Real-world study of adverse events associated with triptan use in migraine treatment based on the U.S. Food and Drug Administration (FDA) adverse event reporting system (FAERS) database.

Triptans selectively agoniste 5-Hydroxytryptamine(5-HT) receptors and are widely used in the treatment of migraine. Nevertheless, there is a dearth of comprehensive real-world clinical research on the safety of triptans. In light of the growing prevalence of migraine, it is imperative to gain a deeper understanding of the true extent of adverse events (AEs) associated with triptans in the clinical management of migraine. A database query of AEs reported to the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database for triptans was performed using the online platform Open Vigil 2.1. The query spanned the period from 1 January 2018 to 31 December 2023 and extracted all AEs for 'sumatriptan', 'zolmitriptan', 'rizatriptan', and 'naratriptan' from the 15-49 years old population and retrospective quantitative analyses. A proportional reporting ratio (PRR), reporting odds ratio (ROR), and Bayesian Confidence Propagation Neural Network (BCPNN) methodology were utilized to contrast AEs across the four triptans. A total of 1.272 AEs reports for sumatriptan, 114 for zolmitriptan, 162 for rizatriptan, and 15 for naratriptan were identified. The ratio of females to males was approximately three times higher in all cases, with the highest number of reports originating from the Americas. A review of the FAERS database revealed that nervous system disorders were the primary SOC category for four drugs, with all four drugs exhibiting the AE indicative of reversible cerebral vasoconstriction syndrome, also classified as Nervous system disorders. The most frequently reported AE signal for sumatriptan was dyspnea, which is classified as respiratory, thoracic and mediastinal disorders. The most frequently reported AEs signals for the remaining three drugs were nausea, vomiting and terminal ileitis, all of which are classified as gastrointestinal disorders. Analyses have demonstrated that AEs are present in a range of systems, including cardiac, nervous, gastrointestinal, and musculoskeletal disorders. It should be noted, however, that the incidence and signal intensity of these AEs vary depending on the specific drug in question. In clinical practice, the selection of an appropriate drug and the monitoring of AEs should be tailored to the individual patient's and specific characteristics.

Liu WH ，Hu HM ，Li C ，Shi Q ，Liu CH ，Liu AX ，Li YF ，Zhang Y ，Mao P ，Fan BF ... -  《-》

Cardiovascular adverse events associated with triptans for treatment of migraine: a pharmacovigilance study of the FDA adverse event reporting system (FAERS).

Sharma P ，Varghese Gupta S ，Bhatt P ，Kandukuru A ，Cheng F ，Upadhyay G ，Sutariya V ... -  《-》

The drug risks of cilostazol: A pharmacovigilance study of FDA Adverse Event Reporting System database.

Cilostazol is indicated for alleviating intermittent claudication (IC) in stable-phase peripheral arterial disease (PAD) patients. Conducting data mining on adverse events (AEs) of cilostazol in the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database to explore its potential medication risks and advance more rational and secure clinical medication practices. This study utilized the Open Vigil 2.1-MedDRA tool to retrieve and extract AE reporting data related to cilostazol from the FAERS database spanning the first quarter of 2004 to the first quarter of 2024. The primary methodology employed was the application of the reporting odds ratio (ROR) method to detect risk signals associated with AEs of cilostazol. A total of 2,130 AE reports involving cilostazol were identified as the primary suspect drug, with a total of 7,134 AEs reported. These reports were predominantly concentrated among patients aged 60 and above, with a higher occurrence in males compared to females. Japan ranked first among the reporting countries, and the majority of reports were submitted by healthcare professionals. Through the screening of cilostazol, a total of 323 positive risk signals for AEs were identified, encompassing 23 system organ classes (SOCs). A comparison with the existing cilostazol product label revealed 8 AEs that were not included based on the number of AE reports, and 19 AEs that were not included based on the strength of the risk signals. Cilostazol exhibited positive risk signals for AEs primarily affecting 8 organ systems based on the SOC classification. Among these, cardiac disorders ranked highest, with a total of 53 positive risk signals for cardiovascular-related AEs identified. In terms of the number of reports, cardiac failure ranked first, aligning with the black box warning issued by the FDA regarding cilostazol. The occurrence of adverse reactions related to cilostazol is primarily concentrated within the first month of treatment. However, a certain proportion of adverse reactions have been reported to occur after long-term use (exceeding 360 days) of cilostazol therapy. Our results have further enriched the observations from existing clinical and real-world studies, uncovering new AE signals for cilostazol, including fall, cerebral infarction, pneumonia, loss of consciousness, acute kidney injury, renal impairment, renal failure, cardiac vein perforation, basal ganglia haematoma, cerebral hyperperfusion syndrome, et al. This study also highlights the significant impact of cilostazol on the cardiovascular system, necessitating close attention to potential cardiovascular toxicities. In addition to focusing on the short-term adverse reactions following cilostazol administration, thorough research into its long-term safety profile is also imperative. This study provides recommendations and guidance for the rational and safe clinical use of cilostazol. In the future, prospective studies are needed to explore the occurrence of related AEs further.

Peng L ，Li X ，Li J ，Liu S ，Liang G ... -  《PLoS One》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Lamotrigine versus levetiracetam or zonisamide for focal epilepsy and valproate versus levetiracetam for generalised and unclassified epilepsy: two SANAD II non-inferiority RCTs.

Marson AG ，Burnside G ，Appleton R ，Smith D ，Leach JP ，Sills G ，Tudur-Smith C ，Plumpton CO ，Hughes DA ，Williamson PR ，Baker G ，Balabanova S ，Taylor C ，Brown R ，Hindley D ，Howell S ，Maguire M ，Mohanraj R ，Smith PE ... -  《-》