Safety and efficacy of Rucaparib in the treatment of ovarian cancer and patients with BRCA mutation: a systematic review and meta-analysis of phase III randomized clinical trials.

INTRODUCTION: Our systematic review and meta-analysis aimed to evaluate the clinical efficacy and safety of Rucaparib, a PARP inhibitor (PARPi), in patients with ovarian cancer and BRCA mutation. METHODS: Online databases were comprehensively searched for all phase III Randomized trials that used Rucaparib therapy for ovarian cancer patients and patients having BRCA mutation. Efficacy results are progression-free survival and overall response rate in addition to addressing its safety concerns. RESULTS: After pooling data from 4 clinical trials, the analysis showed a significant improvement in PFS among ovarian cancer patients and for the maintenance therapy with a hazard ratio (HR) of 0.49 (95% CI 0.34-0.73, p = 0.0003) and 0.42 (95% CI 0.29-0.62, p < 0.0001), respectively. For patients with BRCA mutations, the PFS showed significant improvement with a (HR) of 0.42 (95% CI 0.25-0.71, p < 0.001). A difference was observed in the risk of grade ≥ 3 TEAEs between the two groups (RR = 2.48; 95% CI 1.40-4.37). CONCLUSION: Rucaparib demonstrated significant efficacy in improving PFS and ORR in ovarian cancer patients, particularly those having BRCA mutations. However, they should be closely monitored due to the greater risk of various adverse effects.

A Scoring Framework and Apparatus for Epilepsy Seizure Detection Using a Wearable Belt.

To develop a wearable device that can detect epilepsy seizures. In particular, due to their prevalence, attention is focused on detecting the generalized tonic-clonic seizure (GTCS) type. When a seizure is detected, an alert phone call is initiated and an alarm SMS sent to the nearest health-care provider (and/or a predesignated family member), including the patient's location as global positioning system (GPS) coordinates. A wearable belt is developed including an Arduino processor that constantly acquires data from four different sensing modalities and monitors the acquired signal patterns for abnormalities. The sensors are a heart rate sensor, electromyography sensor, blood oxygen level (oxygen saturation) sensor, and an accelerometer to detect sudden falls. Higher-than-normal threshold levels are established for each sensor's signal. If two or more signal measurements exceed the corresponding threshold value for a predetermined time interval, then the seizure alarm is triggered. Clinical trials were not pursued in this study as this is the initial phase of system development (phase 0). Instead, the instrumented belt seizure detection prototype was tested on nine healthy individuals mimicking, to some degree, seizure symptoms. A total of eighteen trials took place of which half had <2 sensor thresholds exceeded and no alarm, whereas the other half resulted in activating the alarm when two or more sensor thresholds were exceeded for at least the predetermined time interval corresponding to each of the higher-than-normal sensor readings. For each trial that triggered the alarm when a seizure was detected, the on-board GPS and global system for mobile communication (GSM) units successfully initiated an alert phone call to a predesignated number in addition to sending an SMS message, including GPS location coordinates. Continuous real-time monitoring of signals from the four different sensors allows the developed wearable belt to detect GTCS while reducing false alarms. The proposed device produces an important alarm that may save a patient's life.