All-Cause Mortality for Life Insurance Applicants with a History of Breast Cancer.

Breast cancer is the most commonly diagnosed cancer worldwide. Breast cancer is also the second leading cause of cancer death among women in the United States after lung cancer with over 40,000 breast cancer deaths occurring each year. The purpose of this research was to determine the all-cause mortality of applicants diagnosed with breast cancer currently or at some time in the past. Life insurance applicants with reported breast cancer were extracted from data covering United States residents between November 2007 and November 2014. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2007 to 2011 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2007 to 2014 to determine vital status. If there was a death from the other death source, then the SSDMF was searched to verify the death. The study had approximately 561,000 person-years of exposure. Actual-to-expected (A/E) mortality ratios were calculated using the Society of Actuaries 2008 Valuation Basic Table (2008VBT), select and ultimate table (age last birthday) and the 2010 US population as expected mortality ratios. Since the A/Es presented in this paper were known to be an underestimate due to the exclusion of the recent SSDMF deaths, comparative analysis of the mortality ratios was done. Since there was no smoking status information in this study, all expected bases were not smoker distinct. Overall, the 35-44 age group had 6.3 times the relative mortality ratio than those in the 65-75 age group. The relative mortality ratio for the 35-44 age group applicants, when cancer severity was accounted for in combination with 3 or more nodes of cancer involvement, was 29.3 times that when compared to those in the 65-75 age group having localized cancer, where no nodes are involved. The 35-44 age group applicants who were diagnosed with cancer within the last year had over 10-fold increase in relative mortality ratios compared to the 65-75 age group, who were over 10 years from diagnosis. Taking the severity of cancer along with time from diagnosis showed over a 12 times relative mortality ratio between the low rate of over 10 years from diagnosis and localized involvement to those diagnosed within the last year having 3 or more nodes with cancer. Applicant age, time since diagnosis and cancer severity were the most significant variables to predict the relative mortality ratios.

All-Cause Mortality for Life Insurance Applicants with a History of Prostate Cancer.

OBJECTIVE: - To determine the all-cause mortality of life insurance applicants diagnosed with prostate cancer currently or at some time in the past. BACKGROUND: - Prostate cancer is common and a frequent cause of cancer death. Both the frequency of prostate cancer in men and its propensity for causing premature mortality require insurance company medical directors and underwriters to have a good understanding of prostate cancer-related mortality trends, patterns, and outcomes in the insured population. METHODOLOGY: - Life insurance applicants with reported prostate cancer were extracted from data covering United States residents between November 2007 and November 2014. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2007 to 2011 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2007 to 2014 to determine vital status. Actual to Expected (A/E) mortality ratios were calculated using the Society of Actuaries 2015 Valuation Basic Table (2015VBT), select and ultimate table (age last birthday) and the 2013 US population as expected mortality ratios. All expected bases were not smoker distinct. RESULTS: - The study covered applicants between the ages of 45 and 75 and had approximately 405,000 person-years of exposure. Older aged applicants had a lower mortality ratio than those who were younger. Applicants 45 to 54 had the highest mortality ratios in the first year after diagnosis which steadily decreased in years 6 to 10 with an increase in the mortality ratio for those over 10 years from diagnosis. Relative mortality rate was close to unity for those with localized cancer across all age groups. The mortality ratio was 2 to 4 times greater for those with cancer in 1 positive node, and much greater with 3 positive nodes. For each time-from-diagnosis category, the relative mortality ratios compared to age were highest in the 45-54 age group. The A/E mortality ratios based on the 2015VBT were consistently 3 to 4 times that of the mortality ratios based on the 2013 US population. CONCLUSION: - The mortality patterns of insurance applicants with prostate cancer were similar to that observed in individuals with prostate cancer in the general population. Applicant age, time to diagnosis and cancer severity were the most significant variables to predict mortality.

All-Cause Mortality for Diabetics or Individuals with Hyperglycemia Applying for Life Insurance.

Diabetics and individuals with lab results consistent with a diagnosis of diabetes or hyperglycemia were extracted from data covering US residents who applied for life insurance between January 2007 and January 2014. Information about these applicants was matched to the Social Security Death Master File (SSDMF) and another commercially available death source file to determine vital status. Due to the inconsistencies of reporting within the death files, there were two cohorts of death cases, one including the imputed year of birth (full cohort of deaths), and the second where the date of birth was known (reduced cohort of deaths). The study had approximately 8.5 million person-years of exposure. Actual to expected (A/E) mortality ratios were calculated using the Society of Actuaries 2008 Valuation Basic Table (2008VBT) select table, age last birthday and the 2010 US population as expected mortality rates. With the 2008VBT as an expected basis, the overall A/E mortality ratio was 3.15 for the full cohort of deaths and 2.56 for the reduced cohort of deaths. Using the US population as the expected basis, the overall A/E mortality ratio was 0.98 for the full cohort of deaths and 0.79 for the reduced cohort. Since there was no smoking status information in this study, all expected bases were not smoker distinct. A/E mortality ratios varied by disease treatment category and were considerably higher in individuals using insulin. A/E mortality ratios decreased with increasing age and took on a J-shaped distribution with increasing BMI (Body Mass Index). The lowest mortality ratios were observed for overweight and obese individuals. The A/E mortality ratio based on the 2008VBT decreased with the increase in applicant duration, which was defined as the time since initial life insurance application.

Morphotropic phase boundaries in ferromagnets: Tb(1-x)Dy(x)Fe2 alloys.

The structure and properties of the ferromagnet Tb(1-x)Dy(x)Fe(2) are explored through the morphotropic phase boundary (MPB) separating ferroic phases of differing symmetry. Our synchrotron data support a first order structural transition, with a broadening MPB width at higher temperatures. The optimal point for magnetomechanical applications is not centered on the MPB but lies on the rhombohedral side, where the high striction of the rhombohedral majority phase combines with the softened anisotropy of the MPB. We compare our findings with single ion crystal field theory and with ferroelectric MPBs, where the controlling energies are different.

The role of the pharmaceutical industry in meeting the public health threat of antibacterial resistance.

The established market model for pharmaceutical products, as for most other products, is heavily dependent on sales volumes. Thus, it is a primary interest of the producer to sell large quantities. This may be questionable for medicinal products and probably most questionable for antibacterial remedies. For these products, treatment indications are very complex and encompass both potential patient benefits, possible adverse effects in the actual patient and, which is unique for this therapeutic class, consideration about what effects the drug use will have on the future therapeutic value of the drug. This is because bacteria are sure to develop resistance. The European Federation of Pharmaceutical Industries and Associations (EFPIA) agrees with the general description of the antibacterial resistance problem and wants to participate in measures to counteract antibacterial resistance. Stakeholders should forge an alliance that will address the need for and prudent use of new antibiotics. A variety of incentives probably have to be applied, but having all in common that the financial return has to be separated from the use of the product.

Preoperative anemia and transfusion in cardiac surgery: a single-centre retrospective study.

BACKGROUND: Preoperative anemia and transfusion are associated with worse outcomes. This study aims to identify the prevalence of preoperative anemia, transfusion rates on surgery day, and predictors of transfusion in elective cardiac surgery patients at our centre. We also aim to evaluate our preoperative intervention program, and examine the intervention window for anemia before surgery. METHODS: This study included 797 adult patients who underwent elective cardiac surgery at a tertiary hospital. Multivariable logistic regression analysis was used to identify predictors of transfusion on surgery day. RESULTS: Preoperative anemia was present in 15% of patients. Anemic patients had a significantly higher transfusion rate at 53% compared to 10% in non-anemic patients. Hemoglobin concentration, estimated glomerular filtration rate (eGFR), body surface area (BSA), and total cardiopulmonary bypass time were predictive of transfusion on surgery day. Patients had a median of 7 days between initial visit and surgery day, however, referral to the blood conservation clinic was only done for 8% of anemic patients and treatment was initiated in 3% of anemic patients. Among the 3 anemic patients who received treatment, 2 did not require blood transfusion on surgery day. CONCLUSIONS: Preoperative anemia is present in 15% of patients at our centre and these patients have 53% transfusion rates on surgery day. Hemoglobin concentration, eGFR, BSA, and total cardiopulmonary bypass time were predictors of transfusion on surgery day. Patients had a median of 7 days between initial visit and surgery day. Referral and anemia treatment were infrequently initiated in preoperative anemic patient.

Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials.

Clinical trial efficiency, defined as facilitating patient enrollment, and reducing the time to reach safety and efficacy decision points, is a critical driving factor for making improvements in therapeutic development. The present work evaluated a machine learning (ML) approach to improve phase II or proof-of-concept trials designed to address unmet medical needs in treating schizophrenia. Diagnostic data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) trial were used to develop a binary classification ML model predicting individual patient response as either "improvement," defined as greater than 20% reduction in total Positive and Negative Syndrome Scale (PANSS) score, or "no improvement," defined as an inadequate treatment response (<20% reduction in total PANSS). A random forest algorithm performed best relative to other tree-based approaches in model ability to classify patients after 6 months of treatment. Although model ability to identify true positives, a measure of model sensitivity, was poor (<0.2), its specificity, true negative rate, was high (0.948). A second model, adapted from the first, was subsequently applied as a proof-of-concept for the ML approach to supplement trial enrollment by identifying patients not expected to improve based on their baseline diagnostic scores. In three virtual trials applying this screening approach, the percentage of patients predicted to improve ranged from 46% to 48%, consistently approximately double the CATIE response rate of 22%. These results show the promising application of ML to improve clinical trial efficiency and, as such, ML models merit further consideration and development.

Post-injection delirium/sedation syndrome in patients with schizophrenia treated with olanzapine long-acting injection, II: investigations of mechanism.

BACKGROUND: Olanzapine long-acting injection (LAI) is a salt-based depot antipsychotic combining olanzapine and pamoic acid. The slow intramuscular dissolution of this practically insoluble salt produces an extended release of olanzapine lasting up to 4 weeks. However, in a small number of injections (< 0.1%), patients experienced symptoms suggestive of olanzapine overdose, a phenomenon that has been termed "post-injection delirium/sedation syndrome" (PDSS). The authors conducted a series of parallel investigations into the possible reasons PDSS events occur. METHODS: Healthcare providers involved in the PDSS cases were queried for clinical information around the events. Plasma samples from patients experiencing PDSS were collected when possible (12/30 cases) and olanzapine concentrations compared with the known pharmacokinetic profile for olanzapine LAI. Product batches and used vials from the PDSS cases were evaluated for compliance with established manufacturing standards and/or possible user error. Because this depot formulation depends upon slow dissolution at the intramuscular injection site, in-vitro experiments were conducted to assess solubility of olanzapine pamoate in various media. RESULTS: Injection administrators reported no unusual occurrences during the injection. No anomalies were found with the product batches or the remaining suspension in the used vials. Olanzapine concentrations during PDSS events were higher than the expected 5-73 ng/mL range, with concentrations exceeding 100 ng/mL and in some cases reaching >600 ng/mL during the first hours after injection but then returning to the expected therapeutic range within 24 to 72 hours. Solubility and dissolution rate of olanzapine pamoate were also found to be substantially greater in plasma than in other media such as those approximating the environment in muscle tissue. CONCLUSIONS: Manufacturing irregularities, improper drug reconstitution, and inappropriate dosing were ruled out as possible causes of PDSS. In-vitro solubility and in-vivo pharmacokinetic investigations suggest that PDSS is related to exposure of the injected product to a substantial volume of blood. This exposure is most likely the result of unintended partial intravascular injection or blood vessel injury during the injection (occurring even with proper injection technique) with subsequent seepage of the medication into the vasculature, which would produce higher than intended olanzapine concentrations and symptoms consistent with PDSS. TRIAL REGISTRATION: ClinicalTrials.gov ID; URL: http://http//www.clinicaltrials.gov/: NCT00094640, NCT00088478, NCT00088491, NCT00088465, and NCT00320489.

Inhibitory Effects of Probenecid on Pharmacokinetics of Tenofovir Disoproxil Fumarate and Emtricitabine for On-Demand HIV Preexposure Prophylaxis.

In a randomized, crossover pharmacokinetic study in healthy volunteers (N = 14), a single dose of 2 g probenecid (PRO)-boosted 600 mg tenofovir disoproxil fumarate (TDF)/400 mg emtricitabine (FTC) (test (T) +PRO) was compared with the current on-demand HIV preexposure prophylaxis from the IPERGAY study (a 600 mg TDF/400 mg FTC on day 1 and 300 mg TDF/200 mg FTC on days 2 and 3) (control, C IPERGAY). PRO increased mean single-dose area under the plasma concentration-time curve extrapolated to infinity (AUC0-∞,SD ) of tenofovir (TFV) and FTC by 61% and 68%, respectively. The TFV-diphosphate (TFV-DP) concentrations in peripheral blood mononuclear cells were higher (~30%) at 24 hours in T +PRO but then fell significantly lower (~40%) at 72 hours compared with C IPERGAY. The interaction between FTC and PRO was unexpected and novel. Further study is needed to determine if this PRO-boosted TDF/FTC regimen would be clinically effective.

Olanzapine plasma concentrations after treatment with 10, 20, and 40 mg/d in patients with schizophrenia: an analysis of correlations with efficacy, weight gain, and prolactin concentration.

Objectives of the study were to evaluate the relationship between olanzapine plasma concentrations and efficacy, prolactin, and weight and to assess effects of smoking, sex, and race on the pharmacokinetic characteristics of oral olanzapine up to 40 mg/d. Patients were randomly allocated to olanzapine 10, 20, or 40 mg/d for 8 weeks. Olanzapine concentrations in 634 samples from 380 patients were analyzed. Mean sample collection time was approximately 15 hours after dose for all groups. Mean olanzapine concentrations were 19.7 +/- 11.4, 37.9 +/- 22.8, and 74.5 +/- 43.7 ng/mL for 10-, 20-, and 40-mg doses, respectively. Olanzapine concentration and Positive and Negative Syndrome Scale improvement were not significantly correlated. Change in both weight and prolactin showed significant dose response. Prolactin concentration was correlated with olanzapine concentration (r = 0.46, P < 0.001). No significant correlation between olanzapine concentration and weight change was observed. Olanzapine concentrations were lower in self-reported smokers (16.5 +/- 9.6, 34.2 +/- 20.8, and 60.9 +/- 34.6 ng/mL) than in self-reported nonsmokers (25.6 +/- 12.3, 43.4 +/- 24.7, and 113.2 +/- 44.0 ng/mL) for 10-, 20-, and 40-mg doses, respectively (P

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a common complication of type 2 diabetes mellitus (T2DM). A retrospective analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial was intended to identify such factors using ML. The longitudinal data were stratified by time after patient enrollment to differentiate early and late predictors. Our results showed that Random Forest and Simple Logistic Regression methods exhibited the best performance among the evaluated algorithms. Baseline values for glomerular filtration rate (GFR), urinary creatinine, urinary albumin, potassium, cholesterol, low-density lipoprotein, and urinary albumin to creatinine ratio were identified as DN predictors. Early predictors were the baseline values of GFR, systolic blood pressure, as well as fasting plasma glucose (FPG) and potassium at month 4. Changes per year in GFR, FPG, and triglycerides were recognized as predictors of late development. In conclusion, ML-based methods successfully identified predictive factors for DN among patients with T2DM.

Pharmacokinetics of duloxetine in breast milk and plasma of healthy postpartum women.

OBJECTIVE: The purpose of this study was to characterize duloxetine pharmacokinetics in the breast milk and plasma of lactating women and to estimate the duloxetine dose that an infant might consume if breastfed. METHODS: This open-label study included six healthy women aged 22-35 years who stopped nursing during and after the study. Duloxetine 40 mg was given orally every 12 hours for 3.5 days; seven plasma and milk samples over 12 hours were obtained after the seventh dose. Plasma and milk samples were analysed using validated liquid chromatography-tandem mass spectrometry methods. Safety measures included vital signs, ECGs, laboratory tests, adverse event monitoring and depression rating scales. RESULTS: The mean steady-state milk-to-plasma duloxetine exposure ratio was 0.25 (90% CI 0.18, 0.35). The amount of duloxetine in the breast milk was 7 microg/day (range 4-15 microg/day). The estimated infant dose was 2 microg/kg/day (range 0.6-3 microg/kg/day), which is 0.14% of the maternal dose. Dizziness, nausea and fatigue were commonly reported adverse events. No clinically important changes in safety measures occurred. CONCLUSION: Duloxetine is detected in breast milk, and steady-state concentrations in breast milk are about one-fourth of those in maternal plasma. As the safety of duloxetine in infants is unknown, prescribers should carefully assess, on an individual basis, the potential risks of duloxetine exposure to infants and the benefits of nursing an infant when the mother is on duloxetine therapy.

In vitro and in vivo evaluations of cytochrome P450 1A2 interactions with duloxetine.

OBJECTIVE: To determine whether duloxetine is a substrate, inhibitor or inducer of cytochrome P450 (CYP) 1A2 enzyme, using in vitro and in vivo studies in humans. METHODS: Human liver microsomes or cells with expressed CYP enzymes and specific CYP inhibitors were used to identify which CYP enzymes catalyse the initial oxidation steps in the metabolism of duloxetine. The potential of duloxetine to inhibit CYP1A2 activity was determined using incubations with human liver microsomes and phenacetin, the CYP1A2 substrate. The potential for duloxetine to induce CYP1A2 activity was determined using human primary hepatocytes treated with duloxetine for 72 hours. Studies in humans were conducted using fluvoxamine, a potent CYP1A2 inhibitor, and theophylline, a CYP1A2 substrate, as probes. The subjects were healthy men and women aged 18-65 years. Single-dose duloxetine was administered either intravenously as a 10-mg infusion over 30 minutes or orally as a 60-mg dose in the presence or absence of steady-state fluvoxamine (100 mg orally once daily). Single-dose theophylline was given as 30-minute intravenous infusions of aminophylline 250 mg in the presence or absence of steady-state duloxetine (60 mg orally twice daily). Plasma concentrations of duloxetine, its metabolites and theophylline were determined using liquid chromatography with tandem mass spectrometry. Pharmacokinetic parameters were estimated using noncompartmental methods and evaluated using mixed-effects ANOVA. Safety measurements included vital signs, clinical laboratory tests, a physical examination, ECG readings and adverse event reports. RESULTS: The in vitro results indicated that duloxetine is metabolized by CYP1A2; however, duloxetine was predicted not to be an inhibitor or inducer of CYP1A2 in humans. Following oral administration in the presence of fluvoxamine, the duloxetine area under the plasma concentration-time curve from time zero to infinity (AUC(infinity)) and the maximum plasma drug concentration (C(max)) significantly increased by 460% (90% CI 359, 584) and 141% (90% CI 93, 200), respectively. In the presence of fluvoxamine, the oral bioavailability of duloxetine increased from 42.8% to 81.9%. In the presence of duloxetine, the theophylline AUC(infinity) and C(max) increased by only 13% (90% CI 7, 18) and 7% (90% CI 2, 14), respectively. Coadministration of duloxetine with fluvoxamine or theophylline did not result in any clinically important safety concerns, and these combinations were generally well tolerated. CONCLUSION: Duloxetine is metabolized primarily by CYP1A2; therefore, coadministration of duloxetine with potent CYP1A2 inhibitors should be avoided. Duloxetine does not seem to be a clinically significant inhibitor or inducer of CYP1A2; therefore, dose adjustment of CYP1A2 substrates may not be necessary when they are coadministered with duloxetine.

Mortality experience in the elderly in the Impairment Study Capture System.

Using the dataset of the Impairment Study Capture System, we analyzed mortality experience and underwriting on policies issued at ages 70 and up. Policy issue dates were from 1990-1998 and observation ran from 5-12 years. There were 1430 deaths in a total exposure of over 102,000 policy-years. Nearly two thirds of the total exposure was for females. Despite the use of expected mortality differentiated by smoking status, the mortality ratio for smokers was much higher than for nonsmokers. Both the type of underwriting (paramedical and medical compared to nonmedical and simplified) and the underwriting risk class confirmed the intended effects of underwriting. Variation of mortality ratio by duration after issue did not contradict the select period slope of the 2001 VBT.

Medicines Adaptive Pathways to Patients (MAPPs): A Story of International Collaboration Leading to Implementation.

After nearly a decade of discussion, analysis, and development, the Medicines Adaptive Pathways to Patients (MAPPs) initiative is beginning to see acceptance from regulators, industry, patients, and payers, with the first live pilot project initiated under the guidance of the European Medicines Agency in 2014. Although it is a significant achievement to see the first asset being placed into human trials under an adaptive pathway, there is much to be learned regarding the multinational and multi-stakeholder effort that has driven the growing acceptance of MAPPs as a methodology and concept, as well as the need for continued and increasing international collaboration to foster the wider adoption of MAPPs. Changes in available science and technology, as well as a number of challenges in the current system, outlined in this paper, are transforming approaches to medicines development and approval. It is these challenges that have led directly to the groundbreaking MAPPs collaboration between the Massachusetts Institute of Technology Center for Biomedical Innovation's New Drug Development Paradigms Initiative, the EMA, patient, payer and health technology assessment groups, the European Federation of Pharmaceutical Industries and Associations, and the Innovative Medicines Initiative-a European public-private partnership. This article examines the development of MAPPs, from inception of the concept, to the establishment of this trans-Atlantic initiative, and examines challenges for the future.

Mortality study of policies on insured lives with diabetes mellitus known at time of issue.

BACKGROUND: This is an Impairment Study Capture System (ISCS) study of contemporary diabetes mellitus mortality among insured lives. Because the diagnosis and treatment of diabetes has changed during the last 15 years, many applicants may be expected to exhibit more favorable outcomes than in the past. The study covers policy-years durational experience extending to only 10 years. METHODS: We analyzed the total mortality experience of 41,972 insurance policies. The policies were issued at standard or substandard premium rates between 1989 and 2002 policy anniversaries. The number of policies terminated by death (actual deaths) is compared with expected deaths using the 2001 Valuation Basic Table (2001 VBT). Main outcome measures are expressed as mortality ratios (MR %) and excess death rates/1000 (EDR/M). Poisson confidence intervals are used to test the statistical significance of mortality ratios at the 95% confidence limit. RESULTS: The total experience is based on 103,104 policy-years exposure: males 57,888 policy-years (56%) and females 45,216 policy-years (44%). There were 495 policy-deaths 284 male and 211 female. Substandard risks represented the majority of the total exposure, 76,658 policy-years in both sexes combined (male 56%, female 44%). The mean duration of substandard exposure was 2.3 years. Total mortality for all insured age-groups and risk categories combined was 187%. The mortality ratios for policies rated standard had confidence intervals that were consistent with 100% of the 2001 VBT. The mortality ratios for policies rated substandard had confidence intervals that were above 100% of the 2001 VBT. Mortality ratios varied with the type of treatment. They were lowest in those treated with diet alone and highest in individuals treated with diet plus insulin. CONCLUSION: A clinical diagnosis of diabetes continues to demonstrate evidence of increased, but improving, mortality in insured individuals. The underwriting risk appraisal process effectively categorizes the risk, especially for the substandard classes where the ratings assigned to policies were consistent with the mortality results. The lack of significant differences in the mortality ratios between males and females as well as between nonsmokers and smokers indicate that the early duration variations by gender and smoking status in the 2001 VBT account for these differences in early duration diabetes mortality. Subsequent follow-up studies containing longer durations may show these differences emerging. Results must be interpreted with caution because of the small data set, limited number of ISCS participating companies, and durational experience extending to only 10 policy years.