Tag: statistics

Neurourol Urodyn. 2022 Jan 25. doi: 10.1002/nau.24881. Online ahead of print.

ABSTRACT

OBJECTIVE: The increasing wealth of clinical data may become unmanageable for a physician to assimilate into optimal decision-making without assistance. Utilizing a novel machine learning (ML) approach, we sought to develop algorithms to predict patient outcomes following the overactive bladder treatments OnabotulinumtoxinA (OBTX-A) injection and sacral neuromodulation (SNM).

MATERIALS AND METHODS: ROSETTA datasets for overactive bladder patients randomized to OBTX-A or SNM were obtained. Novel ML algorithms, using reproducing kernel techniques were developed and tasked to predict outcomes including treatment response and decrease in urge urinary incontinence episodes in both the OBTX-A and SNM cohorts, in validation and test sets. Blinded expert urologists also predicted outcomes. Receiver operating characteristic curves were generated and AUCs calculated for comparison to lines of ignorance and the expert urologists’ predictions.

RESULTS: Trained algorithms demonstrated outstanding accuracy in predicting treatment response (OBTX-A: AUC 0.95; SNM: 0.88). Algorithms accurately predicted mean decrease in urge urinary incontinence episodes (MSE < 0.15) in OBTX-A and SNM. Algorithms were superior to human experts in response prediction for OBTX-A, and noninferior to human experts in response prediction for SNM.

CONCLUSIONS: Novel ML algorithms were accurate, superior to expert urologists in predicting OBTX-A outcomes, and noninferior to expert urologists in predicting SNM outcomes. Some aspects of the physician-patient interaction are subtle and uncomputable, and thus ML may complement, but not supplant, a physician’s judgment.

PMID:35078268 | DOI:10.1002/nau.24881

Eur J Prev Cardiol. 2022 Jan 25:zwac017. doi: 10.1093/eurjpc/zwac017. Online ahead of print.

ABSTRACT

AIM: To determine the effect of mobile health (mHealth) focused on diet and lifestyle on blood pressure (BP).

METHODS: We performed a systematic review with meta-analysis using the mean difference (MD) of change from baseline as an effect measure. MEDLINE via PubMed, Cochrane Central, and EMBASE were reviewed until May 6, 2020. We included randomized controlled trials of adults who participated in mHealth focused on diet and lifestyle. Interventions were grouped according to the presence of health professional intervention (PI) (PI+mHealth or mHealth only). Eligible controls did not participate in mHealth and were classified as active comparator (PI) or no intervention (NI). Subgroup analyses were performed according to the presence of prior cardiovascular disease and hypertension status.

RESULTS: We included 44 trials involving 24,692 participants. Mobile health interventions were superior to NI in reducing SBP in both situations: alone (MD = -1.8 mmHg; 95%CI: -3.6; 0.0) or with PI (MD = -5.3 mmHg; 95%CI: -7.5;-3.1), with a greater effect size in the latter group (p = 0.016). This benefit was not observed when the control was PI. DBP and SBP had consistent results. There was a marked effect of PI+mHealth vs. NI on the BP reduction among hypertensive participants.

CONCLUSIONS: Current evidence shows that mHealth focused on diet and lifestyle can reduce BP, especially when implemented in hypertensive participants, and PI may provide additional benefit.

PMID:35078238 | DOI:10.1093/eurjpc/zwac017

J Natl Cancer Inst. 2022 Jan 25:djac017. doi: 10.1093/jnci/djac017. Online ahead of print.

ABSTRACT

BACKGROUND: There is limited research on how the opioid epidemic and consequent risk reduction policies have impacted pain management among cancer patients. The purpose of this study is to analyze how an Opioid Safety Initiative (OSI) implemented at the Veteran’s Health Administration (VHA) affected opioid prescribing patterns and opioid-related toxicity.

METHODS: We performed an interrupted time series analysis of 42,064 opioid-naïve patients treated at the VHA for prostate, lung, breast, and colorectal cancer from 2011-2016. Segmented regression was used to evaluate the impact of the OSI on the incidence of any new opioid prescriptions, high-risk prescriptions, persistent use, and pain-related ED visits. We compared the cumulative incidence of adverse opioid events including an opioid related admission or diagnosis of misuse before and after the OSI. All statistical tests were 2-sided.

RESULTS: The incidence of new opioid prescriptions was 26.7% (95% CI = 25.0-28.4%) in 2011 and increased to 50.6% (95% CI = 48.3-53.0%) by 2013 prior to OSI implementation (monthly rate of change: +3.3%, 95% CI = 1.3-4.2%, p < .001). After the OSI, there was a decrease in the monthly rate of change for new prescriptions (-3.4%, 95% CI = -3.9 – -2.9%, p < .001). The implementation of the OSI was associated with a decrease in the monthly rate of change of concomitant benzodiazepines and opioid prescriptions (-2.5%, 95% CI = -3.2 – -1.8%, p < .001), no statistically significant change in high-dose opioids (-1.2%, 95% CI = -3.2-0.9%, p = .26), a decrease in persistent opioid use (-5.7%, 95% CI = -6.8 – -4.7%, p < .001), and an increase in pain-related ED visits (+3.0%, 95% CI = 1.0-5.0%, p = .003). The OSI was associated with a decreased incidence of opioid-related admissions (3-year cumulative incidence: 0.9% [95% CI = 0.7-1.0%] vs. 0.5% [95% CI = 0.4-0.6%], p < .001) and no statistically significant change in the incidence of opioid misuse (3-year cumulative incidence: 1.2% [95% CI = 1.0-1.3%] vs. 1.2% [1.1-1.4%], p = .77).

CONCLUSIONS: The OSI was associated with a relative decline in the rate of new, persistent, and certain high-risk opioid prescribing as well as a slight increase in the rate of pain-related ED visits. Further research on patient-centered outcomes is required to optimize opioid prescribing policies for patients with cancer.

PMID:35078240 | DOI:10.1093/jnci/djac017

G3 (Bethesda). 2022 Jan 25:jkac020. doi: 10.1093/g3journal/jkac020. Online ahead of print.

ABSTRACT

Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are PCA, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns. Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and have been shown to present a promising alternative to traditional statistical methods for various applications in omics research. In this paper, we propose a deep learning model based on a convolutional autoencoder architecture for dimensionality reduction of genotype data. Using a highly diverse cohort of human samples, we demonstrate that the model can identify population clusters and provide richer visual information in comparison to PCA, while preserving global geometry to a higher extent than t-SNE and UMAP, yielding results that are comparable to an alternative deep learning approach based on variational autoencoders. We also discuss the use of the methodology for more general characterization of genotype data, showing that it preserves spatial properties in the form of decay of linkage disequilibrium with distance along the genome and demonstrating its use as a genetic clustering method, comparing results to the ADMIXTURE software frequently used in population genetic studies.

PMID:35078229 | DOI:10.1093/g3journal/jkac020

Oncology. 2022 Jan 25:1-9. doi: 10.1159/000519605. Online ahead of print.

ABSTRACT

BACKGROUND: The 2 approved somatostatin analogs (SSAs) in the first-line treatment of advanced, well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are octreotide long-acting release (Sandostatin LAR) and somatuline depot (Lanreotide). The study’s objective was to compare progression-free survival (PFS) and overall survival (OS) of patients (pts) with GEP-NETs treated with somatuline or octreotide LAR. Pts and Methods: Pts with advanced well-differentiated GEP-NET who received either SSA at Emory University between 1995 and 2019 were included after institutional review board approval. The primary end point was PFS, defined as time to disease progression (according to the Response Evaluation Criteria in Solid Tumors, version 1.1, or clinical progression) or death. The secondary end point was OS. Kaplan-Meier curves were generated, and log-rank tests were conducted to compare the survival outcomes.

RESULTS: A total of 105 pts were identified. The mean age was 62.1 years (SD ± 11.8). The male-to-female ratio was 51:54. The majority (N = 69, 65.7%) were white. Most pts had grade 2 (G2) disease (N = 44, 41.9%). Primary location was small bowel in 58 (55.2%), pancreas in 27 (25.7%), and other in 20 (19.0%). Functional tumors were defined in 32 pts distributed equally between the 2 groups. Distribution of treatment was similar in the 2 groups, with 54 receiving octreotide LAR and 51 receiving somatuline depot. The median PFS for the octreotide LAR and somatuline depot groups was 12 months (95% CI, 6-18 months) and 10.8 months (95% CI, 6-15.6 months), respectively, and the difference was not statistically significant (p = 0.2665). For pts with G1 disease, the median PFS for the octreotide LAR and somatuline depot was 8.4 versus 32.4 months, respectively, and the difference was not statistically significant (p = 0.159). For G2 disease, the difference in median PFS between octreotide LAR and somutaline depot groups was statistically significant (12 vs. 7.2 months, respectively; p = 0.0372). The mean follow-up time for octreotide LAR was 21.6 months versus 11.3 months for somatuline depot.

CONCLUSIONS: Overall, there was no difference in PFS between octreotide LAR and somatuline depot for pts with well-differentiated, metastatic GEP-NETs. A prospective study is worth designing selecting for G.

PMID:35078191 | DOI:10.1159/000519605

Aesthet Surg J. 2022 Jan 25:sjac009. doi: 10.1093/asj/sjac009. Online ahead of print.

ABSTRACT

BACKGROUND: A stable cartilaginous framework sets up the foundation for a successful rhinoplastic procedure. However, the curvature of the anterior septal angle usually does not match the added tip graft, leaving a structural gap that potentially causes postoperative rotation of the nasal tip. A supplementary graft is required to fill this gap, consolidating this structure at three dimensions.

OBJECTIVES: To detail and validate the utilization of a graft that fills the structural gap for a more stabilized framework and better-sustained tip position in the long term.

METHODS: Intraoperative counter-rotating Newton force and complications were retrospectively collected. Three-dimensional stereophotogrammetric evaluations were performed. Anthropometric points were analyzed in a blinded fashion. Outcome variables were tip projection, nasal length, the Goode ratio, and tip rotation. Results were compared statistically.

RESULTS: Thirty-one female patients, ranging in age from 18-41 years, finished the study. Intraoperative rotating measurement indicated an unequivocal stabilizing effect of the plug-in graft. Postoperative analysis showed great maintenance of tip position over time. Tip projection and nasolabial angle had a slight decrease over time, the differences were not statistically different.

CONCLUSIONS: The plug-in graft effectively consolidates the entire cartilaginous framework in rib-based rhinoplasty procedures. This anatomically integrated structure sets up the fundamental groundwork which provides uncompromising support for the tip graft, so as to achieve an aesthetically pleasing outcome that endures. When executed properly, this graft is effective in maintaining postoperative tip positions, which warrants the technical challenges and the prolonged operating time.

PMID:35078208 | DOI:10.1093/asj/sjac009

J Neural Eng. 2022 Jan 25. doi: 10.1088/1741-2552/ac4ecf. Online ahead of print.

ABSTRACT

Objective – We present a framework to objectively test and compare stimulation artefact removal techniques in the context of neural spike sorting. Approach – To this end, we used realistic hybrid ground-truth spiking data, with superimposed artefacts from in vivo recordings. We used the framework to evaluate and compare several techniques: blanking, template subtraction by averaging, linear regression, and a multi-channel Wiener filter (MWF). Main results – Our study demonstrates that blanking and template subtraction result in a poorer spike sorting performance than linear regression and MWF, while the latter two perform similarly. Finally, to validate the conclusions found from the hybrid evaluation framework, we also performed a qualitative analysis on in vivo recordings without artificial manipulations. Significance – Our framework allows direct quantification of the impact of the residual artefact on the spike sorting accuracy, thereby allowing for a more objective and more relevant comparison compared to indirect signal quality metrics that are estimated from the signal statistics. Furthermore, the availability of a ground truth in the form of single-unit spiking activity also facilitates a better estimation of such signal quality metrics.

PMID:35078163 | DOI:10.1088/1741-2552/ac4ecf

Phys Med Biol. 2022 Jan 25. doi: 10.1088/1361-6560/ac4ed9. Online ahead of print.

ABSTRACT

The aim of this work is to investigate in-room proton radiographies to compensate realistic rigid and non-rigid transformations in clinical-like scenarios based on 2D-3D deformable image registration (DIR) framework towards future clinical implementation of adaptive radiation therapy (ART). Monte Carlo simulations of proton radiographies (pRads) based on clinical X-ray CT of a head and neck, and a brain tumor patients are simulated for two different detector configurations (i.e., integration-mode and list-mode detectors) including high and low proton statistics. A realistic deformation, derived from cone beam CT of the patient, is applied to the treatment planning CT. Rigid inaccuracies in patient positioning are also applied and the effect of small, medium and large fields of view (FOVs) is investigated. A stopping criterion, as desirable in realistic scenarios devoid of ground truth proton CT (pCT), is proposed and investigated. Results show that rigid and non-rigid transformations can be compensated based on a limited number of low dose pRads. The root mean square error with respect to the pCT shows that the 2D-3D DIR of the treatment planning CT based on 10 pRads from integration-mode data and 2 pRads from list-mode data is capable of achieving comparable accuracy (~90% and >90%, respectively) to conventional 3D-3D DIR. The dice similarity coefficient over the segmented regions of interest also verifies the improvement in accuracy prior to and after 2D-3D DIR. No relevant changes in accuracy are found between high and low proton statistics except for 2 pRads from integration-mode data. The impact of FOV size is negligible. The convergence of the metric adopted for the stopping criterion indicates the optimal convergence of the 2D-3D DIR. This work represents a further step towards the potential implementation of ART in proton therapy. Further computational optimization is however required to enable extensive clinical validation.

PMID:35078167 | DOI:10.1088/1361-6560/ac4ed9

Epidemics. 2022 Jan 19;38:100537. doi: 10.1016/j.epidem.2022.100537. Online ahead of print.

ABSTRACT

During a pandemic, data are very “noisy” with enormous amounts of local variation in daily counts, compared with any rapid changes in trend. Accurately characterizing the trends and reliable predictions on future trajectories are important for planning and public situation awareness. We describe a semi-parametric statistical model that is used for short-term predictions of daily counts of cases and deaths due to COVID-19 in Canada, which are routinely disseminated to the public by Public Health Agency of Canada. The main focus of the paper is the presentation of the model. Performance indicators of our model are defined and then evaluated through extensive sensitivity analyses. We also compare our model with other commonly used models such as generalizations of logistic models for similar purposes. The proposed model is shown to describe the historical trend very well with excellent ability to predict the short-term trajectory.

PMID:35078118 | DOI:10.1016/j.epidem.2022.100537

Animal. 2022 Jan 22;16(2):100449. doi: 10.1016/j.animal.2021.100449. Online ahead of print.

ABSTRACT

In the dairy industry, the dry period has been identified as an area for potential reduction in antibiotic use, as part of a one health approach to preserve antibiotic medicines for human health. The objective of this study was to assess the impact of dry cow treatment on somatic cell count (SCC), intramammary infection (IMI) and milk yield on five commercial Irish dairy herds. A total of 842 cows across five spring calving dairy herds with a monthly bulk tank SCC of < 200 000 cells/mL were recruited for this study. At dry-off, cows which had not exceeded 200 000 cells/mL in the previous lactation were assigned one of two dry-off treatments: internal teat seal (ITS) alone (Lo_TS) or antibiotic plus ITS (Lo_AB + TS). Cows which exceeded 200 000 cells/mL in the previous lactation were treated with antibiotic plus ITS and included in the analysis as a separate group (Hi_AB + TS). Test-day SCC and lactation milk yield records were provided by the herd owners. Quarter milk samples were collected at dry-off, after calving and at mid-lactation for bacteriological culture and quarter SCC analysis. Cow level SCC was available for 789 cows and was log-transformed for the purpose of analysis. Overall, the log SCC of the cows in the Lo_TS group was significantly higher than the cows in Lo_AB + TS group and not statistically different to the cows in the Hi_AB + TS group in the subsequent lactation. However, the response to treatment differed according to the herd studied; the log SCC of the cows in the Lo_TS group in Herds 3, 4 and 5 was not statistically different to the cows in Lo_AB + TS group, whereas in the other two herds, the log SCC was significantly higher in the Lo_TS when compared to the Lo_AB + TS group. There was a significant interaction between dry-off group and herds on SCC and odds of infection in the subsequent lactation. The results of this study suggest that the herd prevalence of IMI may be useful in decision-making regarding the treatment of cows with ITS alone at dry-off to mitigate its impact on udder health.

PMID:35078119 | DOI:10.1016/j.animal.2021.100449