Calcium score of the entire thoracic aorta is an independent predictor of all-cause mortality in patients referred to chest computed tomography.

BACKGROUND: Thoracic arterial calcifications (TAC) are not routinely reported or quantified in chest CT scans. We aimed to evaluate the association between TAC of the entire thoracic aorta and all-cause mortality (ACM) in patients referred to standard chest CT. METHODS: A retrospective analysis of consecutive standard chest CT scans (non-gated, non-contrast) for the quantification of TAC, CAC and aortic valve calcification. TAC was divided into 4 sample-derived categories (TAC 1 = 0, TAC 2 = 1-65, TAC 3 = 66-439 and TAC 4 ≥ 440). Data regarding ACM was retrieved from the health care provider database. Multivariate Cox proportional regression models were used to assess associations between the TAC categories and ACM. RESULTS: The study cohort included 415 patients (mean age 67 years, 52% male); 107 ACM events were recorded during a median follow-up of 9 years (inter-quartile range: 7.4-10.4). The rate of ACM was 13%, 25%, 32%, 41% according to TAC category (p < 0.001). The highest TAC category (≥ 440) was a strong and independent predictor of ACM [HR = 1.69 (1.13-2.52; 0.01)] in multivariate analysis. Other independent predictors of ACM included age [HR = 1.07 (1.04-1.10; p < 0.001)], male sex [HR = 2.27 (1.49-3.46; 0.001)] and malignancy [HR = 2.21 (1.49-3.23; < 0.001)]. CONCLUSIONS: Severe TAC (≥ 440) was found to be an independent predictor of ACM. Thus, we suggest that documenting and quantifying TAC should be routinely incorporated into standard chest CT reports.

Cancer Risk in Patients with Gaucher Disease Using Real-World Data.

The association between GD and cancer has been uncertain due to ascertainment bias in previously published studies. We analyzed cancer incidence using the Maccabi Healthcare Service (MHS) electronic health records among 264 patients with GD compared to 3440 matched controls. We ascertained cancers diagnosed before and after the index date (i.e., the first documentation of GD in cases and the corresponding date for controls). Before the index date, cancers were diagnosed in 18 individuals, with 11 (4.2%) in the GD group and 7 (0.2%) in the control group. After the index date, cancers were diagnosed in 57 individuals, with 20 (7.9%) in the GD group and 37 (1.1%) in the control group, with a median follow-up of almost 13 years in both groups. The most common cancers diagnosed in GD were non-melanoma skin cancer (NMSC) and hematological malignancies, with a clustering of diagnoses around the time of GD diagnosis. The incidence of cancers (excluding MNSC) was 4.1 (95% CI 2.2-7.1) and 0.7 (95% CI 0.4-0.9) per 1000 patient-years in the GD and control groups, respectively, with an incidence rate ratio of 6.37 (95% CI 3-12.7). Patients with GD underwent more cancer screening tests than their counterparts in the control group. While our study revealed an increased occurrence of cancers in patients with GD, this finding might be partly attributed to the more rigorous surveillance procedures employed in this patient population.

The Association Between Depression and Invasive and In-situ Cervical Tumors: A Large Population Based Cohort Study.

BACKGROUND: Depression has been shown to be associated with cervical tumors (CTs), an association mostly demonstrated in studies in which temporality could not have been ascertained. OBJECTIVES: To study the association between depression and CTs and the influence of co-morbidities of this association in a large cohort study. METHODS: A retrospective computer-based cohort study was conducted. The cohort included 357,450 female members of Maccabi Healthcare Services. The cohort was classified as depressed or non-depressed using the International Classification of Diseases 9/10 codes. For each subgroup, demographic characteristics, behavioral characteristics, co-morbidities, and CTs diagnosis were obtained. The burden of co-morbidities was defined as the sum of major co-morbidities. We used zero-inflated negative binomial regression analysis due to over-dispersion to estimate the relative risk (RR) for CTs with 95% confidence interval (95%CI). RESULTS: Depression was diagnosed in 15,789 women. Among this group, CTs were diagnosed in 1585 (10.0%). Among the 341,661 non-depressed, CTs were diagnosed in 4185 (1.2%). After adjustment to age and socioeconomic status, the association between depression and CTs was RR=9.2 (95%CI 8.7-9.9, P-value < 0.0001). The association between depression and CTs increased as the burden of clinical conditions increased (P-value < 0.0001). CONCLUSIONS: Women with depression are at a higher risk for CTs, especially among those who have several co-morbidities. Tighter gynecology surveillance is crucial among these women.

Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment.

Breast cancer (BC) risk models based on electronic health records (EHR) can assist physicians in estimating the probability of an individual with certain risk factors to develop BC in the future. In this retrospective study, we used clinical data combined with machine learning tools to assess the utility of a personalized BC risk model on 13,786 Israeli and 1,695 American women who underwent screening mammography in the years 2012-2018 and 2008-2018, respectively. Clinical features were extracted from EHR, personal questionnaires, and past radiologists' reports. Using a set of 1,547 features, the predictive ability for BC within 12 months was measured in both datasets and in sub-cohorts of interest. Our results highlight the improved performance of our model over previous established BC risk models, their ultimate potential for risk-based screening policies on first time patients and novel clinically relevant risk factors that can compensate for the absence of imaging history information.

Shifting from vitamin K antagonists to non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation: predictors, patterns and temporal trends.

BACKGROUND: Non-Vitamin K antagonist oral anticoagulants (NOACs) emerged as an alternative with comparable or superior efficacy and safety to vitamin K antagonists (VKAs) for stroke prevention in patients with non-valvular atrial fibrillation (AF). OBJECTIVES: The aim of the current study was to investigate the patterns, predictors, timelines and temporal trends of shifting from VKAs to NOACs. METHODS: In this retrospective observational study, the computerized database of a large healthcare provider in Israel, Maccabi Healthcare Services, was searched to identify patients with AF for whom either a VKA or NOAC was prescribed between 2012 and 2015. Time from diagnosis to therapy initiation and to shifting between therapies was evaluated. RESULTS: Out of 6987 eligible AF incident patients, 2338 (33.4%) initiated treatment with a VKA and 2221 (31.7%) with a NOAC. In addition, 5259 prevalent patients were analyzed. During the study period, NOAC prescriptions proportion among the newly diagnosed cases increased from 32 to 68.4% (p for trend <  0.001). The median time from diagnosis to first dispensing was greater in NOAC than VKA and decreased among patients treated with NOAC during the study period (2012: 1.9 and 0.3 months, 2015: 0.7 and 0.2 months, respectively). During follow-up, 3737 (49%) patients (54.3% and 47.1% of the incident and prevalent cases, respectively), shifted from a VKA to a NOAC, after a median of 22 months and 39 months in the incident and prevalent cases, respectively, decreasing throughout the study period. Female gender, younger age, southern district, higher CHADS2 and CHA2DS2-VASC score, non-smoking, and treatment with antiplatelets were associated with a greater likelihood for therapy shift. Shifting from a NOAC to a VKA decreased over time from 8 to 4.5% in 2012 to 0.5% and 0.7% in 2015 in the incident and prevalent groups, p <  0.001 respectively. CONCLUSIONS: Shifting from VKA to NOAC occurred in 50% of the cases, more frequently among incident cases, and younger patients with greater stroke risk. Shifting from a NOAC to a VKA was much less frequent, yet it occurred more often in incident cases and decreased over time. A socially and economically sensitive program to optimize the initiation of OAC therapy upon diagnosis is warranted.

Real-world study of PD-L1 testing patterns and treatment distribution in patients with metastatic non-small-cell lung cancer in Israel.

Aim: We describe PD-L1 testing patterns and first-line treatment for patients with metastatic non-small-cell lung cancer in a 2.3 million-member state-mandated health service in Israel. Materials & methods: Newly diagnosed stage IV non-small-cell lung cancer patients initiating systemic anticancer treatment from 1 January 2017 until 31 December 2018 were identified from the national cancer registry and Maccabi Healthcare Service database and followed until 30 June 2019. Results: The cohort consisted of 410 patients; 58% males, median age 68 years, 70% current/former smokers, 81% adenocarcinoma, 14% had brain metastases, and Eastern Cooperative Oncology Group performance status was 46/17/37% for 0-1/2-4/unknown, respectively. A total of 80% tested for PD-L1 expression, of which 47% had tumor proportion score (TPS) ≥ 50%. A total of 95% with TPS ≥ 50% and no known tumor aberrations (including EGFR mutations, and translocations in ALK and ROS1) received first-line PD-1/PD-L1-inhibitor monotherapy, and 80% of untested/TPS < 50% received platinum doublets. Conclusion: Fast uptake of testing was observed, and treatment patterns showed high adherence to guidelines.

Lay abstract We describe PD-L1 testing patterns in a cohort of 410 patients with stage IV non-small-cell lung cancer. All patients were newly diagnosed and newly treated in the years 2017 and 2018. In this cohort, 58% were males, average age was 68 years and 70% were current or former smokers. In this, 80% were tested for PD-L1 expression and 95% of those with a tumor score of >50% and no other tumor receptor mutations received first-line PD-1/PD-L1-inhibitor monotherapy (most receiving pembrolizumab). Moreover, 80% of those untested for PD-L1 or with a low tumor proportion score (<50%) received chemotherapy. After introduction in 2017, a fast uptake of PD-L1 testing was observed, and treatment patterns showed high adherence to guidelines.

Real World Analysis of Small Cell Lung Cancer Patients: Prognostic Factors and Treatment Outcomes.

In this observational study, we assessed treatment patterns and prognostic factors in patients with small cell lung cancer (SCLC) in a large state-mandated healthcare organization in Israel. Methods: All incident cases with histologically confirmed SCLC who initiated systemic anti-cancer treatment between 2011 and 2017 were identified. Treatment patterns and overall survival (OS) were evaluated for each line of therapy. Results: A total of 235 patients were identified (61% male, median age 64 years, 95% ever smokers, 64% had extensive stage). The first-line treatment was platinum-etoposide regimen for 98.7% of the cohort. The second and third-line regimen were given to 43% and 12% of patients, respectively. Mean OS for extensive and limited stage patients was 9.1 and 23.5 months respectively. In a multivariable model, increased risk for mortality was observed among patients with an ECOG performance status (PS) of 2 compared to a PS of 0-1 for the extensive stage patients (Hazard ratio (HR) = 1.63, 95% confidence ratios (CI): 1.00-2.65); and for males compared to females for the limited stage patients (HR = 2.17; 95% CI: 1.12-4.20). Regarding all 2nd line patients in a multivariable model incorporating relevant confounding factors, demonstrated a significantly better outcome with platinum-based regimens compared to topotecan. Median survival after initiation of 2nd line in platinum-sensitive patients was longer (p = 0.056) for those re-challenged with platinum-based regimen (n = 7): 6.8mo (6.1-not reported (NR)), compared with those switched to a different treatment (n = 27): 4.5 mo (2.6-6.6) for extensive stage patients, and a non-significant difference was also observed for limited stage patients. Conclusion: To our knowledge, this is one of the largest real-world studies of SCLC patients. OS for SCLC patients was similar to that reported in clinical trials. PS for extensive stage patients and sex for limited stage patients were significant correlates of prognosis. Re-challenge of the platinum-based doublet was associated with longer OS compared to switching treatment in extensive stage patients.

The impact of a Facebook campaign among mothers on HPV vaccine uptake among their daughters: A randomized field study.

OBJECTIVE: The popularity of social networks provide an incredible opportunity to enhance the impact of preventive medicine programs. We aimed to assess whether a targeted Facebook campaign among mothers may increase the uptake of human Papilloma virus (HPV) immunization among their 8th-grade daughters. METHODS: This field study was conducted among the members of a state-mandated health organization in Israel. Included were all 21,592 members who were mothers to 14 year-old daughters in the 2018-19 school-year. A total of 17,271 (80%) were randomly allocated to the campaign arm and the rest (n=4,321) were selected as a reference group. The Facebook ads addressed issues and concerns regarding HPV-related diseases and HPV vaccine. Main outcome measures were Facebook metrics on exposure to campaign and HPV immunization among eighth grade daughters of the study participants. RESULTS: Between 8/2018-10/2018, Facebook ads were shown 1.8-million times (a reach of 88%). The uptake of HPV vaccine among daughters of women allocated to the campaign arm (55.3%) was similar (p = 0.749) to 55.0% in the control group. The only significant differences between study groups were observed when stratifying by SES level. In the lowest SES quartile, Facebook campaign significantly (p = .02) reduced vaccine uptake (35% vs. 39.0%), with a relative risk of 0.90 (95%CI: 0.82-0.98), while in the second SES quartile, Facebook campaign increased vaccine uptake from 52.6% to 55.8%, with a RR of 1.06 (95%CI,1.00-1.12). Among mothers in higher SES levels, daughters of exposed and unexposed mothers had similar immunization rates. CONCLUSIONS: Facebook campaign may increase the uptake of HPV vaccine among daughters to mothers of medium-to-low SES level, but it may reduce vaccination among lower SES groups.

Epidemiology, longitudinal treatment patterns and outcomes of chronic lymphocytic leukemia in Israel.

This study aims to describe chronic lymphocytic leukemia (CLL) epidemiology, treatment patterns and outcomes in a 2.3-million-member healthcare provider database (Maccabi Healthcare Services, Israel). Newly-diagnosed CLL patients (1999-2017) were followed through 31/3/2018. A total of 1857 newly-diagnosed CLL patients were included. Annual incidence was 5.82 per 100,000 population. Median overall survival (OS) was 12.7 (95%CI: 11.8-13.5) years since diagnosis. Approximately 1/3 initiated treatment within 5 y. A statistical trend (p = 0.066) for improved OS over time was observed among younger patients (age <70 y) treated in 2009-2017 vs. 1999-2008). Among patients treated since 2009 (n = 411; median age = 68y), fludarabine-cyclophosphamide-rituximab (FCR), bendamustine-rituximab and obinutuzumab ± chlorambucil accounted for 19.5%, 12.2% and 11.4% of first line, respectively. Median (95%CI) time to next treatment and OS were 3.1(2.6-3.6) and 7.0(6.3-7.7) years, respectively. CLL incidence in Israel is comparable to developed countries. Real-world data suggest a trend of improved survival over the last decade among patients treated before age 70.

An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.

BACKGROUND: There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We report here on a blinded clinical validation study and deployment of an artificial intelligence (AI)-based algorithm in a pathology laboratory for routine clinical use to aid prostate diagnosis. METHODS: An AI-based algorithm was developed using haematoxylin and eosin (H&E)-stained slides of prostate CNBs digitised with a Philips scanner, which were divided into training (1 357 480 image patches from 549 H&E-stained slides) and internal test (2501 H&E-stained slides) datasets. The algorithm provided slide-level scores for probability of cancer, Gleason score 7-10 (vs Gleason score 6 or atypical small acinar proliferation [ASAP]), Gleason pattern 5, and perineural invasion and calculation of cancer percentage present in CNB material. The algorithm was subsequently validated on an external dataset of 100 consecutive cases (1627 H&E-stained slides) digitised on an Aperio AT2 scanner. In addition, the AI tool was implemented in a pathology laboratory within routine clinical workflow as a second read system to review all prostate CNBs. Algorithm performance was assessed with area under the receiver operating characteristic curve (AUC), specificity, and sensitivity, as well as Pearson's correlation coefficient (Pearson's r) for cancer percentage. FINDINGS: The algorithm achieved an AUC of 0·997 (95% CI 0·995 to 0·998) for cancer detection in the internal test set and 0·991 (0·979 to 1·00) in the external validation set. The AUC for distinguishing between a low-grade (Gleason score 6 or ASAP) and high-grade (Gleason score 7-10) cancer diagnosis was 0·941 (0·905 to 0·977) and the AUC for detecting Gleason pattern 5 was 0·971 (0·943 to 0·998) in the external validation set. Cancer percentage calculated by pathologists and the algorithm showed good agreement (r=0·882, 95% CI 0·834 to 0·915; p<0·0001) with a mean bias of -4·14% (-6·36 to -1·91). The algorithm achieved an AUC of 0·957 (0·930 to 0·985) for perineural invasion. In routine practice, the algorithm was used to assess 11 429 H&E-stained slides pertaining to 941 cases leading to 90 Gleason score 7-10 alerts and 560 cancer alerts. 51 (9%) cancer alerts led to additional cuts or stains being ordered, two (4%) of which led to a third opinion request. We report on the first case of missed cancer that was detected by the algorithm. INTERPRETATION: This study reports the successful development, external clinical validation, and deployment in clinical practice of an AI-based algorithm to accurately detect, grade, and evaluate clinically relevant findings in digitised slides of prostate CNBs. FUNDING: Ibex Medical Analytics.

What Factors Increase the Risk of Complications in SARS-CoV-2-Infected Patients? A Cohort Study in a Nationwide Israeli Health Organization.

BACKGROUND: Reliably identifying patients at increased risk for coronavirus disease (COVID-19) complications could guide clinical decisions, public health policies, and preparedness efforts. Multiple studies have attempted to characterize at-risk patients, using various data sources and methodologies. Most of these studies, however, explored condition-specific patient cohorts (eg, hospitalized patients) or had limited access to patients' medical history, thus, investigating related questions and, potentially, obtaining biased results. OBJECTIVE: This study aimed to identify factors associated with COVID-19 complications from the complete medical records of a nationally representative cohort of patients, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: We studied a cohort of all SARS-CoV-2-positive individuals, confirmed by polymerase chain reaction testing of either nasopharyngeal or saliva samples, in a nationwide health organization (covering 2.3 million individuals) and identified those who suffered from serious complications (ie, experienced moderate or severe symptoms of COVID-19, admitted to the intensive care unit, or died). We then compared the prevalence of pre-existing conditions, extracted from electronic health records, between complicated and noncomplicated COVID-19 patient cohorts to identify the conditions that significantly increase the risk of disease complications, in various age and sex strata. RESULTS: Of the 4353 SARS-CoV-2-positive individuals, 173 (4%) patients suffered from COVID-19 complications (all age ≥18 years). Our analysis suggests that cardiovascular and kidney diseases, obesity, and hypertension are significant risk factors for COVID-19 complications. It also indicates that depression (eg, males ≥65 years: odds ratio [OR] 2.94, 95% CI 1.55-5.58; P=.01) as well as cognitive and neurological disorders (eg, individuals ≥65 years old: OR 2.65, 95% CI 1.69-4.17; P<.001) are significant risk factors. Smoking and presence of respiratory diseases do not significantly increase the risk of complications. CONCLUSIONS: Our analysis agrees with previous studies on multiple risk factors, including hypertension and obesity. It also finds depression as well as cognitive and neurological disorders, but not smoking and respiratory diseases, to be significantly associated with COVID-19 complications. Adjusting existing risk definitions following these observations may improve their accuracy and impact the global pandemic containment and recovery efforts.

Gestational diabetes and long-term risk for dyslipidemia: a population-based historical cohort study.

OBJECTIVES: To assess the course of lipid levels over time in postpartum women according to gestational diabetes status, taking into account potential confounders, such as comorbid conditions and body weight. METHODS: The data for the present analysis were collected from a 2.3 million member integrated care provider in Israel. Included were all female members aged 15-50 years who performed a 50 g glucose challenge test (GCT) between March 1995 and May 2009. We collected all follow-up lipid consecration tests performed from date of delivery following the GCT (index date) until April 2017. Data analysis was performed for each lipid component individually (triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)) and the effects of the several risk factors (history of gestational diabetes mellitus (GDM), age at delivery, obesity status and smoking status) were investigated using general linear model taking into account potential confounders. RESULTS: A total of 160 527 women (6.1 million person-years of actual follow-up) were eligible for the analysis, including 10 234 women with GDM (6.4% of the entire cohort). During the study follow-up period, a total of 2.1 million lipid tests were performed. When adjusting for follow-up time, age at index date, body mass index status, and smoking status, GDM was associated with a 1.8-fold risk (95% CI 1.73 to 1.88) for dyslipidemia defined by TG, 1.45-fold risk (95% CI 1.38 to 1.52) for dyslipidemia defined by LDL-C, and 1.44-fold risk (95% CI 1.39 to 1.50) for dyslipidemia defined by HDL-C. DISCUSSION: The results of this retrospective cohort analysis indicate that gestational diabetes confers added risk for developing hyperlipidemia post partum, particularly dyslipidemia defined by TG, as compared with women with normal glucose tolerance.

Postnatal steroid therapy is associated with autism spectrum disorder in children and adolescents of very low birth weight infants.

BACKGROUND: This study evaluates the association between major neonatal morbidities and autism spectrum disorder (ASD) in children and adolescents born of very low birth weight (VLBW). METHODS: Historical cohort study using the Israel national VLBW infant database linked with the Maccabi Healthcare Services (MHS) medical records. The study cohort comprised 4963 VLBW subjects born from 1999 to 2012, >1 year of age. Multivariable logistic regression analyses were used to assess factors associated with ASD. RESULTS: The diagnosis of ASD was confirmed in 113 children (2.3%). Infants with major neonatal morbidities had higher rates of ASD; however, in the multivariable analyses these were not significantly associated with ASD: severe intraventricular hemorrhage (OR 1.21 [95% CI 0.60-2.45]), post-hemorrhagic hydrocephalus (OR 1.77 [0.73-4.29]), periventricular leukomalacia (OR 1.02 [0.42-2.51]), severe retinopathy of prematurity (OR 1.91 [0.995-3.67]), and bronchopulmonary dysplasia (OR 1.44 [0.84-2.45]). Postnatal steroid therapy when included separately was associated with an OR of 1.97 [1.18-3.29] for ASD. This association remained significant when postnatal steroid therapy was included with each of the neonatal morbidities (ORs ranging from 1.91 to 2.11). CONCLUSIONS: This study suggests a significant association between postnatal steroid therapy and ASD in VLBW infants. This possible association should be considered in future studies evaluating potential risk factors for ASD in preterm infants.

Fracture incidence after denosumab discontinuation: Real-world data from a large healthcare provider.

BACKGROUND: Vertebral fractures (VF) upon Denosumab (DMAB) discontinuation were first described as a distinct phenomenon in 2015, yet the magnitude of this event remains undetermined. OBJECTIVES: To estimate fracture risk after DMAB discontinuation, in a real-world setting. METHODS: The computerized database of a 2.3-million members' state-mandated health organization was utilized to detect osteoporotic patients with at least two DMAB dispenses. Treatment discontinuation was defined as a refill gap of 3 months or more, while the discontinuation date was defined as an anticipated missed purchase date. Fractures were identified by an osteoporosis registry and individually adjudicated by an expert's review. Fractures occurring within one year from discontinuation among DMAB discontinuers (DD) and from the 2nd year of treatment onwards for persistent users (PU) were included. RESULTS: A total of 1500 DD (92% females, mean ±â€¯SD age = 71.8 ±â€¯9.5y), and 1610 PU (91%, 71.7 ±â€¯8.8) were identified. At baseline, the groups were comparable in fracture- history, bisphosphonate exposure, smoking, and bone density. Multiple VF occurred in 12 (0.8%) DD vs. 2 (0.1%) PU (p = 0.006). The overall rate of fractures per 100 patient-years of follow-up was significantly higher in DD than PU (RR 3.2, 95% CI 2.2-4.8), as well as the rate of VF (RR 4.7, 95% CI 2.3-9.6) and multiple VF (RR 14.6, 95% CI 3.3-65.3, effect size 1.06). CONCLUSIONS: Patients who discontinue DMAB are at greater risk of major OP fractures than those who persist with treatment. Same is true for clinical multiple vertebral fractures, yet the incidence of the latter was low. These findings demonstrate a need for greater awareness and thoughtful management of DMAB discontinuation.

Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning.

Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. We aimed to test the utility of machine learning applied to big data in identifying the potential role of concomitant drugs not taken for diabetes which may contribute to lowering blood glucose. Success in controlling blood glucose was defined as achieving HgA1c levels < 6.5% after 90-365 days following diagnosis and initiating treatment. Among numerous concomitant drugs taken by type 2 diabetic patients, alpha 1 (α1)-adrenoceptor antagonist drugs were the only group of medications that significantly improved the success rate of glucose control. Searching the published literature, this effect of α1-adrenoceptor antagonists has been shown in animal models, where this class of medications appears to induce insulin secretion. In conclusion, machine learning of big data is a novel method to identify effective antidiabetic effects for potential repurposable medications already on the market for other indications. Because these α1-adrenoceptor antagonists are widely used in men for treating benign prostate hyperplasia (BPH) at age groups exhibiting increased rates of type 2 diabetes, this finding is of potential clinical significance.

Assisted reproductive technology and the risk of pediatric cancer: A population based study and a systematic review and meta analysis.

BACKGROUND: There is controversy whether exposure to assisted reproductive technology (ART) is associated with increased risk of pediatric cancer. We aimed at calculating the overall risk of pediatric cancers after ART in a large cohort of exposed women; and to conduct a systematic review and meta- analysis of cohort studies examining overall risk of pediatric cancers after ART. METHODS: All children born in Israel who were members of Maccabi Health Services (MHS) between 1999 and 2016 after ART, were linked to the Israeli Registry of Childhood Cancer (IGS) to identify those with cancer diagnosed before 16 years of age. In parallel we conducted a systematic review and meta-analysis of observational cohort studies with more than 5000 ART- exposed cases that measured pediatric cancer after ART. RESULTS: In the cohort study, the risk ratio for pediatric cancer after ART in general was 0.95 (95% CI, 0.76-1.19). The RR was 1.09 (95% CI, 0.79-1.48) for IVF treatments. Meta- analysis of 13 cohort studies with a total of 750,138 women exposed to ART (with 1152 pediatric cancers) and 214,008,000 unexposed controls (with 30,458 pediatric cancers) did not reveal increased risk for pediatric cancers (RR 0.99; 95% CI, 0.85-1.15). CONCLUSIONS: Based on very large numbers, ART in general, and IVF in particular, are not associated with overall increased risk of pediatric cancer.

Real-world epidemiology, treatment patterns and survival of multiple myeloma patients in a large nationwide health plan.

BACKGROUND: Survival of patients with multiple myeloma (MM) has improved significantly with access to autologous stem cell transplant (SCT) and new treatments. This study aims to describe epidemiology, treatment patterns, and outcomes of MM in Israel. METHODS: A retrospective observational study was conducted in Maccabi Healthcare Services, a 2-million-member nationwide health plan in Israel. MM was defined by cross-linking data on MM diagnoses, dispensed treatments, and serum free light-chain assays. Point prevalence (31/12/2016) and incidence (2012-2016) rates were age-standardized. Newly diagnosed and treated patients (2009-2015) were followed through 31/12/2016 for progression to second-line (L2), with death as a competing risk. RESULTS: MM prevalence and incidence rates were 26.2 and 4.6 per 100,000 population, respectively. In the treatment cohort (N = 552), mean ±â€¯SD) age was 65.6 ±â€¯11.3) years (60.1% male) and median (95% CI) OS in years was 5.2 (4.3-6.1) overall and 6.5 (4.9-8.1) for first-line (L1) bortezomib (N = 421). In a multivariable analysis, OS was significantly higher among patients starting L1 in 2012-2015 vs. 2009-2011. Within a year, 38.4% underwent SCT. Cumulative incidence of L2 was 38.2% and 51.4% within 1 and 2 years, respectively, and was associated with older age (≥65y; P < 0.001). CONCLUSION: These results from a large heterogeneous population demonstrate MM incidence and survival rates that are in line with the literature, together with a significant improvement in overall survival over time. Approximately half of newly treated patients progressed to L2 within two years. These results will serve as a baseline for further research to evaluate the clinical impact of new interventions.

The association between adherence with oral bisphosphonates and the risk of breast cancer in post-menopausal women.

BACKGROUND: Several observational studies have suggested a protective effect of oral bisphosphonates (BP) on the risk of breast cancer, but no such association has been seen in randomized control trials. The role of oral BP in breast cancer prevention remains unclear. AIM: To investigate the association between different levels of BP exposure and breast cancer incidence in a cohort of osteoporotic post-menopausal women. SUBJECTS AND METHODS: This historical prospective study was conducted using the computerized databases of Maccabi Healthcare Services (MHS) in Israel. Included in the study were osteopenic and osteoporotic women aged 55-75 years who started BP therapy between 1998 and 2012. The subjects were enrolled in MHS for at least 3 years before therapy initiation, and had a minimum follow-up of 5 years in MHS. Women with a previous cancer, and women treated with selective estrogen receptor modulators (SERMs) were excluded. BP exposure was expressed in quintiles of proportion of days covered (PDC) with BP during follow-up period and cancer incidence was ascertained by the Israel National Tumor Registry. Person-years of follow-up began on January 1st, 1998 and ended at the date of cancer diagnosis, death, or December 31st, 2012, whichever occurred first. RESULTS: A total of 11,717 patients (mean age = 66.87 ±â€¯4.38) were eligible for the analysis. During a total of 130,252 person-years of follow-up, (mean 7.2 years) 173 incident cases of breast cancer were diagnosed. Compared to women with a PDC with BP of 20% or lower, the adjusted hazard ratio for breast cancer were HR = 0.81 (95%CI: 0.48-1.39), HR = 0.82 (95%CI: 0.50-1.33), HR = 0.72 (95%CI:0.45-1.15) and HR = 1.14 (95%CI:0.76-1.70) among women with 20-40%, 40-60%, 60%-80%, and 80% or higher, PDC, respectively. CONCLUSION: In this study, we did not find a significant association between oral BP therapy for osteoporosis and the risk of breast cancer in postmenopausal women. The discrepancy between our results and the reports of such an association in observational studies might originate from an indication bias.

Clinical pharmacology of old age.

Introduction: With the majority of elderly persons consuming multiple drugs, inappropriate drug use is a major issue in geriatric medicine. Areas covered: We reviewed PubMed, Embase, and Cochrane from inception to 1 May 2019 for potentially inappropriate use of medications, polypharmacy, and age-dependent changes in pharmacokinetics and pharmacodynamics. We selected to highlight new aspects that have emerged in recent years: appropriate monitoring of drug adherence and the introduction of Big Data analysis in advancing geriatric pharmacology. Expert opinion: There are major gaps in the pharmacological treatment of the elderly. Most drugs were designed and tested in adults, with no pharmacokinetic and pharmacodynamic data on changes in old age. This void must be corrected through systematic and well-designed research programs. Potentially inappropriate use of medications (PIM) in the elderly is a serious issue in advanced age. Analysis of PIM shows relatively low predictive value in real life medicine. Most physicians continue to prescribe to the elderly medicines which should not be given at all, or not combined. Polypharmacy is a complex issue in old age, and in many cases treating physicians are not conducting critical assessment of the need for numerous medications.

Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.

Background Computational models on the basis of deep neural networks are increasingly used to analyze health care data. However, the efficacy of traditional computational models in radiology is a matter of debate. Purpose To evaluate the accuracy and efficiency of a combined machine and deep learning approach for early breast cancer detection applied to a linked set of digital mammography images and electronic health records. Materials and Methods In this retrospective study, 52 936 images were collected in 13 234 women who underwent at least one mammogram between 2013 and 2017, and who had health records for at least 1 year before undergoing mammography. The algorithm was trained on 9611 mammograms and health records of women to make two breast cancer predictions: to predict biopsy malignancy and to differentiate normal from abnormal screening examinations. The study estimated the association of features with outcomes by using t test and Fisher exact test. The model comparisons were performed with a 95% confidence interval (CI) or by using the DeLong test. Results The resulting algorithm was validated in 1055 women and tested in 2548 women (mean age, 55 years ± 10 [standard deviation]). In the test set, the algorithm identified 34 of 71 (48%) false-negative findings on mammograms. For the malignancy prediction objective, the algorithm obtained an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI: 0.89, 0.93), with specificity of 77.3% (95% CI: 69.2%, 85.4%) at a sensitivity of 87%. When trained on clinical data alone, the model performed significantly better than the Gail model (AUC, 0.78 vs 0.54, respectively; P < .004). Conclusion The algorithm, which combined machine-learning and deep-learning approaches, can be applied to assess breast cancer at a level comparable to radiologists and has the potential to substantially reduce missed diagnoses of breast cancer. © RSNA, 2019 Online supplemental material is available for this article.