Citations

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Abstract Background The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution. In typical (memory‐predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicenters. However, atypical (non‐amnestic‐predominant) AD variants with heterogeneous tau patterns provide a key opportunity to assess the universality of connectivity as a scaffold for tau progression. Method We included tau‐PET data from 320 subjects with atypical AD, characterized by highly heterogeneous tau patterns ( n = 139 posterior cortical atrophy/PCA‐AD; n = 103 logopenic variant primary progressive aphasia/lvPPA‐AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS‐AD) from 14 sites, with a subset of patients ( n = 78) having longitudinal tau‐PET data. As an independent sample, we further included regional post‐mortem tau stainings from 93 atypical AD patients from two sites ( n = 19 PCA‐AD, n = 32 lvPPA‐AD, n = 23 bvAD, n = 19 CBS‐AD). Gaussian mixture modeling was used to harmonize different tau‐PET tracers by transforming tau‐PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether 1) brain regions with stronger functional connectivity showed greater covariance in cross‐sectional and longitudinal tau‐PET and post‐mortem tau pathology, and 2) functional connectivity of tau‐PET epicenters and tau‐PET accumulation epicenters was associated with cross‐sectional and longitudinal tau patterns. Result Tau‐PET epicenters—defined as the 5% brain regions with the highest tau load—aligned with clinical variants, e.g. a posterior pattern in PCA‐AD (“visual AD”) and left‐hemispheric temporal predominance in lvPPA‐AD (“language AD”) (Figure 1). More strongly functionally connected regions showed correlated concurrent tau‐PET levels, which was confirmed with post‐mortem data (Figure 2). Moreover, the connectivity profile of tau‐PET epicenters and accumulation epicenters corresponded to tau‐PET progression patterns (Figure 3). Conclusion Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicenters, across all AD clinical variants. Since tau proteinopathy is a key driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant‐specific endpoints in clinical trials.

Abstract Introduction/Objective Burnout among trainers can lead to increased human-derived laboratory errors (HDLEs), which can negatively affect patient outcomes. Through implemented improvement strategies, trainer burnout and HDLEs were reduced without impacting the trainee burnout by creating a core training group to ensure consistency in training and providing additional training tools. Methods/Case Report Burnout was assessed using a survey from the Burnout Assessment Tool1. This survey indicates burnout as a numerical score and was given to trainers and trainees at 3 intervals. Pre-implementation concluded trainer burnout average score was 2.47. HDLEs were categorized and totaled in conjunction with the burnout surveys. Pre-implementation data for HDLEs showed 14% were associated with a training event and 14% were associated with a process change that did not have a training event. Results: Conclusion Final data showed a decrease in average burnout score for trainers (pre=2.47, post=2.26). Trainee score was not statistically different. Post-implementation data of HDLEs showed 6% were associated with a training event and 0% were associated with a process change that didn’t have a training event. In review of the project, standardization of training, proper communication of process changes decreases average burnout of trainers and reduces the amount of HDLEs associated with training and process changes.

Abstract The link between regional tau load and clinical manifestation of Alzheimer’s disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD (‘visual AD’) and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD (‘language AD’). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.

Abstract Background and Aims Truncating variants in the TTN gene (TTNtv) are the most common genetic cause of dilated cardiomyopathy (DCM) but also occur as incidental findings in the general population. This study investigated factors associated with the clinical manifestation of TTNtv. Methods An international multicentre retrospective observational study was performed in families with TTNtv-related DCM. Shared frailty models were used to estimate associations of variant characteristics with lifetime risk of DCM, and logistic regression to estimate odds ratios (ORs) for individual-level clinical risk factor profiles (cardiac conditions, cardiovascular comorbidities, lifestyle) and DCM. Results A total of 3158 subjects in 1043 families with TTNtv-related DCM were studied. TTNtv-positive subjects were 21-fold more likely to develop DCM [OR, 21.21; 95% confidence interval (CI), 14.80–30.39]. Disease onset was earlier in males, but was similar for TTNtv of different types and locations. The presence of clinical risk factors was associated with earlier DCM onset (OR, 3.41; 95% CI, 2.06–5.64), with a prior history of atrial fibrillation having a two-fold increased odds of DCM (OR, 2.05; 95% CI, 1.27–3.32). The prevalence of clinical risk factors increased with age; however, the strength of the DCM association was greatest for young-onset (<30 years) disease (OR, 4.75; 95% CI, 2.35–9.60). Administration of beta-adrenergic receptor or renin-angiotensin system-blocking drugs prior to overt DCM was associated with 87% reduced odds of DCM (OR, .13; 95% CI, .08–.23). Conclusions Disease onset in TTNtv-associated familial DCM is dependent on individual patient context and is potentially modifiable by risk factor management and prophylactic therapeutic intervention.

AbstractBackgroundThere is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial.MethodWe included 269 amyloid‐β‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [18F]AV1451/[18F]flortaucipir/Tauvid, 27% [18F]MK6240, 19% [18F]PI2620). Using Gaussian mixture modeling including amyloid‐β‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly.ResultTau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Figure 1). In line with this, tau epicenters were highly heterogeneous across variants (Figure 1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Figure 2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Figure 3).ConclusionThis multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

AbstractBackgroundThere is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial.MethodWe included 269 amyloid‐ß‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [18F]AV1451/[18F]flortaucipir/Tauvid, 27% [18F]MK6240, 19% [18F]PI2620). Using Gaussian mixture modeling including amyloid‐ß‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly.ResultTau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Fig.1). In line with this, tau epicenters were highly heterogeneous across variants (Fig.1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Fig.2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Fig.3).ConclusionThis multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

Context : A common component within rehabilitation recommendations for baseball pitchers is employment of an interval throwing program. However, there is a lack of a consistent set of advocated guidelines for program content and implementation for athletes at the professional and collegiate levels. Design : Cross-sectional study. Methods : A survey was developed to obtain clinician views regarding the composition and implementation of interval throwing programs for baseball pitchers. The survey was divided into demographic information and sections on criteria to begin throwing programs, frequency of throwing, soreness management, warm-up components, program components and regulation of a program, and criteria to achieve permitting live throwing. Clinicians including physicians, physical therapists, and certified athletic trainers who evaluate and treat musculoskeletal injuries among baseball pitchers at the professional-level and/or collegiate-level clinician received the survey. Responses were tabulated and compared between the professional-level clinician and collegiate-level clinician groups using chi-square analyses with statistical significance set at P ≤ .05. Results : The survey was completed by 166 clinicians (collegiate level = 81, professional-level clinician = 85). There were no statistical differences between groups for allowing warm-up throws, program regulation, maximum distance allowed, managing soreness, or criteria to achieve before permitting live throwing. Between-group differences included criteria to begin a program (≤.03), warm-up distance ( P ≤ .02), nonthrowing warm-up methods ( P ≤ .04), non-warm-up distance ( P ≤ .01), using ratings of perceived exertion ( P < .01), throwing frequency ( P < .01), and program components ( P ≤ .04). Conclusions : Responses appear to mirror interval throwing program designs previously reported in the literature but there are modifications and additions utilized by clinicians at different playing levels.

Background: There remains room for improvement in surgical outcomes after medial ulnar collateral ligament reconstruction (MUCLR) in professional pitchers. The role and influence of postoperative rehabilitation on the outcomes of MUCLR are unknown. There is a paucity of clinical data in the current literature comparing the success of various postsurgical rehabilitation protocols after MUCLR. Purpose: To summarize the current rehabilitation process for professional pitchers recovering from MUCLR, evaluates what player and surgical factors correlate with outcomes, and determines whether rehabilitation timing and milestones correlate with successful outcomes. Study Design: Case series; Level of evidence, 4. Methods: 717 professional baseball pitchers who underwent MUCLR between 2010 and 2016 were identified and included in the analysis. Player characteristics evaluated included age at the time of surgery, throwing side dominance, primary pitching role (starter vs reliever), and level of play (MLB, AAA, AA, A). Surgical factors studied included date of surgery, graft type (palmaris longus autograft vs gracilis autograft), and surgical technique (figure of 8 vs docking vs other). The rehabilitation and throwing progression details were as follows: initiation date; first throw date; dates to start throwing from various distances; longest distance thrown; first flat ground throw date; first mound throw date; and first live batting practice (BP) date. The primary outcomes of interest were the ability to return to play at any level (RTP), the ability to return to the same level (RSL), and the time to RTP/RSL. Results: On average, pitchers threw a baseball for the first time 4.9 months after surgery, with a broad range (2.8-14.9 months). For the 675 (94%) pitchers who were able to progress to mound throwing, the first throws off a mound occurred at a mean of 9.4 months after surgery. Before progressing to the mound, the mean longest long-toss distance reached was 137.5 feet, with a broad range (105-300 feet). A high variation in the time to RTP (7.6-53.9 months) and RSL (8.6-60.7 months) was noted. A total of 599 (84%) pitchers were able to RTP at a mean time of 14.9 ± 4.9 months after surgery (range, 7.6-53.9 months). Also, 528 (74%) pitchers were able to RSL after MUCLR at a mean of 17.4 ± 7 months (range, 8.6-60.7 months) postoperatively. Age was the most significant predictor of RTP (hazard ratio [HR], 1.03 [95% CI, 1.01-1.05]; P = .01) and RSL (HR, 0.96 [95% CI, 0.93-0.99]; P < .01). For every 1-year increase in age, there was a 3% increase in the chance of RTP. Conversely, for every 1-year decrease in age, there was a 4% increase in the chance of RSL. MLB players were more likely to RTP (HR, 1.39 [95% CI, 1.18-1.63]; P < .01) but not necessarily to RSL (HR, 0.90 [95% CI, 0.75-1.08]; P = .24). The time from surgery to any of the rehabilitation milestones of interest (first throw, first flat ground pitching, first mound throwing, and first live BP) did not correlate with RTP or RSL (all, P >.05). The same was true for the greatest long-toss distance thrown before transitioning to the mound. Conclusion: Significant variability in the postoperative rehabilitation protocols after MUCLR was observed in 717 professional baseball pitchers. The timing of achievement of throwing progression and rehabilitation milestones postoperatively varied widely but did not correlate with outcomes. Player characteristics—except for player age and professional pitching level—did not correlate with RTP and RSL outcomes. Older pitchers and MLB pitchers were more likely to RTP, but younger players were more likely to RSL. Surgical factors did not correlate with rehabilitation outcomes.