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(1) Background: As Kaplan–Meier (KM) analysis is limited to single unidirectional endpoints, most advanced cancer randomized clinical trials (RCTs) are powered for either progression-free survival (PFS) or overall survival (OS). This discards efficacy information carried by partial responses, complete responses, and stable disease that frequently precede progressive disease and death. Chauhan Weighted Trajectory Analysis (CWTA) is a generalization of KM that simultaneously assesses multiple rank-ordered endpoints. We hypothesized that CWTA could use this efficacy information to reduce sample size requirements and expedite efficacy signals in advanced cancer trials. (2) Methods: We performed 100-fold and 1000-fold simulations of solid tumor systemic therapy RCTs with health statuses rank-ordered from complete response (Stage 0) to death (Stage 4). At increments of the sample size and hazard ratio, we compared KM PFS and OS with CWTA for (i) sample size requirements to achieve a power of 0.8 and (ii) the time to first significant efficacy signal. (3) Results: CWTA consistently demonstrated greater power, and it reduced the sample size requirements by 18% to 35% compared to KM PFS and 14% to 20% compared to KM OS. CWTA also expedited time-to-efficacy signals by 2- to 6-fold. (4) Conclusions: CWTA, by incorporating all efficacy signals in the cancer treatment trajectory, provides a clinically relevant reduction in the required sample size and meaningfully expedites the efficacy signals of cancer treatments compared to KM PFS and KM OS. Using CWTA rather than KM as the primary trial outcome has the potential to meaningfully reduce the numbers of patients, trial duration, and costs to evaluate therapies in advanced cancer.

Abstract Purpose The aim of this study was to describe the longitudinal developmental trajectories and its influencing factors of sexual activity in patients with breast cancer during treatment. Methods A prospective longitudinal study was conducted, including 225 newly diagnosed breast cancer patients in A tumor specialty three-class hospital in Southwest China. We measured sexual activity at the time of admission and diagnosis (T0) and one month (T1), three months (T2), six months (T3), and nine months (T4) after diagnosis. A trajectory analysis model (GBTM) was used to explore the changes in sexual activity in breast cancer patients. Multivariate binary logistic regression analysis was used to analyse the factors that affected the classification of sexual activity trajectories. Results The ratio of sexual activity abruptly declined from 100% at baseline to 39.1% at T1. The percentage of sexual activity was improved, from 51.4% at T2 to 63.1% at T4. The optimal model was a 2-group trajectory of sexual activity in breast cancer patients,36.6% in the “low activity group” and 63.4% in the “high activity group.” The multivariate binary logistic regression analysis revealed statistically significant and positive correlations between sexual activity and age (β = 0.085, OR = 1.089, 95%CI 1.035 ∼ 1.145, P = 0.001),libido(β = 0.774, OR = 2.168, 95%CI 1.337 ∼ 3.515, P = 0.002), vaginal lubrication(β = 1.254, OR = 33.503, 95%CI 2.000 ∼ 6.137, P

Aiming at the lack of effective analysis and identification of operational area in the traditional battlefield situation awareness process, a method of aerial battlefield target trajectory analysis method for operational area extraction is proposed. Firstly, based on the improved Douglas-Peucker algorithm, the featured trajectory is extracted based on the original target trajectory, thus reducing the trajectory redundant information. Secondly, the clustering by fast search and find of density peaks (CFSFDP) algorithm is used to cluster the featured trajectory, which obtains multiple featured points clusters. Finally, each featured points cluster is scanned based on Graham's convex hull algorithm to obtain closed polygons to characterize the combat areas. The feasibility and effectiveness of the algorithm model are verified by several case simulations.

Given the disruptions the COVID-19 pandemic has engendered in people's professional lives, the importance and contribution of certain workforces has been under particular scrutiny. In England, the teaching profession has been under particularly close public scrutiny, with concerns that teachers' perceived social appreciation may have decreased throughout the pandemic. Thus, the current study examined the trajectory of teachers' perceptions of how much society, policymakers and the media had valued the teaching profession throughout this time. With an initial sample of 24 primary and secondary teachers in mainstream state schools in England, 54 online interviews took place at three time points: when school buildings were partially reopened for the first time (June 2020), when they were partially closed for the second time (February 2021) and when they were fully reopened for 16 months (July 2022). Three themes were identified in the data using a longitudinal trajectory analysis based on reflexive thematic analysis: 'initial admiration from local communities progressively waned', 'continuous government disrespect towards teachers' and 'initial media vitriol towards teachers was sustained'. Implications for how teachers and other stakeholders in education can most effectively work together for the benefit of the health and effectiveness of the teaching profession and the educational system are considered in the context of the associated risks when teachers have low levels of perceived social appreciation.

Drug-induced sleep endoscopy (DISE) is used for evaluating upper airway anatomy and determining airway obstruction patterns. It is typically performed with the patient in the supine position. Airway collapse severity is influenced by body position and level of consciousness; the resultant dynamic changes may vary across patients. In this study, we evaluated the severity of upper airway collapse through awake endoscopy and DISE and identified factors affecting the pattern of airway collapse severity. This study included 66 patients with obstructive sleep apnea. The patients underwent type 1 polysomnography, tongue strength assessment, awake endoscopy in the sitting and supine positions, and DISE. Group-based trajectory modeling was performed to identify patients with different collapse severity patterns in different body positions and at different levels of consciousness. Patient with similar severity trajectory were assigned to the same group. Two different severity trajectories (group 1 and group 2) were identified at the tongue base level. Tongue depression strength varied significantly between groups 1 and 2 (47.00 vs. 35.00 kPa; P =.047). During awake endoscopy, collapse severity was significantly higher in group 2 than in group 1. Group 1 had lower rapid eye movement/nonrapid eye movement apnea–hypopnea index ratios and higher tongue depression strength than did group 2. In patients with obstructive sleep apnea, tongue strength may vary depending on body position. Our results should be interpreted with caution because of the limited sample size. Future studies should investigate the effect of oropharyngeal rehabilitation on tongue strength and collapse severity. [ABSTRACT FROM AUTHOR]

Abstract Background The trend of Type 2 diabetes-related costs over 4 years could be classified into different groups. Patient demographics, clinical factors (e.g., A1C, short- and long-term complications), and rurality could be associated with different trends of cost. Study objectives are to: (1) understand the trajectories of cost in different groups; (2) investigate the relationship between cost and key factors in each cost trajectory group; and (3) assess significant factors associated with different cost trajectories. Methods Commercial claims data in Texas from 2016 to 2019 were provided by a large commercial insurer and were analyzed using group-based trajectory analysis, longitudinal analysis of cost, and logistic regression analyses of different trends of cost. Results Five groups of distinct trends of Type 2 diabetes-related cost were identified. Close to 20% of patients had an increasing cost trend over the 4 years. High A1C values, diabetes complications, and other comorbidities were significantly associated with higher Type 2 diabetes costs and higher chances of increasing trend over time. Rurality was significantly associated with higher chances of increasing trend over time. Conclusions Group-based trajectory analysis revealed distinct patient groups with increased cost and stable cost at low, medium, and high levels in the 4-year period. The significant associations found between the trend of cost and A1C, complications, and rurality have important policy and program implications for potentially improving health outcomes and constraining healthcare costs.

The Kaplan–Meier (KM) estimator is widely used in medical research to estimate the survival function from lifetime data. KM estimation is a powerful tool to evaluate clinical trials due to simple computational requirements, its use of a logrank hypothesis test, and the ability to censor patients. However, KM estimation has several constraints and fails to generalize to ordinal variables of clinical interest, such as toxicity and ECOG performance. We devised weighted trajectory analysis (WTA) to combine the advantages of KM estimation with the ability to visualize and compare treatment groups for ordinal variables and fluctuating outcomes. To assess statistical significance, we developed a new hypothesis test analogous to the logrank test. We demonstrated the functionality of WTA through 1000-fold clinical trial simulations of unique stochastic models of chemotherapy toxicity and schizophrenia disease course. With increments in sample size and hazard ratio, we compared the performance of WTA to KM estimation and the generalized estimating equation (GEE). WTA generally required half the sample size to achieve comparable power to KM estimation; advantages over the GEE included its robust nonparametric approach and summary plot. We also applied WTA to real clinical data: the toxicity outcomes of melanoma patients receiving immunotherapy and the disease progression of patients with metastatic breast cancer receiving ramucirumab. The application of WTA demonstrated that using traditional methods such as KM estimation can lead to both type I and II errors by failing to model illness trajectory. This article outlines a novel method for clinical outcome assessment that extends the advantages of Kaplan–Meier estimates to ordinal outcome variables.

(1) Background: As Kaplan–Meier (KM) analysis is limited to single unidirectional endpoints, most advanced cancer randomized clinical trials (RCTs) are powered for either progression-free survival (PFS) or overall survival (OS). This discards efficacy information carried by partial responses, complete responses, and stable disease that frequently precede progressive disease and death. Chauhan Weighted Trajectory Analysis (CWTA) is a generalization of KM that simultaneously assesses multiple rank-ordered endpoints. We hypothesized that CWTA could use this efficacy information to reduce sample size requirements and expedite efficacy signals in advanced cancer trials. (2) Methods: We performed 100-fold and 1000-fold simulations of solid tumor systemic therapy RCTs with health statuses rank-ordered from complete response (Stage 0) to death (Stage 4). At increments of the sample size and hazard ratio, we compared KM PFS and OS with CWTA for (i) sample size requirements to achieve a power of 0.8 and (ii) the time to first significant efficacy signal. (3) Results: CWTA consistently demonstrated greater power, and it reduced the sample size requirements by 18% to 35% compared to KM PFS and 14% to 20% compared to KM OS. CWTA also expedited time-to-efficacy signals by 2- to 6-fold. (4) Conclusions: CWTA, by incorporating all efficacy signals in the cancer treatment trajectory, provides a clinically relevant reduction in the required sample size and meaningfully expedites the efficacy signals of cancer treatments compared to KM PFS and KM OS. Using CWTA rather than KM as the primary trial outcome has the potential to meaningfully reduce the numbers of patients, trial duration, and costs to evaluate therapies in advanced cancer. [ABSTRACT FROM AUTHOR]

Background: Understanding teachers' experiences throughout the school closures and reopenings that have characterized large periods of the COVID-19 pandemic provides us with unique insights into what it means to be a teacher during a global public health crisis. Aim and Method: To investigate teachers' narratives of their experiences, we conducted 95 semi-structured interviews with 24 teachers in England across four time points between April and November 2020. We used a longitudinal qualitative trajectory analysis of participants' stories of their high-, low- and turning-points. Results: We derived four themes that were evident at each time point and developed over time. The themes were: (1) "growing frustration at uncertainties caused by poor government leadership," (2) "expanding concern for pupil learning and well-being," (3) "an increasingly labour-intensive and exhausting job" and (4) "declining pleasure and pride in being a teacher." Conclusions: The findings shed light on the impact of COVID-19 on the professional identity of these teachers and we propose ways in which teachers can be supported now and in the future.

Objective: The aim of this study was to examine the longitudinal relationships between the trajectories of distinct subtypes of various domains of social supports and risk of subjective motoric cognitive risk (MCR) syndrome. Design: Longitudinal cohort study. Setting and participants: 2,279 participants in the Taiwan Longitudinal Study on Aging (TLSA) between 1999 and 2011. Method: A group-based multi-trajectory modeling (GBMTM) was implemented to identify distinct trajectory subtypes within various social support domains, encompassing social networks, emotional support, instrumental support, as well as working and economic status. Logistic regression models were then utilized to evaluate the associations between these trajectory subtypes and the risk of subjective MCR. Results: Among 2,279 participants, GBMTM identified four distinct trajectory subtypes: ''low social support'' (n = 371), ''medium social support '' (n = 862), ''high social support'' (n = 292), and ''high social support with employment'' (n = 754). The incidence rates of subjective MCR for these groups were 9.4%, 9.0%, 4.1%, and 0.8%, respectively. After adjusting for age, sex, education level, and comorbidities, both “low social support” (adjusted odds ratio (aOR) 4.07, 95% CI [1.60–10.34]) and “medium social support” (aOR 3.10, 95% CI [1.26−7.66]) were significantly associated with an increased risk of subjective MCR compared to the ''high social support with employment'' group. Conclusions and implications: The current study demonstrates that social support significantly reduces the risk of subjective MCR, with lower support levels correlating to higher risk, necessitating further intervention studies to confirm the link between social support and risk of subjective MCR.

Objective: To characterize patterns of health care utilization before and after surgery and determine any association with preoperative frailty. Background: Frail patients experience worse postoperative outcomes and increased costs during the surgical encounter. Evidence is comparatively lacking for the longer-term effects of frailty on postoperative health care utilization. Methods: Retrospective, longitudinal cohort analysis of adult patients undergoing any elective surgical procedure after preoperative frailty assessment with the Risk Analysis Index from February 2016 to December 2020 at a large integrated health care delivery and financing system. Group-based trajectory modeling of claims data estimated distinct clusters of patients with discrete utilization trajectories. Multivariable regression predicted membership in trajectories of interest using preoperative characteristics, including frailty. Results: Among 29,067 surgical encounters, 4 distinct utilization trajectories emerged in longitudinal data from the 12 months before and after surgery. All cases exhibited a surge in utilization during the surgical month, after which most patients returned to “low” [25,473 (87.6%)], “medium” [1403 (4.8%)], or “high” [528 (1.8%)] baseline utilization states established before surgery. The fourth trajectory identified 1663 (5.7%) cases where surgery occasioned a transition from “low” utilization before surgery to “high” utilization afterward. Risk Analysis Index score alone did not effectively predict membership in this transition group, but a multivariable model with other preoperative variables was effective (c = 0.859, max rescaled R2 = 0.264). Conclusions: Surgery occasions the transition from low to high health care utilization for a substantial subgroup of surgical patients. Multivariable modeling may effectively discriminate this utilization trajectory, suggesting an opportunity to tailor care processes for these patients. [ABSTRACT FROM AUTHOR]