemoprevention strategy. A large body of evidence suggests that 3,3-diindolylmethane (DIM), a dimer of indole-3-carbinol (I3C) found in cruciferous vegetables, can potentially prevent carcinogenesis and tumor development. The primary aim of this prospective study was to investigate the effect of DIM supplementation on breast density, a recognized predictive factor of breast-cancer risk. Methods: Participants were 23 healthy female BRCA carriers (median age 47 years; 78% postmenopausal) who were treated with oral DIM 100 mgx1/d for one year. The amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE) on magnetic resonance imaging (MRI) performed before and after the intervention were scored by two independent expert radiologists using the Breast Imaging and Reporting Data System (BI-RADS). Each woman in the cohort was matched by age (within 3 years) and menopausal status to a woman attending the clinic who was not participating in the study and who underwent breast MRI in parallel year. Results: A decrease in the average score for FGT amount from 2.8±0.8 at onset to 2.65±0.842.8 after one year (p = 0.031), with no significant change in BPE (p = 0.429). A group of DIM-untreated age- and menopausal-status-matched clinic patients did not show a significant change in FGT amount (p = 0.33) or BPE (p = 0.814) in a parallel year. Mean estradiol level decreased from 159 to 102 pmol/L (p = 0.01), and mean testosterone level, from 0.42 to 0.31 pmol/L (p = 0.007). Side effects were grade 1. Conclusions: One year’s supplementation with DIM 100 mgX1/d in BRCA carriers was associated with a significant decline in FGT amount on MRI. Larger randomized studies are warranted to corroborate these findings. Clinical trial information: NCT02197000.
Development of a novel liquid biopsy test to diagnose and locate gastrointestinal cancers.
Authors: Wang Yuying , Zheng Jianchao , Li Zhilong , Jiang Ruijingfang , Peng Jiaxi , Sun Jianlong , Yang Guanghui , Yang Xin-Rong , Huang Ao , Wang Yupeng , Jie Yuan , Liu Xuanhui , Gao Feng , Wu Xiaojian , WANG Dansong , Wu Wenchuan , Lou Wenhui , Zhou Jian , Fan Jia
Published: May 2020

1557

Background: Cancers of the gastrointestinal (GI) system, including esophagus, stomach, pancreas, gallbladder, liver, bile duct, colon, and rectum are estimated to account for 38% of all cancer incidences and nearly 46% of cancer-related deaths in China. We conducted a multi-center study to evaluate the feasibility of using genetic and epigenetic abnormalities in plasma cfDNA to diagnose and locate GI cancers. Methods: We performed parallel genetic and epigenetic profiling of plasma cfDNA from hepatocellular carcinoma (HCC), colorectal cancer (CRC) and pancreatic cancer (PC) patients as well as age-matched healthy individuals by ultra-deep sequencing targeting cancer driver genes, and by targeted bisulfite sequencing covering genome-wide CpG islands, shelves, and shores. Results: Using a pre-specified mutation scoring system, we found that cfDNA mutation profiling achieved a sensitivity of 59.6%, 67.2%, and 46.8% for detecting HCC (n = 322), CRC (n = 244) and PC (n = 141) respectively, with a specificity of 95% in healthy controls (n = 207). For 901 plasma cfDNA samples that underwent methylome profiling, we first applied a machine learning approach to classify each cancer type versus healthy controls in the training cohort (HCC: n = 125; CRC: n = 105; PC: n = 97; healthy individuals: n = 84). Random Forest models with 10-fold cross validation achieved an AUC of 0.96±0.04,0.89±0.06, 0.91±0.07 for HCC, CRC, and PC, respectively. Further analyses were performed on the validation cohort, including 172 HCC patients, 162 CRC patients, 60 PC patients, and an independent cohort of healthy individuals (HCC validation: n = 63; HCC independent validation: n = 109; CRC validation: n = 104; CRC external validation: n = 58; PC validation: n = 60; healthy controls: n = 96). The trained model achieved a sensitivity of 83.1% (specificity = 95.8%), 89.5% (specificity = 95.8%), and 76.7% (specificity = 91.7%) for HCC, CRC, and PC, respectively. Using regional methylation markers from diagnostic models for individual cancer types, we built a tissue-of-origin classification model, which achieved a cross-validation accuracy of 83.3% in the training cohort and an accuracy of 80.1% in the validation cohort in assigning correct cancer types. Conclusions: Plasma cfDNA methylome profiling identified effective biomarkers for the detection and tissue-of-origin determination of GI cancers, and outperformed mutation-based detection approach. Therefore, a liquid biopsy test capable of detecting and locating GI cancers is feasible and may serve as a valuable tool for early detection and intervention.
Evaluation of circulating miRNAs for earlier cancer detection through machine-learning expression profiling.
Authors: Hsieh Jason Chia-Hsun , Liao Chun-Ta , Wang Hung-Ming , Lien Ming-Yu , Lin Yung-Chang , Shen Shih-Che , Kang Shih-Ting , Chen Wei-Ming , Hsieh Yi-Shan , Fan Ya-Chun , Yang Eric Pok Eric
Published: May 2020

1559

Background: Earlier cancer diagnosis leads to higher patient survival rate and reduces financial burdens for patients and their families. Over the past five years, liquid biopsy has demonstrated tremendous promise in the early detection of tumor presence. In addition to circulating tumor cells and circulating tumor DNAs, extracellular microRNAs (miRNAs) have also been shown to be promising diagnostic biomarkers. Through machine-learning profiling, we sought to determine whether or not we could use individuals’ miRNA expression to distinguish between healthy subjects and cancer patients. Methods: Blood samples were collected from healthy donors and from patients of various cancer types. Plasma samples were purified within two hours of sample collection, followed by miRNA extraction. After performing reverse transcription of miRNAs into cDNAs, expression analysis of miRNAs was done using a novel multi-gene, amplification-based detection system that simultaneously analyzes over 160 miRNAs. For subsequent data processing, miRNAs without amplification signals across all profiles were first removed, resulting in 135 miRNAs. These 135 resulting miRNAs were then used as features in Support Vector Machine (SVM) to build OncoSweep classifier, a proprietary prediction algorithm for classification of the samples. Ten-fold cross validation was used to evaluate the performance of OncoSweep. Results: 344 healthy donor samples and 417 cancer patient samples were collected for the study. The prediction algorithm, OncoSweep, was derived based on the miRNA expression patterns of the healthy and the patient samples. The algorithm scored an overall accuracy for cancer prediction of 86.47%, with a sensitivity of 91.4%, a specificity of 85%, a PPV of 85% and an NPV of 88.5%. Conclusions: Utilizing machine-learning method of analyzing circulating miRNA expression profiles, the derived algorithm OncoSweep shows significant promise in cancer prediction. Validation is currently being performed in a larger study. We believe circulating miRNAs, through stringent sample processing and machine-learning methodology, are powerful biomarkers for earlier cancer detection.
Development and validation of the PREMMplus clinical prediction model for multigene hereditary cancer risk assessment.
Authors: Yurgelun Matthew B. , Uno Hajime , Furniss C. Sloane , Ukaegbu Chinedu I. , Horiguchi Miki , Chittenden Anu B. , Fehlmann Tara , Yussuf Amal , LaDuca Holly , Garber Judy Ellen , Syngal Sapna
Published: May 2020

1579

Background: Current clinical prediction models provide syndrome-specific numeric estimates of an individual's likelihood of having a specific hereditary cancer syndrome (e.g., PREMM5 for Lynch syndrome; BRCAPRO for BRCA1/2). With the emergence of multigene panel testing (MGPT), there is a need to evaluate individuals' risk of carrying a pathogenic variant in a diverse array of cancer susceptibility genes in parallel. This study’s aim was to develop and validate the PREMMplus clinical prediction model for multigene cancer risk assessment. Methods: PREMMplus was developed in a cohort of 7296 individuals who had undergone germline MGPT at a single center. Logistic regression models were used to examine candidate predictive variables – including age, sex, ethnicity, and personal/family history of cancer – to provide a numeric estimate of an individual’s likelihood of carrying a pathogenic/likely pathogenic germline variant in one of 18 cancer susceptibility genes (11 high- [ APC, BRCA1/2, CDH1, EPCAM, MLH1, MSH2, MSH6, biallelic MUTYH, PMS2, and TP53] and 7 moderate-penetrance [ ATM, CDKN2A, CHEK2, PALB2, PTEN, RAD51C, and RAD51D]). Model performance was validated in an independent dataset of 14845 individuals who had undergone MGPT at a commercial laboratory. Results: Using clinical characteristics, including personal/family history of 18 cancers plus colorectal adenoma burden, PREMMplus demonstrated an excellent ability to predict pathogenic variants in high penetrance genes at 90% sensitivity. PREMMplus had acceptable performance with the addition of 7 moderate penetrance genes. PREMMplus was well-calibrated and demonstrated comparable performance in the external validation dataset. Conclusions: PREMMplus is the first validated risk assessment model to quantify an individual’s likelihood of carrying pathogenic variants in a wide diversity of cancer risk genes, and can be used to select individuals who should undergo MGPT. As expected, PREMMplus’s discriminatory capacity was reduced with the inclusion of moderate penetrance cancer risk genes. [Table: see text]
Using sequential next-generation sequencing assays to identify germline cancer predisposition variants.
Authors: Kraft Ira Lignugaris , Trottier Amy M. , Steinhardt George F. , Niu Nifang , Wanjari Pankhuri , Chen Wenjun , Segal Jeremy , Godley Lucy A.
Published: May 2020

1581

Background: Next-generation sequencing (NGS) increasingly guides clinical care in hematological malignancies by identifying DNA mutations that change dynamically over time. Clinical samples contain variable numbers of malignant and non-malignant cells. So, careful interpretation is required to determine if a particular variant is somatic, germline, or clonal hematopoietic in origin. Methods: The University of Chicago uses a targeted NGS assay of ~1200 genes, reporting 150 as a clinical test. We aimed to identify individuals with hereditary predisposition by detecting persistent variants on sequential assays regardless of disease state. Results: 943 NGS assays from July 2017 – Feb. 2020 on 711 patients [ages 1 mo – 95 yrs, median 65 yrs] were included. 2,320 variants in 33 genes were identified with 144 patients having the same variant identified on more than one assay. Single nucleotide variants (SNVs) with variant allele frequency (VAF) ≥ 0.3 were prioritized. The first candidate gene identified with potential germline SNVs was CSF3R. 28 unique SNVs in CSF3R were found, 14 were confirmed as germline, 6 somatic, and 8 were unconfirmed due to lack of available tissue. At least 2 confirmed germline CSF3R variants were likely deleterious based on functional testing. Sequential SNVs were quantified using the coefficient of variation, characterizing each by change in VAF over time. Using a worst-case-scenario analysis, in which unconfirmed variants were not counted as germline, a computer algorithm was designed to identify potential germline variants (specificity 0.89, PPV 0.75). Via an iterative method, the algorithm compares new assays to a pool of previously reported tests, flagging patients with potential germline mutations so that biopsies may be studied in the lab, records reviewed, and referrals placed to genetic counselors. To date, 61 patients with 89 likely germline variants have been identified. Known hereditary hematological malignancy genes, such as ATM, ASXL1, CHEK2, DDX41, TSC1, and RUNX1, had the most variants identified. Limitations include the challenge in distinguishing variants that do not change over time, reliance on a targeted NGS panel, and normalizing VAF data prior to analysis. Conclusions: These data highlight the utility of NGS of bone marrow and peripheral blood samples to identify patients suspected of having germline DNA variants. In addition to identifying known predisposition syndromes, one may discover new inherited cancer syndromes and help guide clinical practice in real time.
Comparison of genomic instability test scores used for predicting PARP activity in ovarian cancer.
Authors: Timms Kirsten M , Mills Gordon B. , Perry Michael , Gutin Alexander , Lanchbury Jerry , Brown Robert
Published: May 2020

1586

Background: Clinical trials have explored the utility of various genomic instability (GI) scores or gene panels to assess deficiencies in the homologous recombination (HR) DNA repair pathway and support PARP inhibitor use in ovarian cancer; however, these methods of assessing homologous recombination deficiency (HRD) may not be equivalent. The myChoice HRD test is the only analytically and clinically validated, FDA-approved HRD test that includes BRCA1/2 mutation status and three measures of GI. We compared the proportion of patients identified as candidates for PARP inhibitor use by two measures of HRD [percent loss of heterozygosity (%LOH), 11-gene panel] to myChoice HRD. Methods: Whole-genome SNP analysis was used to reconstruct ovarian tumor genomic profiles to calculate the myChoice HRD score and %LOH in 2 cohorts (clinical laboratory cohort, N = 3,278; SCOTROC4 trial, N = 248). Mutation screening for a set of 11 genes in the HR pathway ( ATM, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, MRE11A, NBN, PALB2, RAD51C, RAD51D) was performed for a subset of tumors from the SCOTROC trial (n = 187). Samples were considered positive if the myChoice HRD score was above the threshold (threshold scores of 42 and 33 were assessed), %LOH above the threshold (16%), or a pathogenic variant in one of the 11 HR genes. The correlation between positive results from %LOH and the 11-gene panel were compared to myChoice HRD. Percent positive agreement (PPA) was the proportion of positive test results from myChoice HRD that were also positive by %LOH or the 11-gene panel. Results: The table shows the correlation and PPA between myChoice HRD, %LOH, and the 11-gene panel. Overall, 19%-61% of patients identified as positive by myChoice HRD would have been missed by %LOH or the 11-gene panel in these two cohorts. Conclusions: These data show that HRD tests used in published and ongoing clinical trials are not equivalent, and they should not be considered interchangeable in predicting PARP inhibitor response in clinical practice. [Table: see text]
Effects of initiating in-office germline testing in safety net clinic patients with epithelial ovarian cancer.
Authors: Jordan Scott , Spring Samantha , Schlumbrecht Matthew , Huang Marilyn
Published: May 2020

1588

Background: Germline genetic mutations occur in approximately 25% of women with epithelial ovarian cancers. Recent advances in frontline maintenance therapy for patients with hereditary breast and ovarian cancer syndrome make timely germline testing critical. Adherence to genetic testing remains low (approximately 30% nationally), including at our safety net hospital where germline testing by a genetic counselor was performed in only 38% of patients. After initiating in-office genetic testing, our aim was to compare current patients with historical controls to determine whether this intervention shortened the time to testing and results. Methods: IRB approval was obtained. Patients seen for a diagnosis of epithelial ovarian cancer between 4/1/2018 and 12/31/2019 were identified. Patients with only one visit or those who received testing elsewhere were excluded. Patient and visit data were abstracted for each visit during the study period. Comparison was made between patients treated before (control cohort) and after in-office testing was initiated (intervention cohort) on 5/21/2019. Categorical variables were compared using Chi Squared and Fisher’s Exact test. Mann Whitney U test was used to compare time from first clinic visit to the date of genetic testing and to the reporting of test results in the chart. All tests were two-sided and significance was set at p = 0.05. Results: 74 patients were identified and 504 clinic visits were analyzed. 57 (77%) patients were White Hispanic, 15 (20.3%) were Black, and 2 (2.7%) were White non-Hispanic. 56 (75.7%) underwent germline testing. Overall median time to testing from the first clinic visit was 21.2 weeks, and median time to reporting of results was 37 weeks. Though there was no significant difference in testing rate between the cohorts, the time to the date of genetic testing in the intervention group was approximately one-third as long as in the control group (9.6 vs 32.1 weeks, p < 0.001). Among the 52 patients with reported genetic results, results were recorded in a clinic note at 4.1 weeks from first visit in the intervention group, compared with 28.8 weeks in the control group (p < 0.001). In the intervention group, during clinic visits without genetics performed to date, testing was performed at that visit 25% of the time. Conclusions: By initiating in-office testing, time to testing and receipt of results were meaningfully shortened. Removing delays to test results will greatly improve the ability of our patients to receive potentially life-saving maintenance therapy following front line treatment.
Cancer risk and overall survival in APC I1307K carriers.
Authors: Gruber Stephen B. , Bonner Joseph D , Lejbkowicz Flavio , Schmit Stephanie , Rennert Hedy , Greenson Joel K , Pinchev Mila , Melas Marilena , Moreno Victor , Tomsho Lynn P , Capella Gabriel , Braun Danielle , Smith Sidney A , McDonnell Kevin , Idos Gregory , Rennert Gad
Published: May 2020

1592

Background: The germline variant APC I1307K is one of the most commonly identified pathogenic variants on germline genetic testing panels. The purpose of the Molecular Epidemiology of Colorectal Cancer study was to quantify the risk of colorectal cancer among carriers, characterize the clinical, pathologic, and molecular features of colorectal cancers arising in patients with APC I1307K, and to describe the overall and disease-specific survival of carriers with colorectal cancer. Here, the final results of the Molecular Epidemiology of Colorectal Cancer Study are reported with respect to APC I1307K. Methods: We consented 6,006 incident, pathologically confirmed cases of colorectal adenocarcinoma and 5,023 age, sex, and ethnicity matched controls without colorectal cancer between March 31, 1998 and July 1, 2017 within a geographically defined area of Northern Israel. Comprehensive, in-person epidemiologic interviews were conducted for cases and controls, with uniform histopathologic review, detailed molecular analysis, medical record review and clinical follow-up for up to 21 years. Results: The demographic and clinical features of incident colorectal cancer cases matched the population distribution of colorectal cancer in Israel. APC I1307K was identified in 429 (7.1%) of cases and 201 (4.0%) of controls. The estimated relative risk of colorectal cancer among carriers was 1.89 (95% confidence interval, 1.59 - 2.24), p < 0.0001. The prevalence and odds ratios differed by ethnic group. Homozygous carriers were at especially high risk, with an odds ratio of 3.90 (95% confidence interval 1.11–13.71). APC I1307K carriers were significantly less likely to have microsatellite instable tumors (p = 0.04). Overall survival of APC I1307K carriers was not significantly different than survival of non-carriers, after adjustment for age, stage, sex, ethnicity, and microsatellite instability. Conclusions: APC I1307K is an actionable germline mutation that confers meaningful lifetime risk of colorectal cancer in heterozygous and homozygous carriers. APC I1307K is not an independent prognostic factor for overall survival or disease specific survival and is not associated with the MSI phenotype. Cumulative lifetime risk estimates inform genetic counseling and provide data for policies regarding the timing and frequency of screening and other preventive strategies.
Relative and absolute risk of second primary neoplasms of the central nervous system.
Authors: Liu Elisa , Oh Cheongeun , Sulman Erik P.
Published: May 2020

1593

Background: Cranial radiation is known to increase the relative risk for developing a second primary neoplasm, but existing analyses do not take into account differential survival or follow-up. The absolute risk, or true incidence, of developing a second primary neoplasm in the central nervous system (CNS) is not well characterized. Methods: Patients diagnosed with cancer from between 1976 and 2016 were sampled using the Surveillance, Epidemiology, and End Results (SEER) Program. Relative risks were estimated using standardized incidence ratios (SIRs) and absolute risks were estimated using cumulative incidence (CI) functions with death as a competing risk. Among CNS primaries, comparison groups were matched by age, sex, year of diagnosis, primary histology, and lesion location. Results: Over 3.8 million patient records, including 13,167 second primary CNS tumors, were extracted from SEER. The relative risk of developing a second primary CNS neoplasm is elevated in all patients diagnosed with a CNS primary cancer (SIR = 9.6), but higher in those who received radiation (SIR = 13.1) or chemotherapy (SIR = 12.6). The absolute risk of developing a second primary CNS neoplasm at 25-years is highest in CNS and endocrine cancers (CI 1.0% and 0.50%, respectively). Among long-term ( > 10-year) survivors of CNS primaries, the 25-year CI of a second primary CNS neoplasm was 4.4%. Cranial radiation increased the incidence of second primary tumors in pediatric patients (25-year CI 4.8% vs 1.2%, p = 0.007), but not adults (25-year CI 5.1% vs 4.9%, p = 0.85). Chemotherapy did not increase CI in either pediatric (25-year CI 7.0% vs 5.4%, p = 0.87) or adult (25-year CI 3.6% vs 5.8%, p = 0.11) populations. Meningiomas (39.3% vs 22.0%, p = 1e-6) and glioblastomas (21.1% vs 14.6%, p = 0.03) represent a greater proportion of the second primary CNS tumors in those who received cranial irradiation. Conclusions: The risk of developing a second primary CNS neoplasm is elevated in patients with a prior CNS cancer. Cranial irradiation increased the CI of second primary tumors in pediatric patients but did not affect adult patients. The association between radiation therapy and risk for subsequent cancers may be limited to the pediatric population.
Changes in cancer mortality rates after the adoption of the Affordable Care Act.
Authors: Lee Anna , Shah Kanan , Chino Junzo P. , Chino Fumiko
Published: May 2020

2003

Background: The Affordable Care Act (ACA) was designed to improve health status in the US primarily through improving access to health insurance. As adoption of Medicaid expansion varied at the state level, this study aims to compare cancer mortality rates over time between states who did (EXP) and did not adopt (NonEXP) Medicaid expansion. Methods: Age-adjusted mortality rates per 100,000 were gathered from the National Center for Health Statistics from 1999-2017 to establish trends. Only deaths due to cancer in patients less than 65 were included. Absolute change in cancer mortality was calculated from 2011-2013 and then from 2015-2017 with 2014 as washout year. Changes within subpopulations (gender, race, ethnicity) were also assessed. Mortality changes between EXP and NonEXP groups were via “difference in differences” analysis. Results: Overall age-adjusted cancer mortality in the US fell from 1999-2017 from 66.9 to 48.8 per 100,000. EXP states had higher population (157 vs 118 million) with less black/African Americans (19.2 vs 21.8 million) and more Hispanics (33.0 vs 21.7 million) than NonEXP states (all examples from 2017). The overall age-adjusted cancer mortality was consistently worse in NonEXP states, cancer mortality fell from 64.7 to 46.0 per 100,000 in EXP states and from 69.0 to 51.9 per 100,000 in NonEXP states from 1999-2017 (both trends p < 0.001, comparison p < 0.001). Comparing the mortality changes in the peri-ACA years (2011-2013 vs 2015-2017) between the 2 cohorts, the difference in differences between EXP and NonEXP states was -1.1 and -0.6 per 100,000 respectively (p = 0.006 EXP, p = 0.14 NonEXP). The estimated overall cancer mortality benefit gained in EXP states after Medicaid expansion (∆∆∆) is -0.5 per 100,000 (p = NS). In EXP states, this translates to an estimated 785 less cancer deaths in 2017. Age-adjusted cancer mortality per 100,000 was worse in NonEXP states for black patients (58.5 EXP vs 63.4 NonEXP in 2017) however there was no differential mortality benefit after ACA expansion when comparing between the peri-ACA years. Of the subpopulations assessed, Hispanics in EXP states had the highest differential cancer mortality benefit at -2.1 per 100,000 (p = 0.07). Conclusions: This is the first study to show a directly measured cancer survival benefit from the ACA on a national scale using a comprehensive database. Hispanic populations appear to have the highest differential cancer mortality benefit after Medicaid expansion. Further study is needed to elucidate why other populations like black patients did not appear to reap the same mortality decrease.
Prospective study of an AI enabled online intervention to increase delivery of guideline compliant cancer care, on the ground.
Authors: Pramesh C S. , Sirohi Bhawna , Nag Shona Milon , Gupta Sudeep , Anderson Benjamin O. , Feldman Nancy Renee , Thaker Premal H. , Beriwal Sushil , Badwe Rajendra A.
Published: May 2020

2011

Background: Despite survival benefits of guideline compliant cancer care, under treatment and over treatment are prevalent. Navya is an AI enabled online intervention that matches a patient’s medical record with NCCN and NCG guidelines (National Cancer Grid, India) and layers live multidisciplinary expert review to recommend actionable treatment plans. It was developed to standardize care and mitigate morbidity and mortality, by delivering on-t ime, guideline based expert treatment plans. Methods: From July 2019 to January 2020, all patients who received a Navya treatment plan based on guidelines and live expert review were included. Intended treatment plans were prospectively collected from the patient. Compliance of intended plans with NCCN (including Resource Stratified Framework) or NCG was measured. Noncompliant intended plans were categorized as overtreatment or undertreatment. After delivery of Navya plan, prospective phone follow up assessed whether noncompliant intended plans were changed to guideline compliant care. Results: Of 1707 consecutive patients who received a Navya plan, 1549 intended plans were available. Patients were diverse with respect to geographic, socioeconomic, and primary tumor distribution: West of India: 28%, North: 26%, East: 21%, South: 15%, Central: 7%, International: 3%; 35% of patients with income < $300/month; GI: 23%, Breast: 14%, Head & Neck: 11%, Thoracic: 10%. Of the 1549 intended plans, 441 (28.47% (95% CI ± 0.26%)) were not compliant with NCCN or NCG. Undertreatment was 35%, overtreatment 26%, incomplete staging workup 28% and 11% could not be categorized. Of 441 patients with noncompliant intended plans, 80.19% (± 0.97%) shared the Navya plan with their treating oncologists and 50.40% (± 0.88%) changed their intended plan to receive the Navya treatment plan. Intervention with Navya increased on-the -ground guideline compliance by ~15% (from 71.53% ±0.42% to 85.87% ± 1.73%). Conclusions: Guideline compliant care ensures best achievable clinical outcomes with existing therapies. A technological earthshot that significantly increases adoption of guideline based care is the first step towards cancer moonshots.
Mapping PRO-CTCAE responses to clinician-graded adverse events, dose reductions, interruptions, and discontinuations in phase I cancer trials.
Authors: Watson Geoffrey Alan , Veitch Zachary William Neil , Shepshelovich Daniel , Liu Zhihui (Amy) , Spreafico Anna , Abdul Razak Albiruni Ryan , Bedard Philippe L. , Siu Lillian L. , Minasian Lori M. , Hansen Aaron Richard
Published: May 2020

2014

Background: Typically symptomatic adverse events (sy-AEs) on clinical trials are reported by clinicians using the CTCAE. To complement clinician collected sy-AEs and understand tolerability better, the patient report outcome version of the CTCAE (PRO-CTCAE) has been developed to provide the patient (pt) perspective on severity of AEs (graded scale 0-4) and their interference in daily life (scale 0-4). The aim of this study was to correlate PRO responses with the grade (G) of AEs, dose interruptions/reductions and dose limiting toxicities (DLTs). Methods: Pts enrolled on phase 1 clinical trials at Princess Margaret were surveyed electronically on tablet using the full library of items for PRO-CTCAE. The PRO-CTCAE was administered at baseline (prior to therapy), mid-cycle 1, and mid-cycle 2. AEs on study were recorded by physicians using the CTCAE. The electronic medical records were analyzed for an association between reported sy-AEs and PRO score. Summary statistics were used to describe patient and disease characteristics, as well as the outcomes. Spearman’s method was used to correlate PRO severity and interference responses. Logistic regression was used to assess which factors were associated with CTCAE G 3-4 vs G 2 AEs. Results: We analyzed 158 pts: median age 60yrs, 77 (49%) were male; all were ECOG ≤1 and 22, 55 and 81 pts completed 1, 2 and 3 surveys, respectively. Clinician reported G2, 3 and 4 sy-AEs occurred in 81, 47 and 3 pts, respectively and all of these were related to a PRO item except 5% (4/81), 9% (4/47) and 33% (1/3), respectively because either the AE occurred after 3rd time point or patient not able to complete the PRO (encephalitis). Sy-AEs causing dose interruptions, reductions, DLTs and discontinuations occurred in 45 (28%), 12 (7.5%), 5 (3%) and 12 (7.5%) pts, respectively; with a corresponding PRO item in 40 (89%), 12 (100%), 4 (80%) and 11(92%) pts, respectively. For patients who had CTCAE G2, G3/4 AEs, interruptions and discontinuations, their severity and inference levels were positively correlated (coefficient 0.49, p < 0.001; 0.45, p < 0.001 0.59, p < 0.001, 0.86, p < 0.001). Dose interruptions (p = 0.0027) and reductions (p = 0.0061) were significantly associated with G3-4 compared to G2 AEs. Conclusions: This is the first time an association between PRO-CTCAE severity and interference; and CTCAE G2, 3, 4 AEs, dose interruptions and discontinuations has been demonstrated. Additional modelling and more patient data are being analyzed to explore the relationship.
Post-hoc power of clinical trials supporting anticancer drug approval by FDA.
Authors: Nadler Michelle , Desnoyers Alexandra , Saleh Ramy , Amir Eitan
Published: May 2020

2018

Background: Regulatory approval of drugs is based typically on randomized control trials (RCTs) observing statistically significant superiority of an experimental agent over a prior standard. Statistical significance can result from large effect size and/or over-sampling (as a result of large sample size or long follow-up). Here we explore the source(s) of statistically significant results in trials supporting anti-cancer drug approval by the FDA. Methods: We searched Drugs@FDA to identify anti-cancer drug approvals for solid tumors (excluding lymphoma) from 2015-2019. We retrieved corresponding manuscripts and associated appendices and extracted data on study characteristics, statistical plan, primary outcomes and accrual and follow-up times. Post-hoc power was calculated based on observed results and was compared to expected effect size and power in the statistical plan. We explored associations with higher than expected power resulting from over-sampling using binary logistic regression. Results: We identified 75 unique drug-approvals reporting 94 endpoints. The most common tumour types were lung, breast, melanoma, and renal cell carcinoma. The most common endpoints were progression free survival and overall survival (OS). In 74 endpoints (79%), observed power was greater than expected power. The magnitude of higher than expected power ranged from 0.1 to > 20%. Of these, 59 (80%) had an effect size greater than predicted in the statistical plan. In 44/74 over-powered endpoints (60%), post-trial power was 100%. When post-hoc power was calculated based on expected effect size rather than observed effect size, 50 endpoints (85%) remained over-powered. Higher than expected power resulting from over-sampling was associated with OS compared to other endpoints (OR 3.03), with targeted agents compared to immunotherapy (OR 1.63) and inversely associated with year of approval (OR 0.57). Conclusions: Most cancer drug approvals result from statistically significant studies which are over-powered due to greater than anticipated effect size. Approximately 1 in 5 studies are over-powered likely due to over-sampling. In this setting, benefit observed in RCTs may not translate to the real-world setting.
Evaluating barriers to uptake of comprehensive genomic profiling (CGP) in advanced cancer patients (pts).
Authors: Smith Kortnye Maureen , O Haire Sophie , Khuong-Quang Dong Anh , Markman Ben , Gan Hui Kong , Ekert Paul G , O'Byrne Kenneth John , Millward Michael , Solomon Benjamin J. , Tran Ben , Scott Clare L. , Kee Damien , McArthur Grant A. , Fellowes Andrew , Weerasuriya Rona , Lynch Elly , Martyn Melissa , Gaff Clara , Fox Stephen B. , Desai Jayesh
Published: May 2020

2033

Background: Despite increasing evidence of benefit supporting CGP in personalizing cancer therapy, its widespread uptake remains limited. Barriers include low patient understanding, unmet patient expectations related to low utility, clinician concerns over cost-effectiveness, perceived value, and discomfort in management of complex genomic results. Methods: This prospective cross-institutional demonstration study was designed to evaluate implementation of CGP in the care of adult and paediatric advanced cancer pts, incorporating pt reported outcomes (PROMs), discrete choice experiment (DCE), ongoing process optimization and clinician evaluations. DNA sequencing of FFPE tumor and matched blood was completed with CGP (PMCC Comprehensive Cancer Panel; 391 genes) via central laboratory. A tumor board reported results weekly with emphasis on therapeutic relevance. Oncologists performed consent and results delivery. Pts completed pre-and post-test surveys, including validated and study-specific questions, DCE and if eligible, semi-structured interviews. Qualitative interviews were undertaken with study clinicians and laboratory staff to evaluate processes. Results: 86% (315) of 365 enrolled pts had successful CGP; of these 63% (199) had relevant therapeutic, diagnostic or germline results. 50 (16%) had treatment change at 6m, 49 (16%) had germline mutations. 293 (88% of adult pts) completed PROMs. 17 of 19 clinicians/laboratory staff approached consented to an interview. At consent pts cited multifaceted value in testing, showed good understanding of basic concepts, but most (69%) overestimated the likelihood of result-led change. Post-test pts remained consistently satisfied with accessing CGP; valuing research contribution, taking opportunities and information for family. 21% struggled with understanding results but there were low levels of decisional regret following participation (89% had nil/mild regret). Pt-elicited preferences (via DCE) indicated priority for high rates of clinical utility and timeliness. Clinicians sited collaboration and communication as critical to delivery of CGP. Conclusions: Pts undergoing CGP are generally satisfied, and derive value on its use beyond potential therapeutic benefit. Our results suggest that to improve test utility and delivery of CGP with value to pts and investing institution, focus must be placed on addressing the additional barriers to its wider implications including efforts to improve process efficiencies, clinician genomic literacy and decision-making support.
Dynamic 30-day readmission prediction for cancer patients via clinical embeddings.
Authors: Wong Chi Wah , Chen Chen , Rossi Lorenzo A. , Wang Jerry , Abila Monga , Munu Janet , Eftekhari Zahra
Published: May 2020

2040

Background: Existing models typically predict unplanned 30-day readmission for cancer patients at discharge1. Performing prediction dynamically during hospital stay may allow earlier intervention for high risk patients. In addition, readmission risk may be associated with the outcome of a variety of labs and diagnoses. Models including all those elements may not be practical due to large number of variables relative to number of samples. Embeddings have the potential to represent medical concepts in low dimensional spaces2. In this study, we developed a machine learning model utilizing embedding representations of ICD and LOINC codes to dynamically predict readmission risk. Methods: This is a single institutional study examining inpatient 30-day unplanned readmissions from Jan 2013 to Dec 2016 (n = 16361 total, n = 5685 in hematology). The readmission rate was 18% (24% for hematology). We used gradient boosted trees models with 10-fold cross validation and included baseline factors that are typically available shortly after admission: gender, age, service, admission count within 6 months, insurance, emergency admission, admission year, allogeneic or autologous stem cell transplant (hematology only). For dynamic factors, we randomly selected a timepoint (TP, median = 2.4 days) during each visit. We utilized publicly available clinical embeddings2 to generate 300 dimensional representations for ICD9s and LOINCs in the patients’ Electronic Medical Records. We considered diagnoses (ICD9) between 6 months prior to admission and TP, and lab tests (LOINC) ordered between admission time and TP. We used records from Jan 2017 to Dec 2017 for prospective validation (n = 3785 total, n = 1424 in hematology), with 17% readmission rate (22% for hematology). Results: Prospective validation Area Under Receiver Operating Characteristic Curve (AUC) using baseline factors were 0.72 (average precision “AP” = 0.33) and 0.65 (AP = 0.32) for overall and hematology populations, respectively. By including dynamic factors, we obtained AUCs of 0.74 (AP = 0.4) and 0.7 (AP = 0.39) for overall and hematology populations, corresponding to 3% and 8% AUC (21% and 22% AP) improvements, respectively. Conclusions: We found that dynamic readmission prediction utilizing clinical embeddings improves the prediction performance comparing with using baseline factors only. The model shows potential to improve patient care and reduce costs by predicting and preventing readmissions when the patient is still in the hospital. 1 J Surg Oncol 2018; 117:1113-1118. 2 AMIA Jt Summits Transl Sci Proc. 2016;41-50.
Prediction of mental health disorder onset and impact on emergency visits following a cancer diagnosis.
Authors: Chen William , Boreta Lauren , Braunstein Steve E. , Hong Julian C.
Published: May 2020

2041

Background: Cancer patients are at increased risk of mental and emotional distress. The aim of this study is to investigate risk factors and timing of mental health disorder (MHD) onset following a cancer diagnosis, and evaluate its impact on emergency visits. Methods: All patients with a new onset diagnosis of malignancy ( ICD-10 codes C00-C97, with conversion of ICD-9 codes) were identified from an institutional de-identified electronic health data warehouse. Demographic data, Charlson comorbidity index excluding cancer, mortality, and time to onset of a new MHD diagnosis ( ICD-10 codes F00-F99) and emergency visits were extracted and used to calculate rates and Cox-model hazard ratios. A predictive logistic model of MHD was tested on an internal hold-out sample (25%). Results: A total of 110,306 patients with 338,208 person-years of follow up were identified with a new diagnosis of cancer from February 1980 to July 2019, of which 95,474 (86.5%) had no prior diagnosis of MHD. Actuarial rates of new MHD among previously MHD-free patients were 8.1% at 6 months, and 14.1% and 20.8% at 2 and 5 years. Median time to onset of MHD was fastest among head and neck cancer (57 days, HR 2.32 [2.1-2.6]), urinary organ cancer (94 days, HR 2.21 [2.0-2.4]), and lung and thoracic cancers (99 days, HR 2.47 [2.2-2.7]), compared to skin neoplasms (987 days, HR 1.0). Median time to onset was less than one year for all malignancies except for skin neoplasms and male genital cancers (840 days). Male sex, older age, Charlson score, divorce or legal separation, self-identification of a gender-neutral partner, African American or American Indian race, Hispanic ethnicity, current or former smoking status, and self-identification as Christian were associated with higher risk of MHD onset, while married status and native Hawaiian or Pacific Islander race were protective. A logistic model predicted new MHD with an AUROC of 0.72. Onset of new MHD was associated with greater rates of emergency visit (HR 1.92 [1.8-2.0], adjusted for cancer type and Charlson score), and patients with new MHD who experienced an emergency visit had a mean of 3.75+/-0.03 (SEM) total emergency visits versus 2.65+/-0.02 (p < 0.0001). Finally, onset of new MHD was associated with greater mortality even after adjusting for age, Charlson score and cancer type (HR 1.29, [1.23-1.35]). Conclusions: Onset of new mental health diagnosis after a cancer diagnosis was correlated with greater rates of emergency visits and mortality. Cancer patients with risk factors identified here may benefit from increased social and mental health support.