Danaparoid cross-reactivity with heparin-induced thrombocytopenia antibodies: report of 12 cases.

PURPOSE: Danaparoid is a safe and effective drug for the treatment of heparin-induced thrombocytopenia (HIT). We describe an uncommon complication: danaparoid cross-reactivity with HIT antibodies. DESIGN AND SETTING: A retrospective observational multicenter study on HIT was conducted in France. In this study concerning HIT patients treated with lepirudin, 12 patients were treated with lepirudin because danaparoid cross-reacted with the heparin-dependent antibodies. RESULTS: Three groups of situations can be separated. In a first group, four patients received a short course of danaparoid until their initial functional HIT assay showed a cross-reactivity between danaparoid and HIT antibodies. One patient presented a fatal thrombotic complication but the relationship between this thrombotic complication and danaparoid cross-reactivity cannot be certain. In a second group, four patients received for 4 days at least a danaparoid treatment while the initial functional test did not show any danaparoid cross-reactivity. During danaparoid treatment, no significant increase of platelet count was observed and two patients presented a fatal thrombotic complication. In a third group, cross-reactivity between danaparoid and HIT antibodies was not checked before danaparoid therapy. During danaparoid treatment, no significant increase of platelet count was observed and the four patients developed a venous thromboembolic complication. CONCLUSION: Absence of any increase in platelet count after 3 to 5 days of danaparoid therapy and/or the occurrence of a new thrombotic event should lead to danaparoid cross-reactivity suspicion. However, before attributing thrombotic complications to danaparoid cross-reactivity, it is crucial to verify that the patients received the recommended danaparoid dosage regimen

Untreated 24-h intraocular pressures measured with Goldmann applanation tonometry vs nighttime supine pressures with Perkins applanation tonometry

AIMS: To compare supine nighttime intraocular pressure measurements with Perkins applanation tonometry to 24-h sitting intraocular pressures with Goldmann applanation tonometry. METHODS: A prospective, untreated, uncontrolled, observational cohort of qualified consecutive ocular hypertensive or primary open-angle glaucoma patients. Patients underwent sitting intraocular pressure measurements over 24-h by Goldmann and patients had their supine nighttime intraocular pressure measurements by Perkins. RESULTS: In 100 completed patients, the mean intraocular pressure at 1000, 2200, 0200 and 0600 hours while sitting was 22.5+/-3.7 mm Hg, and in the supine position, 23.5+/-4.3 mm Hg (P<0.001). The mean sitting Goldmann intraocular pressures across the three daytime points was 23.3+/-3.4 mm Hg and across three nighttime points was 21.5+/-4.0 mm Hg (P<0.001). In contrast, the mean daytime sitting Goldmann intraocular pressure was not different than the mean nighttime supine intraocular pressure evaluated with Perkins (22.8+/-4.4 mm Hg, P=0.07). However, only 70% of patients were within 1.0 mm Hg of the highest daytime reading for all nighttime supine and sitting intraocular pressures. CONCLUSION: This study suggests that with Perkins applanation tonometry the untreated mean supine intraocular pressures are not higher at night than daytime sitting Goldmann applanation tonometry. However, the highest daytime sitting intraocular pressure measurement does not consistently predict the highest nighttime sitting or supine intraocular pressure valu

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Background: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.</p

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Background Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.Genome Instability and Cance

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

BACKGROUND: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. METHODS: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. RESULTS: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. CONCLUSIONS: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility