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- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 2. |
- Sieberts, SK, et al.
(författare)
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Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis
- 2016
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7, s. 12460-
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Tidskriftsartikel (refereegranskat)abstract
- Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
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| 4. |
- Sahin, O, et al.
(författare)
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International Multi-Specialty Expert Physician Preoperative Identification of Extranodal Extension n Oropharyngeal Cancer Patients using Computed Tomography: Prospective Blinded Human Inter-Observer Performance Evaluation
- 2024
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundExtranodal extension (ENE) is an important adverse prognostic factor in oropharyngeal cancer (OPC) and is often employed in therapeutic decision making. Clinician-based determination of ENE from radiological imaging is a difficult task with high inter-observer variability. However, the role of clinical specialty on the determination of ENE has been unexplored.MethodsPre-therapy computed tomography (CT) images for 24 human papillomavirus-positive (HPV+) OPC patients were selected for the analysis; 6 scans were randomly chosen to be duplicated, resulting in a total of 30 scans of which 21 had pathologically-confirmed ENE. 34 expert clinician annotators, comprised of 11 radiologists, 12 surgeons, and 11 radiation oncologists separately evaluated the 30 CT scans for ENE and noted the presence or absence of specific radiographic criteria and confidence in their prediction. Discriminative performance was measured using accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and Brier score for each physician. Statistical comparisons of discriminative performance were calculated using Mann Whitney U tests. Significant radiographic factors in correct discrimination of ENE status were determined through a logistic regression analysis. Interobserver agreement was measured using Fleiss’ kappa.ResultsThe median accuracy for ENE discrimination across all specialties was 0.57. There were significant differences between radiologists and surgeons for Brier score (0.33 vs. 0.26), radiation oncologists and surgeons for sensitivity (0.48 vs. 0.69), and radiation oncologists and radiologists/surgeons for specificity (0.89 vs. 0.56). There were no significant differences between specialties for accuracy or AUC. Indistinct capsular contour, nodal necrosis, and nodal matting were significant factors in regression analysis. Fleiss’ kappa was less than 0.6 for all the radiographic criteria, regardless of specialty.ConclusionsDetection of ENE in HPV+OPC patients on CT imaging remains a difficult task with high variability, regardless of clinician specialty. Although some differences do exist between the specialists, they are often minimal. Further research in automated analysis of ENE from radiographic images is likely needed.
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| 9. |
- Hemingway, H, et al.
(författare)
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The effectiveness and cost-effectiveness of biomarkers for the prioritisation of patients awaiting coronary revascularisation: a systematic review and decision model.
- 2010
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Ingår i: Health Technology Assessment. - : National Coordinating Centre for Health Technology Assessment. - 1366-5278 .- 2046-4924. ; 14:9, s. 1-178
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To determine the effectiveness and cost-effectiveness of a range of strategies based on conventional clinical information and novel circulating biomarkers for prioritising patients with stable angina awaiting coronary artery bypass grafting (CABG).DATA SOURCES: MEDLINE and EMBASE were searched from 1966 until 30 November 2008.REVIEW METHODS: We carried out systematic reviews and meta-analyses of literature-based estimates of the prognostic effects of circulating biomarkers in stable coronary disease. We assessed five routinely measured biomarkers and the eight emerging (i.e. not currently routinely measured) biomarkers recommended by the European Society of Cardiology Angina guidelines. The cost-effectiveness of prioritising patients on the waiting list for CABG using circulating biomarkers was compared against a range of alternative formal approaches to prioritisation as well as no formal prioritisation. A decision-analytic model was developed to synthesise data on a range of effectiveness, resource use and value parameters necessary to determine cost-effectiveness. A total of seven strategies was evaluated in the final model.RESULTS: We included 390 reports of biomarker effects in our review. The quality of individual study reports was variable, with evidence of small study (publication) bias and incomplete adjustment for simple clinical information such as age, sex, smoking, diabetes and obesity. The risk of cardiovascular events while on the waiting list for CABG was 3 per 10,000 patients per day within the first 90 days (184 events in 9935 patients with a mean of 59 days at risk). Risk factors associated with an increased risk, and included in the basic risk equation, were age, diabetes, heart failure, previous myocardial infarction and involvement of the left main coronary artery or three-vessel disease. The optimal strategy in terms of cost-effectiveness considerations was a prioritisation strategy employing biomarker information. Evaluating shorter maximum waiting times did not alter the conclusion that a prioritisation strategy with a risk score using estimated glomerular filtration rate (eGFR) was cost-effective. These results were robust to most alternative scenarios investigating other sources of uncertainty. However, the cost-effectiveness of the strategy using a risk score with both eGFR and C-reactive protein (CRP) was potentially sensitive to the cost of the CRP test itself (assumed to be 6 pounds in the base-case scenario).CONCLUSIONS: Formally employing more information in the prioritisation of patients awaiting CABG appears to be a cost-effective approach and may result in improved health outcomes. The most robust results relate to a strategy employing a risk score using conventional clinical information together with a single biomarker (eGFR). The additional prognostic information conferred by collecting the more costly novel circulating biomarker CRP, singly or in combination with other biomarkers, in terms of waiting list prioritisation is unlikely to be cost-effective.
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