Tag: pubmed

J Pediatr Orthop. 2023 Apr 27. doi: 10.1097/BPO.0000000000002420. Online ahead of print.

ABSTRACT

BACKGROUND: Patella alta is an anatomic risk factor for patellar instability in adolescents that is also linked to the risk factor of trochlear dysplasia. This study aims to determine the age of onset and age-related incidence of patella alta in a pediatric population of patients with patellar instability. We hypothesized that patellar height ratios would not increase with age, suggesting a congenital rather than the developmental origin of patella alta.

METHODS: A retrospective cross-sectional cohort of patients was collected with the following inclusion criteria: patients aged 5 to 18 who had a knee magnetic resonance imaging performed from 2000 to 2022 and the International Classification of Diseases code for patellar dislocation. Demographic information and details of the patellar instability episode(s) were collected with a chart review. Sagittal magnetic resonance imaging was used to measure Caton-Deschamps Index (CDI) and the Insall-Salvati Ratio (ISR) by 2 observers. Data were analyzed to assess for associations between patellar height ratios and age of the first dislocation and to assess if the proportion of patients categorized as having patella alta changed with age.

RESULTS: The 140 knees included in the cohort had an average age of 13.9 years (SD=2.40; range: 8-18) and were 55% female. Patella alta was present in 78 knees (55.7%) using CDI>=1.2 and in 59 knees (42.1%) using ISR>=1.3. The earliest age patella alta was observed was at age 8 using CDI>=1.2 and age 10 using ISR>=1.3. There were no statistically significant associations between CDI and age without adjustment (P=0.14) nor after adjustment for sex and body mass index (P=0.17). The proportion of knees above the CDI threshold for patella alta to the knees below the cutoff did not show a significant change with age (P=0.09).

CONCLUSIONS: Patella alta, as defined by CDI, is seen in patients as young as 8 years old. Patellar height ratios do not change with age in patients with patellar dislocation, suggesting that patella alta is established at a young age rather than developing during the adolescent years.

LEVEL OF EVIDENCE: Level III-diagnostic, cross-sectional.

PMID:37104788 | DOI:10.1097/BPO.0000000000002420

Psychol Methods. 2023 Apr 27. doi: 10.1037/met0000573. Online ahead of print.

ABSTRACT

Testing null hypotheses of the form “β = 0,” by the use of various Null Hypothesis Significance Tests (rendering a dichotomous reject/not reject decision), is considered standard practice when evaluating the individual parameters of statistical models. Bayes factors for testing these (and other) hypotheses allow users to quantify the evidence in the data that is in favor of a hypothesis. Unfortunately, when testing equality-contained hypotheses, the Bayes factors are sensitive to the specification of prior distributions, which may be hard to specify by applied researchers. The paper proposes a default Bayes factor with clear operating characteristics when used for testing whether the fixed parameters of linear two-level models are equal to zero. This is achieved by generalizing an already existing approach for linear regression. The generalization requires: (a) the sample size for which a new estimator for the effective sample size in two-level models containing random slopes is proposed; (b) the effect size for the fixed effects for which the so-called marginal R² for the fixed effects is used. Implementing the aforementioned requirements in a small simulation study shows that the Bayes factor yields clear operating characteristics regardless of the value for sample size and the estimation method. The paper gives practical examples and access to an easy-to-use wrapper function to calculate Bayes factors for hypotheses with respect to the fixed coefficients of linear two-level models by using the R package bain. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37104765 | DOI:10.1037/met0000573

Psychol Methods. 2023 Apr 27. doi: 10.1037/met0000556. Online ahead of print.

ABSTRACT

Likelihood ratio tests (LRTs) are a popular tool for comparing statistical models. However, missing data are also common in empirical research, and multiple imputation (MI) is often used to deal with them. In multiply imputed data, there are multiple options for conducting LRTs, and new methods are still being proposed. In this article, we compare all available methods in multiple simulations covering applications in linear regression, generalized linear models, and structural equation modeling. In addition, we implemented these methods in an R package, and we illustrate its application in an example analysis concerned with the investigation of measurement invariance. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:37104764 | DOI:10.1037/met0000556

J Clin Oncol. 2023 Apr 27:JCO2202390. doi: 10.1200/JCO.22.02390. Online ahead of print.

ABSTRACT

PURPOSE: It remains unknown whether or not short-term androgen deprivation (STAD) improves survival among men with intermediate-risk prostate cancer (IRPC) treated with dose-escalated radiotherapy (RT).

METHODS: The NRG Oncology/Radiation Therapy Oncology Group 0815 study randomly assigned 1,492 patients with stage T2b-T2c, Gleason score 7, or prostate-specific antigen (PSA) value >10 and ≤20 ng/mL to dose-escalated RT alone (arm 1) or with STAD (arm 2). STAD was 6 months of luteinizing hormone-releasing hormone agonist/antagonist therapy plus antiandrogen. RT modalities were external-beam RT alone to 79.2 Gy or external beam (45 Gy) with brachytherapy boost. The primary end point was overall survival (OS). Secondary end points included prostate cancer-specific mortality (PCSM), non-PCSM, distant metastases (DMs), PSA failure, and rates of salvage therapy.

RESULTS: Median follow-up was 6.3 years. Two hundred nineteen deaths occurred, 119 in arm 1 and 100 in arm 2. Five-year OS estimates were 90% versus 91%, respectively (hazard ratio [HR], 0.85; 95% CI, 0.65 to 1.11]; P = .22). STAD resulted in reduced PSA failure (HR, 0.52; P <.001), DM (HR, 0.25; P <.001), PCSM (HR, 0.10; P = .007), and salvage therapy use (HR, 0.62; P = .025). Other-cause deaths were not significantly different (P = .56). Acute grade ≥3 adverse events (AEs) occurred in 2% of patients in arm 1 and in 12% for arm 2 (P <.001). Cumulative incidence of late grade ≥3 AEs was 14% in arm 1 and 15% in arm 2 (P = .29).

CONCLUSION: STAD did not improve OS rates for men with IRPC treated with dose-escalated RT. Improvements in metastases rates, prostate cancer deaths, and PSA failures should be weighed against the risk of adverse events and the impact of STAD on quality of life.

PMID:37104748 | DOI:10.1200/JCO.22.02390

Pain Med. 2023 Apr 27:pnad049. doi: 10.1093/pm/pnad049. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate how a behavioral health, artificial intelligence (AI)-powered, digital self-management tool affects the daily functions in adults with chronic back and neck pain.

DESIGN: Eligible subjects were enrolled in a 12-week prospective, multicenter, single-arm, open-label study and instructed to use the digital coach daily. Primary outcome was a change in Patient-Reported Outcomes Measurement Information Systems (PROMIS) scores for pain interference. Secondary outcomes were changes in PROMIS physical function, anxiety, depression, pain intensity scores and pain catastrophizing scale (PCS) scores.

METHODS: Subjects logged daily activities, using PainDrainerTM, and data analyzed by the AI engine. Questionnaire and web-based data were collected at 6 and 12-weeks and compared to subjects’ baseline.

RESULTS: Subjects completed the 6- (n = 41) and 12-week (n = 34) questionnaires. A statistically significant Minimal Important Difference (MID) for pain interference was demonstrated in 57.5% of the subjects. Similarly, MID for physical function was demonstrated in 72.5% of the subjects. A pre- to post-intervention improvement in depression score was also statistically significant, observed in 100% of subjects, as was the improvement in anxiety scores, evident in 81.3% of the subjects. PCS mean scores was also significantly decreased at 12 weeks.

CONCLUSION: Chronic pain self-management, using an AI-powered, digital coach anchored in behavioral health principles significantly improved subjects’ pain interference, physical function, depression, anxiety, and pain catastrophizing over the 12-week study period.

PMID:37104747 | DOI:10.1093/pm/pnad049

Bioinformatics. 2023 Apr 27:btad291. doi: 10.1093/bioinformatics/btad291. Online ahead of print.

ABSTRACT

MOTIVATION: Testing association between multiple phenotypes with a set of genetic variants simultaneously, rather than analyzing one trait at a time, is receiving an increasing attention for its high statistical power and easy explanation on pleiotropic effects. The kernel-based association test (KAT), being free of data dimensions and structures, has proven to be a good alternative method for genetic association analysis with multiple phenotypes. However, KAT suffers from substantial power loss when multiple phenotypes have moderate to strong correlations. To handle this issue, we propose a maximum kernel-based association test (MaxKAT) and suggest using the generalized extreme value distribution to calculate its statistical significance under the null hypothesis.

RESULTS: We show that MaxKAT reduces computational intensity greatly while maintaining high accuracy. Extensive simulations demonstrate that MaxKAT can properly control type I error rates and obtain remarkably higher power than KAT under most of the considered scenarios. Application to a porcine dataset used in biomedical experiments of human disease further illustrates its practical utility.

AVAILABILITY AND IMPLEMENTATION: The R package MaxKAT that implements the proposed method is available on Github https://github.com/WangJJ-xrk/MaxKAT.

PMID:37104737 | DOI:10.1093/bioinformatics/btad291

Am J Public Health. 2023 Apr 27:e1-e8. doi: 10.2105/AJPH.2023.307302. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has revealed the importance of the population-scale effects of both diseases and interventions. Vaccines have had an enormous impact, greatly reducing the suffering caused by COVID-19. Clinical trials have focused on individual-level clinical benefits, however, so the broader effects of the vaccines on preventing infection and transmission, and their overall effect at the community level, remain unclear. These questions can be addressed through alternative designs for vaccine trials, including assessing different endpoints and randomizing at the cluster instead of individual level. Although these designs exist, various factors have limited their use as preauthorization pivotal trials. They face statistical, epidemiological, and logistical limitations as well as regulatory barriers and uncertainty. Addressing these hindrances through research, communication, and policy can improve the evidence base of vaccines, their strategic deployment, and population health, both in the COVID-19 pandemic and in future infectious disease outbreaks. (Am J Public Health. Published online ahead of print April 27, 2023:e1-e8. https://doi.org/10.2105/AJPH.2023.307302).

PMID:37104734 | DOI:10.2105/AJPH.2023.307302

J Clin Oncol. 2023 Apr 27:JCO2201153. doi: 10.1200/JCO.22.01153. Online ahead of print.

ABSTRACT

PURPOSE: Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown.

METHODS: We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance.

RESULTS: On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures (P_LRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer.

CONCLUSION: AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

PMID:37104728 | DOI:10.1200/JCO.22.01153

J Chem Inf Model. 2023 Apr 27. doi: 10.1021/acs.jcim.3c00187. Online ahead of print.

ABSTRACT

In this work, we show that the apparent pK_a measured by standard titration experiments is an insufficient measure of acidity or basicity of organic functional groups in multiprotic compounds─a frequent aspect of lead optimization in pharmaceutical research. We show that the use of the apparent pK_a in this context may result in costly mistakes. To properly represent the group’s true acidity/basicity, we propose pK₅₀─a single-proton midpoint measure derived from a statistical thermodynamics treatment of multiprotic ionization. We show that pK₅₀, which may be directly measured in specialized NMR titration experiments, is superior in tracking the functional group’s acidity/basicity across congeneric series of related compounds and converges to the well familiar ionization constant in the monoprotic case.

PMID:37104727 | DOI:10.1021/acs.jcim.3c00187

J Clin Oncol. 2023 Apr 27:JCO2202389. doi: 10.1200/JCO.22.02389. Online ahead of print.

ABSTRACT

PURPOSE: To report patient-reported outcomes (PROs) of a phase III trial evaluating total androgen suppression (TAS) combined with dose-escalated radiation therapy (RT) for patients with intermediate-risk prostate cancer.

METHODS: Patients with intermediate-risk prostate cancer were randomly assigned to dose-escalated RT alone (arm 1) or RT plus TAS (arm 2) consisting of luteinizing hormone-releasing hormone agonist/antagonist with oral antiandrogen for 6 months. The primary PRO was the validated Expanded Prostate Cancer Index Composite (EPIC-50). Secondary PROs included Patient-Reported Outcome Measurement Information System (PROMIS)-fatigue and EuroQOL five-dimensions scale questionnaire (EQ-5D). PRO change scores, calculated for each patient as the follow-up score minus baseline score (at the end of RT and at 6, 12, and 60 months), were compared between treatment arms using a two-sample t test. An effect size of 0.50 standard deviation was considered clinically meaningful.

RESULTS: For the primary PRO instrument (EPIC), the completion rates were ≥86% through the first year of follow-up and 70%-75% at 5 years. For the EPIC hormonal and sexual domains, there were clinically meaningful (P < .0001) deficits in the RT + TAS arm. However, there were no clinically meaningful differences by 1 year between arms. There were also no clinically meaningful differences at any time points between arms for PROMIS-fatigue, EQ-5D, and EPIC bowel/urinary scores.

CONCLUSION: Compared with dose-escalated RT alone, adding TAS demonstrated clinically meaningful declines only in EPIC hormonal and sexual domains. However, even these PRO differences were transient, and there were no clinically meaningful differences between arms by 1 year.

PMID:37104723 | DOI:10.1200/JCO.22.02389