Myriad Genetics, Inc. · Companion diagnostic · Companion diagnostic
olaparib is a companion diagnostic developed by Myriad Genetics, Inc.. It is approved for therapeutic indications via others.
| Brand Names | myChoice CDx |
| Company | Myriad Genetics, Inc. |
| Drug Class | Companion diagnostic |
| Route | Others |
| Status | Approved |
olaparib is developed for 1 unique indication across 1 therapeutic area.
| Therapeutic Area | Condition | Phase |
|---|---|---|
| Neoplasms benign, malignant and unspecified (incl cysts and polyps) | Uterine cancer | ✓ Approved |
Jie Zhuye Z, Liang Weiting W, Ding Qiuxia Q, Liu Xiaomin X et al.
Zhao Miaomiao M, Hu Qiuxiang Q, Wang Qing Q, Cha Xinlang X et al.
WHO reports that only 54% of tuberculosis (TB) patients received rapid diagnostic tests at their initial presentation. Conventional laboratory methods in TB detection have high specificity (>90%) but low sensitivity (<50%). This means a large number of tuberculosis patients are missed. A better diagnostic approach is essential to decrease the TB burden. Studies on multi-indicator blood-based models for rapid TB diagnosis remain limited. We developed a rapid, non-sputum-based model to improve the efficiency of TB diagnosis. This was a retrospective case-control study including 301 patients with active tuberculosis (ATB) and 191 patients with other pulmonary diseases (OPD) who were evaluated at the Department of Pulmonary Medicine of the Affiliated Infectious Diseases Hospital of Soochow University between May 2023 and May 2024. A composite clinical diagnosis served as the gold standard for ATB diagnosis, including either a clinical diagnosis or bacteriological confirmation. The diagnostic outcome of ATB (ATB vs OPD) was defined as the dependent variable, while guanylate-binding protein 5 (GBP5) expression levels and routine laboratory indicators (including blood cell counts and plasma protein measurements) were defined as independent variables. Univariate and multivariate logistic regression analyses were performed to identify key predictors, and an AdaBoost algorithm was used to construct a TB diagnostic model. The performance of the model was compared with traditional laboratory-based TB tests. DeLong's Test was used to evaluate the statistical difference of AUC between AdaBoost and traditional methods. Through univariate and multivariate logistic regression analyses, the GBP5 gene, white blood cell (WBC) count, platelet (PLT) count, and prothrombin time (PT) were selected to construct an ATB diagnosis model using the AdaBoost algorithm. The AdaBoost model achieved an AUC of 0.808 in the training set and 0.805 in the test set, while the AUC of smear microscopy, MTB culture, Xpert MTB/RIF, and IGRA were 0.67, 0.59, 0.63 and 0.75 respectively. Therefore, our model demonstrated better diagnostic performance than conventional methods. This study preliminarily demonstrates that our AdaBoost diagnostic model based on GBP5 gene expression and routine blood indicators could serve as a potential tool for the clinical diagnosis of ATB. However, to be applied to the clinic, large samples are needed to validate the performance of the model.
Yılmaz Ercan E, Özer Nezihe Koker NK, Topal Erdem E
Cicek Sevil S, Kapudere Bilge B, Kaya Parspancı Yasemin Beyza YB, Tavukcuoglu Zehra Z et al.
Gu Jiawei J, Shao Jie J
Delgado Anna Falk AF, Fällmar David D, Martin Heather H, Mazya Michael V MV et al.
Intracranial venous thrombosis encompasses diverse etiologies with clinical presentations ranging from an incidental finding to coma and death. Despite potentially devastating consequences, venous thrombosis is frequently overlooked by radiologists due to its predominantly extraaxial location close to the skull and clinical emphasis on arterial imaging evaluation in acute stroke management. This educational review addresses common and uncommon presentations across all anatomical locations of intracranial venous thrombosis, providing practical pearls and pitfalls for diagnostic interpretation. We review the imaging modalities CT and MRI, together with their venographic techniques, correlating imaging findings with anatomical location, thrombus age and signal evolution, complications, and underlying causes. Critical interpretive pitfalls are highlighted with strategies to avoid misdiagnosis. The review also emphasizes the important yet underrecognized association between intracranial pressure disorders and venous thrombosis, providing radiologists with a practical framework for improved diagnostic accuracy. KEY POINTS: Question How can radiologists systematically recognize intracranial venous thrombosis across all anatomical locations and avoid the diagnostic pitfalls that lead to clinically significant missed diagnoses? Findings Location-specific imaging patterns, thrombus signal evolution, and recognition of common mimics such as arachnoid granulations enable accurate detection using combined non-contrast and venographic sequences. Critical relevance statement By organizing intracranial venous thrombosis imaging anatomically and pairing each location with its specific mimics and pitfalls, this review equips radiologists with a practical framework to improve detection accuracy and prevent clinically significant missed diagnoses.
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