25 research outputs found

    A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

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    BACKGROUND: In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without; ii) subjects with two different cancers; iii) subjects with two different types of one cancer; and iv) subjects with same cancer resulting in differential time to metastasis. RESULTS: Our algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed. CONCLUSION: The proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states

    Phase Ib/II study combining tosedostat with capecitabine in patients with advanced pancreatic adenocarcinoma

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    Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with limited therapeutic options. We evaluated the safety and efficacy of the aminopeptidase inhibitor tosedostat with capecitabine in advanced PDAC. Methods: We conducted a phase Ib/II trial of tosedostat with capecitabine as second-line therapy for advanced PDAC. Planned enrollment was 36 patients. Eligible patients were treated with capecitabine 1,000 mg/m Results: Sixteen patients were enrolled. Tosedostat 120 mg oral twice daily with capecitabine 1,000 mg/m Conclusions: Tosedostat with capecitabine displayed tolerable toxicity, and prolonged disease control in a subset of patients. These data encourage further exploration of aminopeptidase inhibitors in pancreatic cancer

    Pacritinib to inhibit JAK/STAT signaling in refractory metastatic colon and rectal cancer

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    Background: Treatment options for patients with refractory colorectal cancer are limited and typically provide a chance of only modest benefit. The goal of this study was to evaluate the benefit of inhibiting the JAK/STAT inflammatory pathway with single agent pacritinib in patients with metastatic refractory colorectal adenocarcinoma. Methods: A single arm institutional trial was initiated and enrolled patients with metastatic colorectal cancer refractory to at least two standard lines of treatment. Pacritinib 400 mg daily was administered orally continuously in 28 day cycles. Results: The trial was discontinued prior to reaching the planned accrual due to an FDA hold on pacritinib and a lack of treatment benefit. Eleven patients were enrolled and seven were evaluated for response. Median baseline C-reactive protein level was 12.1 (2.1-147) mg/L. One patient had stable disease at eight weeks by RECIST criteria and six progressed. There were no grade 4 or 5 adverse events while patients were on study. The grade 2 and lower AE events experienced were consistent with prior pacritinib trials. Conclusions: In seven evaluable patients there were no objective responses. The trial was discontinued prior to completing planned accrual based on a low likelihood that the progression free survival goal of 4 months would be met

    Phase 1b trial of anti-VEGF/PDGFR vorolanib combined with immune checkpoint inhibitors in patients with advanced solid tumors

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    PURPOSE: Vorolanib is a multi-target tyrosine kinase inhibitor with anti-angiogenic properties. This study aimed to evaluate the tolerability, safety and efficacy of vorolanib when added to checkpoint inhibitors (CPIs) in patients with advanced solid tumors. METHODS: We conducted a phase 1b study of vorolanib (300 or 400 mg orally once daily) plus pembrolizumab or nivolumab using a standard 3 + 3 design to determine the dose-limiting toxicity (DLT), maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D). The endpoints included safety, toxicity and objective response rate, according to Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST 1.1). RESULTS: Sixteen patients (9 in pembrolizumab arm, 7 in nivolumab arm) with gastrointestinal or lung cancers were enrolled. All patients had at least 1 treatment-related adverse event (TRAE). The most common TRAEs across all cohorts were lymphopenia (n = 7), leukopenia (n = 5), fatigue (n = 5), and alanine aminotransferase elevation (n = 5); most toxicities were grade (G) 1-2. DLTs were reported in 3 patients at vorolanib 400 mg dose level, with G3 aspartate aminotransferase elevation, G3 rectal hemorrhage, and G3 rash. Of 13 total response-evaluable patients, 2 patients had confirmed partial responses (1 rectal squamous cell cancer and 1 small cell lung cancer). Two patients achieved prolonged stable disease. Vorolanib 300 mg daily was determined to be the RP2D for either pembrolizumab or nivolumab. CONCLUSION: Combination vorolanib 300 mg orally once daily plus CPI appears to be a feasible regimen with manageable toxicity and promising efficacy in select tumor types. NCT03511222. Date of Registration: April 18, 2018

    The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

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    Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe
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