41 research outputs found

    Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management : a PIONEER Analysis Based on Big Data

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    Funding statement PIONEER is funded through the IMI2 Joint Undertaking and is listed under grant agreement No. 777492. This joint undertaking receives support from the European Unionā€™s Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations EFPIA. The European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 806968. The Joint Undertaking is supported by the European Unionā€™s Horizon 2020 research and innovation programme and EFPIA, a large association which represents the biopharmaceutical industry in Europe. The views communicated within are those of PIONEER. Neither the IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained hereinPeer reviewe

    Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management:A PIONEER Analysis Based on Big Data

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    Background: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. Objective: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. Design, setting, and participants: From an initial cohort of &gt;100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). Outcome measurements and statistical analysis: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. Results and limitations: The most common comorbidities were hypertension (35ā€“73%), obesity (9.2ā€“54%), and type 2 diabetes (11ā€“28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12ā€“25%) and emergency department visits (10ā€“14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. Conclusions: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. Patient summary: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.</p

    Gleason Grade Group 4 prostate biopsy with no cancer seen on final pathology in the magnetic resonance imaging and Prostate Specific Membrane Antigenā€Positron Emission Tomography era

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    Introduction The absence of prostate cancer on final surgical pathology after biopsyā€proven prostate cancer is a rare finding. Case presentation Case of pT0 prostate cancer following Gleason Grade Group 4 in 1 out of 12 cores from a transrectal ultrasoundā€guided biopsy in a man who underwent both magnetic resonance imaging and 18Fā€PSMAā€1007 Positron Emission Tomography prior to radical prostatectomy. Conclusion pT0 prostate cancer is rare. The use of novel imaging modalities may help in the workup of prostate cancer

    Clinical Characteristics, Management Strategies, and Outcomes of Non-ST-Segment-Elevation Myocardial Infarction Patients With and Without Prior Coronary Artery Bypass Grafting

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    Background There are limited data on the management strategies, temporal trends and clinical outcomes of patients who present with non-ST-segment-elevation myocardial infarction and have a prior history of CABG. Methods and Results We identified 287Ā 658 patients with non-ST-segment-elevation myocardial infarction between 2010 and 2017 in the United Kingdom Myocardial Infarction National Audit Project database. Clinical and outcome data were analyzed by dividing into 2 groups by prior history of coronary artery bypass grafting (CABG): group 1, no prior CABG (n=262Ā 362); and group 2, prior CABG (n=25Ā 296). Patients in group 2 were older, had higher GRACE (Global Registry of Acute Coronary Events) risk scores and burden of comorbid illnesses. More patients underwent coronary angiography (69% versus 63%) and revascularization (53% versus 40%) in group 1 compared with group 2. Adjusted odds of receiving inpatient coronary angiogram (odds ratio [OR], 0.91; 95% CI, 0.88-0.95; P<0.001) and revascularization (OR, 0.73; 95% CI, 0.70-0.76; P<0.001) were lower in group 2 compared with group 1. Following multivariable logistic regression analyses, the OR of in-hospital major adverse cardiovascular events (composite of inpatient death and reinfarction; OR, 0.97; 95% CI, 0.90-1.04; P=0.44), all-cause mortality (OR, 0.96; 95% CI, 0.88-1.04; P=0.31), reinfarction (OR, 1.02; 95% CI, 0.89-1.17; P=0.78), and major bleeding (OR, 1.01; 95% CI, 0.90-1.11; P=0.98) were similar across groups. Lower adjusted risk of inpatient mortality (OR, 0.67; 95% CI, 0.46-0.98; P=0.04) but similar risk of bleeding (OR,1.07; CI, 0.79-1.44; P=0.68) and reinfarction (OR, 1.13; 95% CI, 0.81-1.57; P=0.47) were observed in group 2 patients who underwent percutaneous coronary intervention compared with those managed medically. Conclusions In this national cohort, patients with non-ST-segment-elevation myocardial infarction with prior CABG had a higher risk profile, but similar risk-adjusted in-hospital adverse outcomes compared with patients without prior CABG. Patients with prior CABG who received percutaneous coronary intervention had lower in-hospital mortality compared with those who received medical management

    Semi-automated PIRADS scoring via mpMRI analysis

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    Purpose: Prostate cancer (PCa) is the most common solid organ cancer and second leading cause of death in men. Multiparametric magnetic resonance imaging (mpMRI) enables detection of the most aggressive, clinically significant PCa (csPCa) tumors that require further treatment. A suspicious region of interest (ROI) detected on mpMRI is now assigned a Prostate Imaging-Reporting and Data System (PIRADS) score to standardize interpretation of mpMRI for PCa detection. However, there is significant inter-reader variability among radiologists in PIRADS score assignment and a minimal input semi-automated artificial intelligence (AI) system is proposed to harmonize PIRADS scores with mpMRI data. Approach: The proposed deep learning model (the seed point model) uses a simulated single-click seed point as input to annotate the lesion on mpMRI. This approach is in contrast to typical medical AI-based approaches that require annotation of the complete lesion. The mpMRI data from 617 patients used in this study were prospectively collected at a major tertiary U.S. medical center. The model was trained and validated to classify whether an mpMRI image had a lesion with a PIRADS score greater than or equal to PIRADS 4. Results: The model yielded an average receiver-operator characteristic (ROC) area under the curve (ROC-AUC) of 0.704 over a 10-fold cross-validation, which is significantly higher than the previously published benchmark. Conclusions: The proposed model could aid in PIRADS scoring of mpMRI, providing second reads to promote quality as well as offering expertise in environments that lack a radiologist with training in prostate mpMRI interpretation. The model could help identify tumors with a higher PIRADS for better clinical management and treatment of PCa patients at an early stage
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