The study mapped depressive and anxiety symptom trajectories throughout adolescence and early adulthood, arrayed by time since menarche, a novel indicator of pubertal change and examined the effect ...of age of menarche and pubertal timing, more frequently used variables, on depressive and anxiety symptom severity trajectories.
Secondary analysis of a cross-sequential prospective longitudinal investigation included a community sample of 262 U.S., adolescent females. Participants were enrolled in age cohorts of 11, 13, 15, and 17 years. Four annual waves of data were collected. Self-report of age at menarche was categorized into pubertal timing categories. A novel measure “time since menarche” (chronological age at each wave minus age at menarche), was measured along with depressive and anxiety symptom severity. Two-piece growth curve modeling with landmark registration examined depressive and anxiety symptom severity trajectories according to time since menarche.
There was no change (p > .05) in depression and anxiety symptom severity before menarche; however, in the years leading away from menarche, depression and anxiety symptom severity decreased (p < .05). Age at menarche was not associated with change in depressive and anxiety symptom severity (p > .05) and there were no moderating effects of pubertal timing.
Depressive and anxiety symptoms decrease in the years leading away from menarche, suggesting puberty-related psychopathology may be transitory in some individuals. Time since menarche may be a clinically-relevant indicator of psychological functioning in pubescent adolescent females. Future studies should examine this variable in larger samples, including more adolescents in the earlier stages of puberty.
OBJECTIVES/GOALS: A disease-agnostic translational science framework for data mining is proposed for use across disciplines to: Answer clinical questions, justify future clinical research ...recruitment, and explore under-represented populations. As a case example, male puberty demonstrates utility of the framework. METHODS/STUDY POPULATION: As a case example using the generalizable framework, the following interdisciplinary question was asked: Does early pubertal timing increase the risk of developing type II diabetes (T2d) in boys? A digital phenotype of males < 18 years old was created in the TriNetX Diamond Network utilizing Boolean operator data queries. TriNetX contains patient electronic health record information (ICD-10 diagnoses, anthropometric measures). A case control analysis leveraging patient counts from various digital phenotypes allowed for outcome (T2d) comparison of boys diagnosed with precocious puberty (E30.1, ICD code for early pubertal timing) to those without, while controlling for body mass index (BMI). RESULTS/ANTICIPATED RESULTS: Subjects (N=12,996,132) displayed the following digital phenotype: Male, < 18 years old, without ever having a BMI documented >85th percentile. Boys diagnosed with precocious puberty (E30.1) were 6.89 times more likely to develop T2d when aged 14-18 years old than those without (OR 6.89, 95%CI: 5.17-9.19, p. DISCUSSION/SIGNIFICANCE: Boys are under-represented in the early pubertal timing literature, justifying future human subjects research on male puberty. This case example demonstrates a broader disease-agnostic framework which can be adapted across disciplines. Opportunities may include public health digital phenotyping.
Focal therapy (FT) by high-intensity focused ultrasound (HIFU) is an emerging option for localized prostate cancer (PC). Due to the lack of long-term data, a close monitoring after FT is essential, ...but there are still uncertainties about the optimal follow-up regimen. Here we report on a series of FT-HIFU patients with the focus on oncological short-term outcome and the value of postoperative magnetic resonance imaging (MRI).
We included 21 patients treated by FT-HIFU using the Focal One® device (EDAP TMS, France) between November 2015 and May 2018. PC localization was assessed by preoperative multiparametric MRI (mpMRI) and transrectal ultrasound-guided targeted and systematic biopsy. Oncological follow-up included prostate-specific antigen (PSA) development, mpMRI, control biopsies (targeted and systematic) of the treated and untreated areas and salvage treatment rate. Control mpMRI and control biopsy were performed after 6-12 months.
15 patients (71.4%) were managed by focal ablation of a solitary lesion, while 6 patients (28.6%) underwent zonal tumor ablation. All patients underwent control mpMRI and biopsy. After a mean follow-up period of 11.7 months, cancer relapse was detected in 8 patients (38.1%), with 4 patients (19%) having infield recurrence. Postoperative mpMRI revealed 3 out of 4 infield PC relapses but missed 5 out of 7 outfield relapses. Clinically significant cancer recurrence was present in 1 patient (4.8%), which was missed by mpMRI. Posttreatment mpMRI had a sensitivity, specificity, positive and negative predictive value of 62.5, 92.3, 83.3 and 80.0%, respectively, for overall relapse detection based on patient level. Only 1 of the 8 recurrences was suspected based on PSA progression. 4 of the 8 patients with PC relapse (19%) underwent salvage therapy (2 patients by radical prostatectomy, 2 patients by salvage FT-HIFU).
Postoperative mpMRI might play a valuable role during follow-up after focal HIFU therapy, particularly in terms of infield relapse detection. Irrespective of mpMRI results, the repeat biopsy regimen should incorporate systematic biopsy including cores of the treated and untreated prostate areas.
In the upcoming decades, the KM3NeT detectors will produce valuable data that can be used in various scientific contexts, from astro- and particle physics to environmental and Earth and Sea science. ...Based on the Open Science policy established by the KM3NeT Collaboration, several efforts to offer science-ready data, foster common analysis approaches and publish open source software are currently pursued. In this contribution, ongoing projects focusing on the exchange of high-level data and simulation derivatives and establishment of an integrated computing environment supporting an open-science focused workflow will be discussed.
Certification as a prostate cancer center requires the offer of several supportive measures to patients undergoing radical prostatectomy (RP). However, it remains unclear how patients estimate the ...relevance of these measures and whether the availability of these measures differs between certified prostate cancer centers (CERTs) and non-certified centers (NCERTs). In 20 German urologic centers, a survey comprising questions on the relevance of 15 supportive measures was sent to 1000 patients at a median of 15 months after RP. Additionally, patients were asked to rate the availability of these measures using a four-item Likert scale. The aim of this study was to compare these ratings between CERTs and NCERTs. The response rate was 75.0%. In total, 480 patients underwent surgery in CERTs, and 270 in NCERTs. Patients rated 6/15 supportive measures as very relevant: preoperative medical counselling concerning treatment options, a preoperative briefing answering last questions, preoperative pelvic floor exercises (PFEs), postoperative PFEs, postoperative social support, and postoperative rehabilitation addressing physical fitness recovery. These ratings showed no significant difference between CERTs and NCERTs (
= 0.133-0.676). In addition, 4/9 of the remaining criteria were rated as more detailed by patients in CERTs. IMPROVE represents the first study worldwide to evaluate a patient-reported assessment of the supportive measures accompanying RP. Pertinent offers vary marginally between CERTs and NCERTs.
•We propose a registration model with inferred spatially adaptive regularisation.•The effects of this regularisation prior are shown on tensor based morphometry.•The inferred prior leads to better ...localisation of deformations.•We illustrate how this leads to a more realistic description of registration uncertainty.•We demonstrate how Bayesian model comparison can be used in registration.
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This paper introduces a novel method for inferring spatially varying regularisation in non-linear registration. This is achieved through full Bayesian inference on a probabilistic registration model, where the prior on the transformation parameters is parameterised as a weighted mixture of spatially localised components. Such an approach has the advantage of allowing the registration to be more flexibly driven by the data than a traditional globally defined regularisation penalty, such as bending energy. The proposed method adaptively determines the influence of the prior in a local region. The strength of the prior may be reduced in areas where the data better support deformations, or can enforce a stronger constraint in less informative areas. Consequently, the use of such a spatially adaptive prior may reduce unwanted impacts of regularisation on the inferred transformation. This is especially important for applications where the deformation field itself is of interest, such as tensor based morphometry. The proposed approach is demonstrated using synthetic images, and with application to tensor based morphometry analysis of subjects with Alzheimer’s disease and healthy controls. The results indicate that using the proposed spatially adaptive prior leads to sparser deformations, which provide better localisation of regional volume change. Additionally, the proposed regularisation model leads to more data driven and localised maps of registration uncertainty. This paper also demonstrates for the first time the use of Bayesian model comparison for selecting different types of regularisation.
Background: Immune checkpoint inhibitors (ICI) are standard of care in patients with metastatic urothelial carcinoma (mUC) ineligible for cisplatin, and as second-line therapy after platinum-based ...chemotherapy. To date, few data exist about the efficacy of the former second-line chemotherapeutic agent vinflunine after the failure of sequential platinum-based chemotherapy and ICI treatment. The aim of this analysis was to examine the efficacy of vinflunine in a post-ICI third- or later-line setting. Methods: In this retrospective German multicenter study, data of mUC patients treated with vinflunine were reviewed in six centers between February 2010 and December 2021. All of the 105 included patients had radiologic progression after first-line platinum-based chemotherapy. The objective was to describe the efficacy of vinflunine in terms of overall response rate (ORR), clinical benefit rate (CBR), overall survival (OS), and progression-free survival (PFS) for post-ICI and ICI-naïve patients, respectively. Results: In our cohort, 61 patients (58.1%) had preceding immunotherapy before vinflunine administration, and 44 patients (41.9%) were ICI-naïve. Patients with ICI pretreatment showed an ORR of 22.4% compared to 15.6% within ICI-naïve patients (p = 0.451), and CBR was 51.0% vs. 25.0% (p = 0.020), respectively. Post-ICI patients showed longer OS (8.78 vs. 5.72 months; p = 0.467) and longer PFS (3.09 vs. 2.14 months; p = 0.105). Conclusion: This analysis supports the sequential use of vinflunine in post-ICI patients since the vinca-alkaloid retains a measurable clinical activity in these heavily pretreated patients. The therapeutic benefit may be higher than demonstrated in previous studies.
In this paper, we show how the concept of statistical deformation models (SDMs) can be used for the construction of average models of the anatomy and their variability. SDMs are built by performing a ...statistical analysis of the deformations required to map anatomical features in one subject into the corresponding features in another subject. The concept of SDMs is similar to statistical shape models (SSMs) which capture statistical information about shapes across a population, but offers several advantages over SSMs. First, SDMs can be constructed directly from images such as three-dimensional (3-D) magnetic resonance (MR) or computer tomography volumes without the need for segmentation which is usually a prerequisite for the construction of SSMs. Instead, a nonrigid registration algorithm based on free-form deformations and normalized mutual information is used to compute the deformations required to establish dense correspondences between the reference subject and the subjects in the population class under investigation. Second, SDMs allow the construction of an atlas of the average anatomy as well as its variability across a population of subjects. Finally, SDMs take the 3-D nature of the underlying anatomy into account by analysing dense 3-D deformation fields rather than only information about the surface shape of anatomical structures. We show results for the construction of anatomical models of the brain from the MR images of 25 different subjects. The correspondences obtained by the nonrigid registration are evaluated using anatomical landmark locations and show an average error of 1.40 mm at these anatomical landmark positions. We also demonstrate that SDMs can be constructed so as to minimize the bias toward the chosen reference subject.
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