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BackgroundPatients with cancer may be at increased risk of osteoporosis and fracture; however, gaps exist in the existing literature and the association between cancer and fracture requires further examination.MethodsWe conducted a population-based cohort study of Ontario patients with cancer (breast, prostate, lung, gastrointestinal, haematologic) diagnosed between January 2007 to December 2018 and 1:1 matched non-cancer controls. The primary outcome was incident fracture (end of follow-up December 2019). Multivariable Cox regression analysis was used to estimate the relative fracture risk with sensitivity analysis accounting for competing risk of death.ResultsAmong 172,963 cancer patients with non-cancer controls, 70.6% of patients with cancer were <65 years old, 58% were female, and 9375 and 8141 fracture events were observed in the cancer and non-cancer group, respectively (median follow-up 6.5 years). Compared to non-cancer controls, patients with cancer had higher risk of fracture (adjusted HR [aHR] 1.10, 95% CI 1.07–1.14, p < 0.0001), which was also observed for both solid (aHR 1.09, 95% CI 1.05–1.13, p < 0.0001) and haematologic cancers (aHR 1.20, 95% CI 1.10–1.31, p < 0.0001). Sensitivity analysis accounting for competing risk of death did not change these findings.ConclusionsOur study indicates that patients with cancer are at modest risk of fractures compared to non-cancer controls.

Biomarkers are a key component of precision medicine. However, full clinical integration of biomarkers has been met with challenges, partly attributed to analytical difficulties. It has been shown that biomarker reproducibility is susceptible to data preprocessing approaches. Here, we systematically evaluated machine-learning ensembles of preprocessing methods as a general strategy to improve biomarker performance for prediction of survival from early breast cancer. We risk stratified breast cancer patients into either low-risk or high-risk groups based on four published hypoxia signatures (Buffa, Winter, Hu, and Sorensen), using 24 different preprocessing approaches for microarray normalization. The 24 binary risk profiles determined for each hypoxia signature were combined using a random forest to evaluate the efficacy of a preprocessing ensemble classifier. We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. Interestingly, the classification of these biomarkers and its ensemble show striking consistency, demonstrating that similar intrinsic biological information are being faithfully represented. As such, these classification patterns further confirm that there is a subset of patients whose prognosis is consistently challenging to predict. Performance of different prognostic signatures varies with pre-processing method. A simple classifier by unanimous voting of classifications is a reliable way of improving on single preprocessing methods. Future signatures will likely require integration of intrinsic and extrinsic clinico-pathological variables to better predict disease-related outcomes.

Variable warfarin response during treatment initiation poses a significant challenge to providing optimal anticoagulation therapy. We investigated the determinants of initial warfarin response in a cohort of 167 patients. During the first nine days of treatment with pharmacogenetics-guided dosing, S-warfarin plasma levels and international normalized ratio were obtained to serve as inputs to a pharmacokinetic-pharmacodynamic (PK-PD) model. Individual PK (S-warfarin clearance) and PD (I(max)) parameter values were estimated. Regression analysis demonstrated that CYP2C9 genotype, kidney function, and gender were independent determinants of S-warfarin clearance. The values for I(max) were dependent on VKORC1 and CYP4F2 genotypes, vitamin K status (as measured by plasma concentrations of proteins induced by vitamin K absence, PIVKA-II) and weight. Importantly, indication for warfarin was a major independent determinant of I(max) during initiation, where PD sensitivity was greater in atrial fibrillation than venous thromboembolism. To demonstrate the utility of the global PK-PD model, we compared the predicted initial anticoagulation responses with previously established warfarin dosing algorithms. These insights and modeling approaches have application to personalized warfarin therapy.

CD19‐directed autologous chimeric antigen receptor T cell (CAR‐T) therapy has transformed the management of relapsed/refractory (R/R) large B cell lymphoma (LBCL). Initially approved in the third line and beyond setting, CAR‐T is now standard of care (SOC) for second‐line treatment in patients with refractory disease or early relapse (progression within 12 months) following primary chemoimmunotherapy. Despite becoming SOC, most patients do not achieve complete response, and long‐term cure is only observed in approximately 40% of patients. Accordingly, there is an urgent need to better understand the mechanisms of treatment failure and to identify patients that are unlikely to benefit from SOC CAR‐T. The field needs robust biomarkers to predict treatment outcome, as better understanding of prognostic factors and mechanisms of resistance can inform on the design of novel treatment approaches for patients predicted to respond poorly to SOC CAR‐T. This review aims to provide a comprehensive overview of clinical, molecular, imaging, and cellular features that have been shown to influence outcomes of CAR‐T therapy in patients with R/R LBCL.

Background Population differences in warfarin dosing requirement have been reported; however, unlike the pharmacokinetics (PK) of warfarin, the quantitative influences of pharmacodynamic (PD) factors on the anticoagulation response to warfarin in different ethnic populations are totally unknown. Methods Using population PK/PD analysis, we attempted to identify predictors of S -warfarin clearance [CL(S)] and half maximal effective concentration (EC 50 ) to quantify racial differences in both PK and PD parameters, and to assess the contribution of these parameters to the international normalized ratio (INR) and over-anticoagulation response (INR ≥ 4) in a cohort of 309 White, Asian and African American patients. Results Similar to our previous findings, the median CL(S) was 30% lower in African American patients than Asian and White patients (169 vs. 243 and 234 mL/h, p  < 0.01). EC 50 showed a greater racial difference than CL(S) [1.03, 1.70 and 2.76 μg/mL for Asian, White and African American patients, respectively, p  < 0.01). Significant predictors of INR included demographic/clinical (age, body weight, creatinine clearance and sex) and genotypic ( CYP2C9*3,*8 and VKORC1 −1639G>A ) factors, as well as African American ethnicity. In all three racial groups, genetic predictors of INR appeared to have greater influence than demographic/clinical predictors. Both CL(S) and EC 50 contributed to the over-anticoagulation response to warfarin. Patients having VKORC1 −1639 G>A and/or factors associated with reduced CYP2C9 activity were more likely to have an INR ≥ 4. Conclusions Although there were contrasting racial differences in CL(S) and EC 50 that impacted on the INR, the racial difference in EC 50 was greater than that for CL(S), thus explaining the higher warfarin requirement for African American patients.

Background Cardiovascular disease is a significant cause of morbidity and mortality in patients with end-stage renal disease (ESRD) and kidney transplant (KT) patients. Compared with left ventricular (LV) ejection fraction (LVEF), LV strain has emerged as an important marker of LV function as it is less load dependent. We sought to evaluate changes in LV strain using cardiovascular magnetic resonance imaging (CMR) in ESRD patients who received KT, to determine whether KT may improve LV function. Methods We conducted a prospective multi-centre longitudinal study of 79 ESRD patients (40 on dialysis, 39 underwent KT). CMR was performed at baseline and at 12 months after KT. Results Among 79 participants (mean age 55 years; 30% women), KT patients had significant improvement in global circumferential strain (GCS) ( p  = 0.007) and global radial strain (GRS) ( p  = 0.003), but a decline in global longitudinal strain (GLS) over 12 months ( p  = 0.026), while no significant change in any LV strain was observed in the ongoing dialysis group. For KT patients, the improvement in LV strain paralleled improvement in LVEF (57.4 ± 6.4% at baseline, 60.6% ± 6.9% at 12 months; p  = 0.001). For entire cohort, over 12 months, change in LVEF was significantly correlated with change in GCS (Spearman’s r  = − 0.42, p  < 0.001), GRS (Spearman’s r  = 0.64, p  < 0.001), and GLS (Spearman’s r  = − 0.34, p  = 0.002). Improvements in GCS and GRS over 12 months were significantly correlated with reductions in LV end-diastolic volume index and LV end-systolic volume index (all p  < 0.05), but not with change in blood pressure (all p  > 0.10). Conclusions Compared with continuation of dialysis, KT was associated with significant improvements in LV strain metrics of GCS and GRS after 12 months, which did not correlate with blood pressure change. This supports the notion that KT has favorable effects on LV function beyond volume and blood pessure control. Larger studies with longer follow-up are needed to confirm these findings.

Aims/hypothesisContemporary data for the association of diabetes with haematological malignancies are lacking. We evaluated the risk of developing haematological malignancies and subsequent mortality in individuals with diabetes compared with those without diabetes.MethodsWe conducted a population-based observational study using healthcare databases from Ontario, Canada. All Ontario residents 30 years of age or older free of cancer and diabetes between 1 January 1996 and 31 December 2015 were eligible for inclusion. Using Cox regression analyses, we explored the association between diabetes and the risk and mortality of haematological malignancies (leukaemia, lymphoma, multiple myeloma). The impact of timing on associations was evaluated with analyses stratified by time since diabetes diagnosis (<3 months, 3 months to 1 year, ≥1 year).ResultsWe identified 1,003,276 individuals with diabetes and age and sex matched these to 2,006,552 individuals without diabetes. Compared with individuals without diabetes, those with diabetes had a modest but significantly higher risk of a haematological malignancy (adjusted HR 1.10 [95% CI 1.08, 1.12] p < 0.0001). This association persisted across all time periods since diabetes diagnosis. Among those with haematological malignancies, diabetes was associated with a higher all-cause mortality (HR 1.36 [95% CI 1.31, 1.41] p < 0.0001) compared with no diabetes, as well as cause-specific mortality.Conclusions/interpretationDiabetes is associated with a higher risk of haematological malignancies and is an independent risk factor of all-cause and cause-specific mortality. Greater efforts for lifestyle modification may not only reduce diabetes burden and its complications but may also potentially lower risk of malignancy and mortality.

Contemporary data on the effect of levothyroxine dose on the occurrence of atrial fibrillation (AF) are lacking, particularly in the older population. Our objective was to determine the effect of cumulative levothyroxine exposure on risk of AF and ischemic stroke in older adults. We conducted a population-based observational study using health care databases from Ontario, Canada. We identified adults aged ≥66 years without a history of AF who filled at least 1 levothyroxine prescription between April 1, 2007, and March 31, 2016. Cases were defined as cohort members who had incident AF (emergency room visit or hospitalization) between the date of first levothyroxine prescription and December 31, 2017. Index date was date of AF. Cases were matched with up to 5 controls without AF on the same index date. Secondary outcome was ischemic stroke. Cumulative levothyroxine exposure was estimated based on total milligrams of levothyroxine dispensed in the year prior to index date. Using nested case-control approach, we compared outcomes between older adults who received high (≥0.125 mg/d), medium (0.075-0.125 mg/d), or low (0-0.075 mg/d) cumulative levothyroxine dose. We compared outcomes between current, recent past, and remote past levothyroxine use. Of 183,360 older adults treated with levothyroxine (mean age 82 years; 72% women), 30,560 (16.1%) had an episode of AF. Compared to low levothyroxine exposure, high and medium exposure was associated with significantly increased risk of AF after adjustment for covariates (adjusted odds ratio [aOR] 1.29, 95% CI 1.23-1.35; aOR 1.08, 95% CI 1.04-1.11; respectively). No association was observed between levothyroxine exposure and ischemic stroke. Compared with current levothyroxine use, older adults with remote levothyroxine use had lower risks of AF (aOR 0.56, 95% CI 0.52-0.59) and ischemic stroke (aOR 0.61, 95% CI 0.56-0.67). Among older persons treated with levothyroxine, levothyroxine at doses >0.075 mg/d is associated with an increased risk of AF compared to lower exposure.

Purpose Little data exist for comparing cardiac safety and survival outcomes of trastuzumab/pertuzumab or ado-T emtansine (TDM1) in metastatic breast cancer (MBC) patients enrolled in randomized clinical trial (RCT) vs the real-world. Methods This was a retrospective population-based cohort of all patients with MBC treated with trastuzumab/pertuzumab or TDM1 (2012–2017) in Ontario, Canada. Outcomes were incident heart failure (HF) and overall survival (OS). RCT data were obtained from digitizing survival curves and compared with cohort data using Kaplan–Meier analysis. Age-based comparison of outcomes was conducted for patients ≥ 65 years old vs younger than 65. Results The two cohorts composed of 833 and 397 patients treated with trastuzumab/pertuzumab and TDM1, of whom 5.5% and 7.6% had baseline HF, respectively. Incident HF following trastuzumab/pertuzumab or TDM1 was low (trastuzumab/pertuzumab 1.8 events/100 person years; TDM1 0.02 events/100 person years). The median OS was 39.2 and 56.4 months in the trastuzumab/pertuzumab population-based cohort and CLEOPATRA, respectively. The median OS was 15.4 and 30.9 months in the TDM1 population-based cohort and EMILIA, respectively. Cohort OS was significantly worse than RCT OS (trastuzumab/pertuzumab HR 1.67, 95% CI 1.37–2.03, p  < 0.0001; TDM1 HR 2.80, 95% CI 2.27–3.44, p  < 0.0001). Older patients had worse OS than younger patients for trastuzumab/pertuzumab (HR 1.60, 95% CI 1.19–2.16, p  = 0.0018), but not for TDM1 (HR 1.16, 95% CI 0.81–1.66, p  = 0.43). Conclusion HF incidence during trastuzumab/pertuzumab or TDM1 therapy in this real-world cohort was low. Survival in this cohort was worse compared to RCT, suggesting that recruitment of patients similar to the real-world population is required.

Tamoxifen is a widely utilized adjuvant anti-estrogen agent for hormone receptor-positive breast cancer, known to undergo CYP2D6-mediated bioactivation to endoxifen. However, little is known regarding additional genetic and non-genetic determinants of optimal endoxifen plasma concentration. Therefore, 196 breast cancer patients on tamoxifen were enrolled in this prospective study over a 24-month period. Blood samples were collected for pharmacogenetic and drug-level analysis of tamoxifen and metabolites. Regression analysis indicated that besides CYP2D6, the recently described CYP3A4 *22 genotype, seasonal variation, and concomitant use of CYP2D6-inhibiting antidepressants were significant predictors of endoxifen concentration. Of note, genetic variation explained 33 % of the variability while non-genetic variables accounted for 13 %. Given the proposed notion of a sub-therapeutic endoxifen concentration for predicting breast cancer recurrence, we set the therapeutic threshold at 18 nM, the 20th percentile for endoxifen level among enrolled patients in this cohort. Nearly 70 % of CYP2D6 poor metabolizers as well as extensive metabolizers on potent CYP2D6-inhibiting antidepressants exhibited endoxifen levels below 18 nM, while carriers of CYP3A4 *22 were twofold less likely to be in sub-therapeutic range. Unexpectedly, endoxifen levels were 20 % lower during winter months than mean levels across seasons, which was also associated with lower vitamin D levels. CYP3A4 *22 genotype along with sunshine exposure and vitamin D status may be unappreciated contributors of tamoxifen efficacy. The identified covariates along with demographic variables were integrated to create an endoxifen concentration prediction algorithm to pre-emptively evaluate the likelihood of individual patients falling below the optimal endoxifen concentration.