Impact of luteinizing hormone suppression on hematopoietic recovery after intensive chemotherapy in patients with leukemia.

Treatment of acute leukemia with intensive chemotherapy leads to an increased risk of myelosuppression. Luteinizing hormone (LH) blockade improves hematopoietic recovery in mice after radiation or chemotherapy, through protection of the hematopoietic stem cells which express the LH receptor. We hypothesized that LH blockade improves hematopoietic recovery following intensive chemotherapy in patients with leukemia. We conducted a retrospective analysis on pre-menopausal women with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) who received intensive chemotherapy and leuprolide given for abnormal uterine bleeding prevention or treatment. Given that leuprolide was more commonly administered in younger patients, we performed propensity score matching between the leuprolide (AML N=64; ALL N=49) and control groups (AML N=128; ALL N=98 patients). Patients with AML who received leuprolide had an additional increase of 13.8 x 109/L/year in their platelet count, and a 0.19 x 109/L/year increase in their lymphocyte count after chemotherapy compared to control (P=0.02; P=0.03 respectively). Those with ALL who received leuprolide had an additional increase of 0.37 x 109/L/year in their absolute neutrophil count (P=0.02). In AML, leuprolide was associated with higher long-term hemoglobin levels (P.

Prevalence and risk factors for bleeding in hereditary hemorrhagic telangiectasia: a National Inpatient Sample study.

Hereditary hemorrhagic telangiectasia (HHT) is a common bleeding disorder, but little is known regarding prevalence and risk factors for bleeding. Adult discharges with HHT and bleeding were identified by International Classification of Disease, 10th edition (ICD-10) codes in the National Inpatient Sample (NIS), 2016-2018. Prevalence estimates were weighted using NIS discharge-level weights to reflect national estimates. Risk factors for bleeding were determined by weighted multivariable logistic regression. Among 18 170 849 discharges, 2528 (0.01%) had HHT, of whom 648 (25.6%) had bleeding. Arteriovenous malformation (AVM) (31.9% vs 1.3%), angiodysplasia (23.5% vs 2.3%), telangiectasia (2.3% vs 0.2%), and epistaxis (17.9% vs 0.6%) were more common in HHT than in non-HHT patients (non-HHT), each P < .001. In contrast, menstrual (HMB) and postpartum bleeding (PPH) were less common in reproductive-age HHT than non-HHT, each P < .001. Anemia associated with iron deficiency (IDA), was equally common in HHT with or without bleeding (15.7% vs 16.0%), but more common than in non-HHT (7.5%), P < .001. Comorbidities, including gastroesophageal reflux (25.9% vs 20.0%) and cirrhosis (10.0% vs 3.6%) were greater in HHT than non-HHT, each P < .001. In multivariable logistic regression, peptic ulcer disease (OR, 8.86; P < .001), portal vein thrombosis (OR, 3.68; P = .006), and hepatitis C, (OR, 2.13; P = .017) were significantly associated with bleeding in HHT. In conclusion, AVM and angiodysplasia are more common and HMB and PPH less common in patients in those with HHT than non-HHT. IDA deficiency is as common in HHT with and without bleeding, suggesting ongoing blood loss and need for universal iron screening.

Patient characteristics predicting prolonged length of hospital stay following robotic-assisted radical prostatectomy.

Objective: The objective of this study is to determine the preoperative patient characteristics predicting prolonged length of hospital stay (pLOS) following robotic-assisted radical prostatectomy (RARP). Methods: The National Surgical Quality Improvement Program (NSQIP) database was used to select patients who underwent RARP without other concomitant surgeries between 2008 and 2016. Patients' demographics, comorbidities, and laboratory markers were collected to evaluate their role in predicting pLOS. The pLOS was defined as length of stay (LOS) >2 days. A multinomial logistic regression was constructed adjusting for postoperative surgical complications to assess for the predictors of pLOS. Results: We obtained data for 31,253 patients of which 20,774 (66.5%) patients stayed ⩽1 day, 6993 (22.4%) patients stayed for 2 days, and 3486 (11.2%) patients stayed for >2 days. Demographic variables - including body mass index (BMI) <18.5: odds ratio (OR) = 2.8, 95% confidence interval (CI) = [1.7-4.8]; smoking: OR = 1.2, 95% CI = [1.1-1.4]; and dependent functional status: OR = 3.1, 95% CI = [1.6-6.0] - were predictors of pLOS. Comorbidities - such as heart failure: OR = 4.6, 95% CI = [2.0-10.8]; being dialysis dependent: OR = 2.7, 95% CI = [1.4-5.0]; and predisposition to bleeding: OR = 2.0, 95% CI = [1.5-2.7] - were the strongest predictors of extended hospitalization. In addition, pLOS was more likely to be associated with postoperative bleeding, renal, or pulmonary complications. Conclusion: Preoperative patient characteristics and comorbidities can predict pLOS. These findings can be used preoperatively for risk assessment and patient counseling.

Calibration-free NGS quantitation of mutations below 0.01% VAF.

Quantitation of rare somatic mutations is essential for basic research and translational clinical applications including minimal residual disease (MRD) detection. Though unique molecular identifier (UMI) has suppressed errors for rare mutation detection, the sequencing depth requirement is high. Here, we present Quantitative Blocker Displacement Amplification (QBDA) which integrates sequence-selective variant enrichment into UMI quantitation for accurate quantitation of mutations below 0.01% VAF at only 23,000X depth. Using a panel of 20 genes recurrently altered in acute myeloid leukemia, we demonstrate quantitation of various mutations including single base substitutions and indels down to 0.001% VAF at a single locus with less than 4 million sequencing reads, allowing sensitive MRD detection in patients during complete remission. In a pan-cancer panel and a melanoma hotspot panel, we detect mutations down to 0.1% VAF using only 1 million reads. QBDA provides a convenient and versatile method for sensitive mutation quantitation using low-depth sequencing.

Predictors of outcomes in adults with acute myeloid leukemia and KMT2A rearrangements.

Acute myeloid leukemia (AML) with rearrangement of the lysine methyltransferase 2a gene (KMT2Ar) has adverse outcomes. However, reports on the prognostic impact of various translocations causing KMT2Ar are conflicting. Less is known about associated mutations and their prognostic impact. In a retrospective analysis, we identified 172 adult patients with KMT2Ar AML and compared them to 522 age-matched patients with diploid AML. KMT2Ar AML had fewer mutations, most commonly affecting RAS and FLT3 without significant impact on prognosis, except for patients with ≥2 mutations with lower overall survival (OS). KMT2Ar AML had worse outcomes compared with diploid AML when newly diagnosed and at relapse, especially following second salvage (median OS of 2.4 vs 4.8 months, P < 0.0001). Therapy-related KMT2Ar AML (t-AML) had worse outcomes compared with de novo KMT2Ar AML (median OS of 0.7 years vs 1.4 years, P < 0.0001). Allogeneic hematopoietic stem cell transplant (allo-HSCT) in first remission was associated with improved OS (5-year, 52 vs 14% for no allo-HSCT, P < 0.0001). In a multivariate analysis, translocation subtypes causing KMT2Ar did not predict survival, unlike age and allo-HSCT. In conclusion, KMT2Ar was associated with adverse outcomes regardless of translocation subtype. Therefore, AML risk stratification guidelines should include all KMT2Ar as adverse.

Nucleophosmin 1 Mutations in Acute Myeloid Leukemia.

Nucleophosmin (NPM1) is a ubiquitously expressed nucleolar protein involved in ribosome biogenesis, the maintenance of genomic integrity and the regulation of the ARF-p53 tumor-suppressor pathway among multiple other functions. Mutations in the corresponding gene cause a cytoplasmic dislocation of the NPM1 protein. These mutations are unique to acute myeloid leukemia (AML), a disease characterized by clonal expansion, impaired differentiation and the proliferation of myeloid cells in the bone marrow. Despite our improved understanding of NPM1 mutations and their consequences, the underlying leukemia pathogenesis is still unclear. Recent studies that focused on dysregulated gene expression in AML with mutated NPM1 have shed more light into these mechanisms. In this article, we review the current evidence on normal functions of NPM1 and aberrant functioning in AML, and highlight investigational strategies targeting these mutations.

Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter.

Background Since the beginning of the coronavirus disease 2019 (COVID-19) epidemic, misinformation has been spreading uninhibited over traditional and social media at a rapid pace. We sought to analyze the magnitude of misinformation that is being spread on Twitter (Twitter, Inc., San Francisco, CA) regarding the coronavirus epidemic.  Materials and methods We conducted a search on Twitter using 14 different trending hashtags and keywords related to the COVID-19 epidemic. We then summarized and assessed individual tweets for misinformation in comparison to verified and peer-reviewed resources. Descriptive statistics were used to compare terms and hashtags, and to identify individual tweets and account characteristics. Results The study included 673 tweets. Most tweets were posted by informal individuals/groups (66%), and 129 (19.2%) belonged to verified Twitter accounts. The majority of included tweets contained serious content (91.2%); 548 tweets (81.4%) included genuine information pertaining to the COVID-19 epidemic. Around 70% of the tweets tackled medical/public health information, while the others were pertaining to sociopolitical and financial factors. In total, 153 tweets (24.8%) included misinformation, and 107 (17.4%) included unverifiable information regarding the COVID-19 epidemic. The rate of misinformation was higher among informal individual/group accounts (33.8%, p: <0.001). Tweets from unverified Twitter accounts contained more misinformation (31.0% vs 12.6% for verified accounts, p: <0.001). Tweets from healthcare/public health accounts had the lowest rate of unverifiable information (12.3%, p: 0.04). The number of likes and retweets per tweet was not associated with a difference in either false or unverifiable content. The keyword "COVID-19" had the lowest rate of misinformation and unverifiable information, while the keywords "#2019_ncov" and "Corona" were associated with the highest amount of misinformation and unverifiable content respectively. Conclusions Medical misinformation and unverifiable content pertaining to the global COVID-19 epidemic are being propagated at an alarming rate on social media. We provide an early quantification of the magnitude of misinformation spread and highlight the importance of early interventions in order to curb this phenomenon that endangers public safety at a time when awareness and appropriate preventive actions are paramount.