Association between trajectories of adherence to endocrine therapy and risk of treated breast cancer recurrence among US nonmetastatic breast cancer survivors.

BACKGROUND: Endocrine therapy is the mainstay treatment for breast cancer (BC) to reduce BC recurrence risk. During the first year of endocrine therapy use, nearly 30% of BC survivors are nonadherent, which may increase BC recurrence risk. This study is to examine the association between endocrine therapy adherence trajectories and BC recurrence risk in nonmetastatic BC survivors. METHODS: This retrospective cohort study included Medicare beneficiaries in the United States (US) with incident nonmetastatic BC followed by endocrine therapy initiation in 2010-2019 US Surveillance, Epidemiology, and End Results linked Medicare data. We calculated monthly fill-based proportion of days covered in the first year of endocrine therapy. We applied group-based trajectory models to identify distinct endocrine therapy adherence patterns. After the end of the first-year endocrine therapy trajectory measurement period, we estimated the risk of time to first treated BC recurrence within 4 years using Cox proportional hazards models. RESULTS: We identified 5 trajectories of adherence to endocrine therapy in BC Stages 0-I subgroup (n = 28,042) and in Stages II-III subgroup (n = 7781). A trajectory of discontinuation before 6 months accounted for 7.0% in Stages 0-I and 5.8% in Stages II-III subgroups, and this trajectory was associated with an increased treated BC recurrence risk compared to nearly perfect adherence (Stages 0-I: adjusted hazard [aHR] = 1.84, 95% CI = 1.46-2.33; Stages II-III: aHR = 1.38, 95% CI = 1.07-1.77). CONCLUSIONS: Nearly 7% of BC survivors who discontinued before completing 6 months of treatment was associated with an increased treated BC recurrence risk compared to those with nearly perfect adherence among Medicare nonmetastatic BC survivors.

Recent Advances in Group-Based Trajectory Modeling for Clinical Research.

Group-based trajectory modeling (GBTM) identifies groups of individuals following similar trajectories of one or more repeated measures. The categorical nature of GBTM is particularly well suited to clinical psychology and medicine, where patients are often classified into discrete diagnostic categories. This review highlights recent advances in GBTM and key capabilities that remain underappreciated in clinical research. These include accounting for nonrandom subject attrition, joint trajectory and multitrajectory modeling, the addition of the beta distribution to modeling options, associating trajectories with future outcomes, and estimating the probability of future outcomes. Also discussed is an approach to selecting the number of trajectory groups. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 20 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

Trajectories of adherence to extended treatment with direct oral anticoagulants and risks of recurrent venous thromboembolism and major bleeding.

BACKGROUND: Little is known about medication adherence patterns and their association with effectiveness and safety among patients with venous thromboembolism (VTE) receiving direct oral anticoagulant (DOAC) therapy beyond 3-6 months of initial treatment. OBJECTIVE: To examine the associations between adherence trajectories of extended treatment with DOAC and the risks of recurrent VTE and major bleeding among patients with VTE. METHODS: We conducted a retrospective cohort study of patients with incident VTE who completed 6 months of initial anticoagulant treatment and received either DOAC extended therapy or no extended therapy using MarketScan Commercial and Medicare Supplemental databases (2013-2019). We used group-based trajectory models to identify distinct adherence patterns during extended treatment. Using inverse probability treatment weighted Cox proportional hazards models, we examined the association between the adherence trajectories and the risks of recurrent VTE and major bleeding. RESULTS: Among 10,960 patients with extended treatment with DOACs (rivaroxaban, apixaban, dabigatran, edoxaban) and 5,133 patients with no extended treatment, we identified 4 distinct trajectories (consistently high, gradually declining, rapidly declining, and no extended treatment). Compared with the no extended treatment group, the groups with consistently high adherence (hazard ratio = 0.09, 95% CI = 0.05-0.17) and with gradually declining adherence (0.13, 0.03-0.53) showed decreased recurrent VTE risk without increased major bleeding risk (consistently high adherence 1.19, 0.71-1.99; gradually declining adherence 1.96, 0.81-4.70). There was no difference in the risk of recurrent VTE (0.34, 0.10-1.16) for the group with rapidly declining adherence, but this group was associated with increased major bleeding risk (2.65, 1.01-6.92). CONCLUSIONS: Our findings underscore the clinical importance of continuing and remaining adherent to extended DOAC treatment without increased major bleeding risk for patients with VTE. DISCLOSURES: This research was supported by the BMS/Pfizer Alliance American Thrombosis Investigator Initiated Research Program. The funding source had no role in the design, collection, analysis, or interpretation of the data or the decision to submit the article for publication. Dr Lo-Ciganic reported receiving research funding from Merck Sharp & Dohme Corp. Dr Dietrich reported receiving honorarium for training and education from BMS/Pfizer. Dr DeRemer is a stockholder of Portola Pharmaceuticals and reported receiving personal fees for advisory board meeting from BMS. No other disclosures were reported.

Trajectories of adherence to extended treatment with warfarin and risks of recurrent venous thromboembolism and major bleeding.

Background: Little is published about warfarin therapy adherence patterns beyond 6 months of initial anticoagulant treatment and their association with effectiveness and safety for patients with venous thromboembolism (VTE). Objectives: To compare the risks of recurrent VTE and major bleeding during extended treatment between adherence patterns using MarketScan Commercial and Medicare Supplemental databases (2013-2019). Methods: In a retrospective cohort study, we included patients with incident VTE who completed an initial 6-month anticoagulant treatment and received either warfarin or no extended therapy. Group-based trajectory models were used to identify distinct extended treatment trajectories. Associations between the trajectories and risk of hospitalization due to recurrent VTE and major bleeding were assessed using inverse probability treatment-weighted Cox proportional hazards models. Results: Compared with no extended treatment, consistently high warfarin adherence was associated with a significantly decreased risk of hospitalization due to recurrent VTE (hazard ratio [HR] = 0.23; 95% CI, 0.12-0.45), but gradually (HR = 0.29; 95CI, 0.08-1.06) or rapidly declining (HR = 0.14; 95% CI, 0.02-1.24) adherence showed no association with the risk of hospitalization due to recurrent VTE. Compared with no extended treatment, warfarin extended therapy was associated with an increased risk of hospitalization due to major bleeding regardless of adherence patterns (consistently high: HR = 2.08; 95% CI, 1.18-3.64, gradually declining: HR = 2.10; 95% CI, 0.74-5.95, and rapidly declining: HR = 9.19; 95% CI, 4.38-19.29). However, compared with rapidly declining adherence, consistently high (HR = 0.23; 95% CI, 0.11-0.47) and gradually declining (HR = 0.23; 95% CI, 0.08-0.64) adherence were associated with decreased risk of hospitalization due to major bleeding. Conclusion: The findings indicated that consistently high adherence to extended warfarin treatment was associated with a decreased risk of hospitalization due to recurrent VTE but an increased risk of hospitalization due to major bleeding compared with no extended treatment.

Trajectories of Oral Anticoagulation Adherence and Associated Clinical Outcomes During Long-Term Anticoagulation Among Medicare Beneficiaries With Venous Thromboembolism.

BACKGROUND: Little is known about anticoagulation medication nonadherence patterns impacting effectiveness and safety outcomes in clinical practice. OBJECTIVE: We identified adherence trajectories of extended therapy with direct-acting oral anticoagulants (DOACs) and warfarin after 6 months initial anticoagulant therapy among Medicare beneficiaries with venous thromboembolism (VTE). We further assessed the associated recurrent VTE and major bleeding risks. METHODS: Using group-based trajectory models, this retrospective cohort study identified distinct beneficiary subgroups with similar adherence patterns of extended-phase anticoagulant treatment (DOACs or warfarin) for patients with VTE who completed 6 months of initial anticoagulant treatment. We examined associations between adherence trajectories and risks of recurrent VTE and major bleeding using inverse probability treatment weighted Cox proportional hazards models. RESULTS: Compared with no extended treatment, consistently high DOAC adherence was associated with decreased recurrent VTE risk (hazard ratio [HR] = 0.33, 95% confidence interval [CI] = 0.21-0.51) without increased major bleeding risk, and consistently high warfarin adherence was associated with decreased recurrent VTE risk (HR = 0.62, 95% CI = 0.40-0.95) and increased major bleeding risk (HR = 1.64, 95% CI = 1.12-2.41). Gradually declining adherence to DOACs (HR = 1.80, 95% CI = 1.07-3.03) or warfarin (HR = 2.34, 95% CI = 1.57-3.47) was associated with increased bleeding risk with no change in recurrent VTE risk. CONCLUSION AND RELEVANCE: This real-world evidence suggests persistently adhering to extended DOAC therapy is associated with lower recurrent VTE risk without increasing major bleeding among Medicare beneficiaries with VTE. Persistently adhering to extended warfarin therapy was associated with lower recurrent VTE risk but higher major bleeding risk.

Pain trajectories of nursing home residents.

BACKGROUND: Understanding changes in nursing home (NH) resident pain over time would provide a more informed perspective, allowing opportunities to alter the course of illness, plan care, and set priorities. Therefore, the purpose of this analysis was to identify and characterize clinically meaningful, dynamic pain trajectories in NH residents. METHODS: Retrospective longitudinal analysis of NH resident pain scores with a length of stay >100 days (N = 4864). Group-based trajectory modeling was applied to Minimum Data Set 3.0 assessments to identify pain trajectories. Trajectories were then characterized using unadjusted and adjusted cross-sectional associations between residents' demographic and clinical characteristics and their pain trajectory. RESULTS: We identified four distinct trajectories: (1) consistent pain absence (48.9%), (2) decreasing-increasing pain presence (21.8%), (3) increasing-decreasing pain presence (15.3%), and (4) persistent pain presence (14.0%). Demographics of younger age and living in a rural area were associated with the persistent pain presence trajectory. Clinical variables of obesity and intact cognition were associated with being in the persistent pain presence trajectory. A smaller proportion of residents with moderately or severely impaired cognition were in any of the trajectory groups with pain. CONCLUSIONS: We identified and characterized four pain trajectories among NH residents, including persistent pain presence which was associated with demographic characteristics (younger, female, rural) and clinical factors (obese, fracture, contracture). Moreover, residents with a diagnosis of Alzheimer's disease or dementia were less likely to be in any of the three trajectories with pain, likely representing the difficulty in evaluating pain in these residents. It is important that NH staff understand, recognize, and respond to the factors associated with the identified pain trajectories to improve mitigation of potentially persistent pain (e.g., hip fracture, contracture) or improve proxy pain assessment skills for residents at risk for under reporting of pain (e.g., Alzheimer's Disease).

Bayesian Outcome Prediction After Resuscitation From Cardiac Arrest.

BACKGROUND AND OBJECTIVES: Postarrest prognostication research does not typically account for the sequential nature of real-life data acquisition and interpretation and reports nonintuitive estimates of uncertainty. Bayesian approaches offer advantages well suited to prognostication. We used Bayesian regression to explore the usefulness of sequential prognostic indicators in the context of prior knowledge and compared this with a guideline-concordant algorithm. METHODS: We included patients hospitalized at a single center after cardiac arrest. We extracted prospective data and assumed these data accrued over time as in routine practice. We considered predictors demographic and arrest characteristics, initial and daily neurologic examination, laboratory results, therapeutic interventions, brain imaging, and EEG. We fit Bayesian hierarchical generalized linear multivariate models predicting discharge Cerebral Performance Category (CPC) 4 or 5 (poor outcomes) vs 1-3 including sequential clinical and prognostic data. We explored outcome posterior probability distributions (PPDs) for individual patients and overall. As a comparator, we applied the 2021 European Resuscitation Council and European Society of Intensive Care Medicine (ERC/ESICM) guidelines. RESULTS: We included 2,692 patients of whom 864 (35%) were discharged with a CPC 1-3. Patients' outcome PPDs became narrow and shifted toward 0 or 1 as sequentially acquired information was added to models. These changes were largest after arrest characteristics and initial neurologic examination were included. Using information typically available at or before intensive care unit admission, sensitivity predicting poor outcome was 51% with a 0.6% false-positive rate. In our most comprehensive model, sensitivity for poor outcome prediction was 76% with 0.6% false-positive rate (FPR). The ERC/ESICM algorithm applied to 547 of 2,692 patients and yielded 36% sensitivity with 0% FPR. DISCUSSION: Bayesian models offer advantages well suited to prognostication research. On balance, our findings support the view that in expert hands, accurate neurologic prognostication is possible in many cases before 72 hours postarrest. Although we caution against early withdrawal of life-sustaining therapies, rapid outcome prediction can inform clinical decision making and future clinical trials.

Trajectories of physical capacity among community-dwelling older adults in the United States.

OBJECTIVE: Although the prognostic value of physical capacity is well-established, less is known about longitudinal patterns of physical capacity among community-dwelling older adults. We sought to describe long-term trajectories of physical capacity in a nationally representative sample of Medicare beneficiaries. DESIGN: Cohort study SETTING AND PARTICIPANTS: Annually collected data on 6,783 community-dwelling participants in the National Health and Aging Trends Study from 2011 to 2016 were analyzed. METHODS: Performance-based physical capacity was measured using the Short Physical Performance Battery [(SPPB) range: 0-12, higher is better]. Self-reported physical capacity was measured using six pairs of activities with composite scores from 0 to 12 (higher is better). We then used group-based trajectory modeling to identify longitudinal patterns of each physical capacity measure over 6 years. Associations of baseline characteristics with trajectories were examined using multinomial logistic regression. RESULTS: The cohort was 57% female, 68% white, and 58% were ≥75 years. Six distinct trajectories of SPPB scores were identified. Two "high" groups (n = 2192, 43%) maintained high average SPPB scores. Two "moderate decline" groups (n = 1459, 29%) had a mid-range SPPB score at baseline and demonstrated gradual decline. A "low decline" group (n = 811, 16%) started with a low SPPB score and experienced a greater decline. A "very low" group (n = 590, 12%) had very low SPPB scores in all years. Six trajectories for self-reported physical capacity were also identified. Older age, worse health, lower income and education, and being Black or Hispanic were associated with lower and declining physical capacity.

Dosing profiles of concurrent opioid and benzodiazepine use associated with overdose risk among US Medicare beneficiaries: group-based multi-trajectory models.

BACKGROUND AND AIMS: One-third of opioid (OPI) overdose deaths involve concurrent benzodiazepine (BZD) use. Little is known about concurrent opioid and benzodiazepine use (OPI-BZD) most associated with overdose risk. We aimed to examine associations between OPI-BZD dose and duration trajectories, and subsequent OPI or BZD overdose in US Medicare. DESIGN: Retrospective cohort study. SETTING: US Medicare. PARTICIPANTS: Using a 5% national Medicare data sample (2013-16) of fee-for-service beneficiaries without cancer initiating OPI prescriptions, we identified 37 879 beneficiaries (age ≥ 65 = 59.3%, female = 71.9%, white = 87.6%, having OPI overdose = 0.3%). MEASUREMENTS: During the 6 months following OPI initiation (i.e. trajectory period), we identified OPI-BZD dose and duration patterns using group-based multi-trajectory models, based on average daily morphine milligram equivalents (MME) for OPIs and diazepam milligram equivalents (DME) for BZDs. To label dose levels in each trajectory, we defined OPI use as very low (< 25 MME), low (25-50 MME), moderate (51-90 MME), high (91-150 MME) and very high (>150 MME) dose. Similarly, we defined BZD use as very low (< 10 DME), low (10-20 DME), moderate (21-40 DME), high (41-60 DME) and very high (> 60 DME) dose. Our primary analysis was to estimate the risk of time to first hospital or emergency department visit for OPI overdose within 6 months following the trajectory period using inverse probability of treatment-weighted Cox proportional hazards models. FINDINGS: We identified nine distinct OPI-BZD trajectories: group A: very low OPI (early discontinuation)-very low declining BZD (n = 10 598; 28.0% of the cohort); B: very low OPI (early discontinuation)-very low stable BZD (n = 4923; 13.0%); C: very low OPI (early discontinuation)-medium BZD (n = 4997; 13.2%); D: low OPI-low BZD (n = 5083; 13.4%); E: low OPI-high BZD (n = 3906; 10.3%); F: medium OPI-low BZD (n = 3948; 10.4%); G: very high OPI-high BZD (n = 1371; 3.6%); H: very high OPI-very high BZD (n = 957; 2.5%); and I: very high OPI-low BZD (n = 2096; 5.5%). Compared with group A, five trajectories (32.3% of the study cohort) were associated with increased 6-month OPI overdose risks: E: low OPI-high BZD [hazard ratio (HR) = 3.27, 95% confidence interval (CI) = 1.61-6.63]; F: medium OPI-low BZD (HR = 4.04, 95% CI = 2.06-7.95); G: very high OPI-high BZD (HR = 6.98, 95% CI = 3.11-15.64); H: very high OPI-very high BZD (HR = 4.41, 95% CI = 1.51-12.85); and I: very high OPI-low BZD (HR = 6.50, 95% CI = 3.15-13.42). CONCLUSIONS: Patterns of concurrent opioid and benzodiazepine use most associated with overdose risk among fee-for-service US Medicare beneficiaries initiating opioid prescriptions include very high-dose opioid use (MME > 150), high-dose benzodiazepine use (DME > 40) or medium-dose opioid with low-dose benzodiazepine use.

Spinal pain in childhood: prevalence, trajectories, and diagnoses in children 6 to 17 years of age.

This study aimed to investigate the trajectories of spinal pain frequency from 6 to 17 years of age and describe the prevalence and frequency of spinal pain and related diagnoses in children following different pain trajectories. First through fifth-grade students from 13 primary schools were followed for 5.5 years. Occurrences of spinal pain were reported weekly via text messages. Children reporting spinal pain were physically evaluated and classified using International Classification of Disease criteria. Trajectories of spinal pain frequency were modeled from age 6 to 17 years with latent class growth analysis. We included data from 1556 children (52.4% female, mean (SD) baseline age = 9.1 (1.9) years) and identified 10,554 weeks of spinal pain in 329,756 weeks of observation. Sixty-three percent of children reported one or more occurrences of spinal pain. We identified five trajectories of spinal pain frequency. Half the children (49.8%) were classified as members of a "no pain" trajectory. The remaining children followed "rare" (27.9%), "rare, increasing" (14.5%), "moderate, increasing" (6.5%), or "early-onset, decreasing" (1.3%) spinal pain trajectories. The most common diagnoses in all trajectory groups were non-specific (e.g., "back pain"). Tissue-specific diagnoses (e.g., muscle strain) were less common and pathologies (e.g., fracture) were rare.  Conclusion: From childhood through adolescence, spinal pain was common and followed heterogeneous courses comprising stable, increasing, and early-onset trajectories. These findings accord with recommendations from adult back pain guidelines that most children with spinal pain can be reassured that they do not have a serious disease and encouraged to stay active. What is Known: • Spinal pain imposes a large burden on individuals and society. • Although many people first experience the condition in childhood, little is known about the developmental trajectories of spinal pain from childhood to adolescence. What is New: • Data from 1556 children and 329,756 participant weeks showed five unique spinal pain trajectories from 6 to 17 years: most children rarely reported spinal pain, while one in five followed increasing or early-onset trajectories. • Most pain occurrences were non-specific; pathological diagnoses were rare.

Factors Associated With Children Diagnosed With Attention-Deficit/Hyperactivity Disorder and 30-Day Follow-up Care With Practitioners Among Medicaid Recipients in Georgia.

BACKGROUND AND OBJECTIVES: It is important that children prescribed attention-deficit/hyperactivity disorder (ADHD) medication get timely follow-up care. In 2018, only 44% of US Medicaid recipients attended a follow-up visit within 30 days of their first ADHD prescription. The objective of this study was to identify the member and practitioner-related predictors that were associated with children who were diagnosed with ADHD and had a follow-up visit within 30 days (initiation phase) of their first prescription of ADHD medication (Index Prescription Start Date, or IPSD). METHODS: A cross-sectional study was conducted to identify the independent predictors of a follow-up visit within 30 days and 2 follow-up visits within 270 days after the initiation phase (continuation and maintenance phase, or C&M phase) for Medicaid recipients. Predictive factors examined included race, school age group, gender, geography of residence, Medicaid service region, newly diagnosed ADHD, hospital admission, emergency department (ED) visit, types of ADHD medication, other psychosocial or behavioral diagnoses, psychosocial or behavioral therapy, prescriber specialty, and school season. RESULTS: There were 2369 members eligible for the initiation phase measure, of whom 330 members were eligible for the C&M phase measure. Multiple regression analysis found that unmet 30-day follow-up was significantly associated with African American children with an existing diagnosis of ADHD (adjusted odds ratio [AOR] = 2.13; 95% confidence interval [CI], 1.64-2.76), middle school-aged children (AOR = 1.49; 95% CI, 1.23-1.80), rural residence (AOR = 1.27; 95% CI, 1.05-1.55), no ED visit (AOR = 1.57; 95% CI, 1.16-2.12), no psychosocial or behavioral therapy prior to the IPSD (AOR = 2.30; 95% CI, 1.65-3.21), and primary care practitioners (AOR = 1.88; 95% CI, 1.45-2.44). CONCLUSION: Pediatrics was the most common specialty prescribing ADHD medications. Managed care organizations can focus intervention efforts to improve compliance with 30-day follow-up among Medicaid children by targeting the high-risk categories identified above. They can also focus on facilitating communication between behavioral health practitioners and pediatricians about several key points: (1) the importance of using behavioral health therapy prior to prescribing medication; (2) the importance of timely follow-up care; and (3) the importance of medication management in combination with behavioral health therapy.

Trajectories of Opioid Coverage After Long-Term Opioid Therapy Initiation Among a National Cohort of US Veterans.

PURPOSE: The objective of this study was to identify the trajectories that patients take after initiating long-term opioid therapy (LTOT). MATERIALS AND METHODS: Using a retrospective cohort design, veterans with chronic non-cancer pain (CNCP) initiating LTOT were identified. Group-based trajectory models were used to identify opioid therapy trajectories based on days of opioid supply (primary outcome) and average daily morphine milligram equivalent dose (AMME; secondary outcome) in each 180-day period following initiation of LTOT. RESULTS: A total of 438,398 veterans with CNCP initiated LTOT. Nine trajectories were identified: 33.7% with persistent, high days covered, 17.7% with persistent, moderate days covered, 16.6% with slow, persistent days-covered reduction, 2.4% with days-covered reduction followed by increase, 4.6% with delayed days-covered reduction, 4.1% with rapid days-covered reduction, 10.9% with moderate-paced discontinuation, 3.4% with delayed discontinuation, and 6.5% with rapid discontinuation. Patients following discontinuation trajectories were more likely to be younger, persons of color, use more supportive services (eg, physical therapy), and received less opioid days' supply and lower doses prior to initiating LTOT as compared to patients following persistent opioid days-covered trajectories. AMME trajectories were similar to days-covered trajectories. CONCLUSION: Among persons initiating LTOT, nine opioid trajectories emerged which can be broadly characterized into three main trajectory groups: persistent opioid therapy (2 trajectories), reductions in opioid therapy (4 trajectories), and discontinuation (3 trajectories). A majority of patients (51.4%) maintained persistent opioid therapy. Further research is needed to assess the risks of opioid-related adverse outcomes among the identified trajectories.

Longitudinal Patterns of Pain Reporting Among Community-dwelling Older Adults.

OBJECTIVE: The objective of this study was to identify and describe long-term trajectories of bothersome pain and activity-limiting pain in a population-based sample of older adults. MATERIALS AND METHODS: We conducted a retrospective cohort study of 6783 community-dwelling participants using 6 years of longitudinal data from the National Health and Aging Trends Study (NHATS). NHATS is a cohort of older adults that is representative of Medicare Beneficiaries aged 65 years and older. NHATS data collection began in 2011, and demographic and health data are collected annually through in-person interviews. Participants were asked if they had bothersome pain and activity-limiting pain in the past month. We used group-based trajectory modeling to identify longitudinal patterns of bothersome pain and activity-limiting pain over 6 years. We used weighted, multinomial logistic regression to examine associations with each trajectory. RESULTS: The cohort was 57% female, 68% white, and 58% were 75 years and older. Four trajectories were identified for the probability of bothersome pain: persistently high (n=1901, 35%), increasing (n=898, 17%), decreasing (n=917, 17%), and low (n=1735, 32%). Similar trajectories were identified for activity-limiting pain: persistently high (n=721, 13%), increasing (n=812, 15%), decreasing (n=677, 12%), and low (n=3241, 60%). The persistently high bothersome and activity-limiting pain groups had worse health characteristics, were more likely to have fallen in the past year, and had slower gait speed and worse physical capacity compared with the low groups. DISCUSSION: Approximately one half of older adults had a high or increasing probability of long-term bothersome pain, and over one quarter had a high or increasing probability of long-term activity-limiting pain.

Suicidal ideation and aggression in childhood, genetic variation and young adult depression.

BACKGROUND: Suicidal thoughts and behaviors have been studied in association with a variety of risk factors. The aim of the present study was to determine if levels of child/adolescent aggression and/or variation in candidate genes previously associated with suicidal behaviors in adults would influence the presence of suicidal ideation in childhood/adolescence, and to determine if ideation was associated with young adult depression. METHODS: A longitudinal study of children, adolescents and young adults who were at high or low risk for alcohol and other substance use disorders by familial background were assessed. The Child Behavior Checklist (CBCL) aggression scale scores with derived subtypes (physical and relational) and genetic variation (ANKK1, DRD2, COMT, SLC6A4, HTR2C) were used as predictors of the presence and onset of suicidal ideation in childhood using survival analysis. Structural equation models (SEM) were fit to determine the relative importance of the predictors controlling for background variables. RESULTS: CBCL aggression was significantly associated with child/adolescent suicidal ideation. One SNP in the ANKK1 gene (rs1800497), one in the HTR2C gene (rs6318), and two haplotypes, AAAC in the ANKK1-DRD2 complex and the CCC haplotype of the HTR2C gene, were significantly associated with the presence and onset of child/adolescent suicidal ideation. Follow up in young adulthood showed a significant relationship between suicidal ideation in childhood/adolescence and young adult depression. CONCLUSIONS: Genetic variation and presence of elevated aggression scores from the childhood CBCL are significant predictors of childhood suicidal ideation. Suicidal ideation in childhood and being female are predictors of young adult depression.

Comparison of parametric and nonparametric methods for outcome prediction using longitudinal data after cardiac arrest.

INTRODUCTION: Predicting outcome after cardiac arrest is challenging. We previously tested group-based trajectory modeling (GBTM) for prognostication based on baseline characteristics and quantitative electroencephalographic (EEG) trajectories. Here, we describe implementation of this method in a freely available software package and test its performance against alternative options. METHODS: We included comatose patients admitted to a single center after resuscitation from cardiac arrest from April 2010 to April 2019 who underwent ≥6 h of EEG monitoring. We abstracted clinical information from our prospective registry and summarized suppression ratio in 48 hourly epochs. We tested three classes of longitudinal models: frequentist, statistically based GBTMs; non-parametric (i.e. machine learning) k-means models; and Bayesian regression. Our primary outcome of interest was discharge CPC 1-3 (vs unconsciousness or death). We compared sensitivity for detecting poor outcome at a false positive rate (FPR) <1%. RESULTS: Of 1,010 included subjects, 250 (25%) were awake and alive at hospital discharge. GBTM and k-means derived trajectories, group sizes and group-specific outcomes were comparable. Conditional on an FPR < 1%, GBTMs yielded optimal sensitivity (38%) over 48 h. More sensitive methods had 2-3 % FPRs. CONCLUSION: We explored fundamentally different tools for patient-level predictions based on longitudinal and time-invariant patient data. Of the evaluated methods, GBTM resulted in optimal sensitivity while maintaining a false positive rate <1%. The provided code and software of this method provides an easy-to-use implementation for outcome prediction based on GBTMs.

Classifying Patients with Amyotrophic Lateral Sclerosis by Changes in FVC. A Group-based Trajectory Analysis.

Rationale: A model for stratifying progression of respiratory muscle weakness in amyotrophic lateral sclerosis (ALS) would identify disease mechanisms and phenotypes suitable for future investigations. This study sought to categorize progression of FVC after presentation to an outpatient ALS clinic.Objectives: To identify clinical phenotypes of ALS respiratory progression based on FVC trajectories over time.Methods: We derived a group-based trajectory model from a single-center cohort of 837 patients with ALS who presented between 2006 and 2015. We applied our model to the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database with 7,461 patients with ALS. Baseline characteristics at first visit were used as predictors of trajectory group membership. The primary outcome was trajectory of FVC over time in months.Measurements and Main Results: We found three trajectories of FVC over time, termed "stable low," "rapid progressor," and "slow progressor." Compared with the slow progressors, the rapid progressors had shorter diagnosis delay, more bulbar-onset disease, and a lower ALS Functional Rating Scale-Revised (ALSFRS-R) total score at baseline. The stable low group had a shorter diagnosis delay, lower body mass index, more bulbar-onset disease, lower ALSFRS-R total score, and were more likely to have an ALSFRS-R orthopnea score lower than 4 compared with the slow progressors. We found that projected group membership predicted respiratory insufficiency in the PRO-ACT cohort (concordance statistic = 0.78, 95% CI, 0.76-0.79).Conclusions: We derived a group-based trajectory model for FVC progression in ALS, which validated against the outcome of respiratory insufficiency in an external cohort. Future studies may focus on patients predicted to be rapid progressors.

A novel methodological framework for multimodality, trajectory model-based prognostication.

INTRODUCTION: Prognostic tools typically combine several time-invariant clinical predictors using regression models that yield a single, time-invariant outcome prediction. This results in considerable information loss as repeatedly or continuously sampled data are aggregated into single summary measures. We describe a method for real-time multivariate outcome prediction that accommodates both longitudinal data and time-invariant clinical characteristics. METHODS: We included comatose patients treated after resuscitation from cardiac arrest who underwent ≥6 h of electroencephalographic (EEG) monitoring. We used Persyst v13 (Persyst Development Corp, Prescott AZ) to generate quantitative EEG (qEEG) features and calculated hourly summaries of whole brain suppression ratio and amplitude-integrated EEG. We randomly selected half of subjects as a training sample and used the other half as a test sample. We applied group-based trajectory modeling (GBTM) to the training sample to group patients based on qEEG evolution, then estimated the relationship of group membership and clinical covariates with awakening from coma and surviving to hospital discharge using logistic regression. We used these parameters to calculate posterior probabilities of group membership (PPGMs) in the test sample, and built three prognostic models: adjusted logistic regression (no GBTM), unadjusted GBTM (no clinical covariates) and adjusted GBTM (all data). We compared these models performance characteristics. RESULTS: We included 723 patients. Group-specific outcome estimates from a 7-group GBTM ranged from 0 to 75%. Compared to unadjusted GBTM, adjusted GBTM calibration was significantly improved at 6 and 12 h, and time to an outcome estimate <10% and <5% were significantly shortened. Compared to simple logistic regression, adjusted GBTM identified a substantially larger proportion of subjects with outcome probability <1%. CONCLUSIONS: We describe a novel methodology for combining GBTM output and clinical covariates to estimate patient-specific prognosis over time. Refinement of such methods should form the basis for new avenues of prognostication research that minimize loss of clinically important information.

Patterns of antihypertensive and statin adherence prior to dementia: findings from the adult changes in thought study.

BACKGROUND: Detecting patients with undiagnosed dementia is an important clinical challenge. Changes in medication adherence might represent an early sign of cognitive impairment. We sought to examine antihypertensive and statin adherence trajectories in community-dwelling older adults, comparing people who went on to develop dementia to those who did not. METHODS: We analyzed data from Adult Changes in Thought (ACT), a population-based cohort study embedded within an integrated healthcare delivery system. Analyses included 4368 participants aged ≥65 years who had at least one follow-up visit. Research-quality dementia diagnoses were used to identify cases. We selected non-dementia control visits matched on age, sex, and study cohort that occurred at similar ACT follow-up time as the case's dementia onset; we treated this as the index date. Participants were included if they were prevalent users of either a statin or antihypertensive medication on the first day of follow up - 3 years prior to the index date. Using prescription fill dates and days supply, we calculated daily binary medication availability measures for each participant ('days covered') over 3 years leading up to the index date. We used group-based trajectory models to identify patterns of antihypertensive and statin adherence, and used conditional logistic regression to examine associations between adherence trajectories and dementia. RESULTS: Four trajectories were identified for antihypertensive users (292 cases, 3890 control visits), including near perfect (n = 1877, 36.6% cases, 45.5% controls), high (n = 1840, 43.2% cases, 44.1% controls), moderate (n = 365, 18.5% cases, 8.0% controls) and early poor adherence (n = 100, 1.7% cases, 2.4% controls). Odds of dementia was 3 times greater for those with moderate antihypertensive adherence compared to those with near perfect adherence (adjusted OR 3.0, 95% CI 2.0, 4.3). Four trajectories were identified for statin users (148 cases, 1131 control visits), including high (n = 1004, 75.0% cases, 79.0% controls), moderate (n = 192, 19.6% cases, 14.4% controls), early poor (n = 43, 2.0% cases, 3.5% controls), and delayed poor adherence (n = 40, 3.4% cases, 3.1% controls). No association was detected between statin adherence trajectories and dementia. CONCLUSIONS: Patterns of medication adherence may be useful to identify a subset of people at higher likelihood of developing dementia.

Adherence trajectories of buprenorphine therapy among pregnant women in a large state Medicaid program in the United States.

PURPOSE: Little is known about the longitudinal patterns of buprenorphine adherence among pregnant women with opioid use disorder, especially when late initiation, nonadherence, or early discontinuation of buprenorphine during pregnancy may increase the risk of adverse outcomes. We aimed to identify distinct trajectories of buprenorphine use during pregnancy, and factors associated with these trajectories in Medicaid-enrolled pregnant women. METHODS: A retrospective cohort study included 2361 Pennsylvania Medicaid enrollees aged 15 to 46 having buprenorphine therapy during pregnancy and a live birth between 2008 and 2015. We used group-based trajectory models to identify buprenorphine use patterns in the 40 weeks prior to delivery and 12 weeks postdelivery. Multivariable multinomial logistic regression models were used to identify factors associated with specific trajectories. RESULTS: Six distinct trajectories were identified. Four groups initiated buprenorphine during the first trimester of the pregnancy (early initiators): 31.6% with persistently high adherence, 15.1% with moderate-to-high adherence, 10.5% with declining adherence, and 16.7% with early discontinuation. Two groups did not initiate buprenorphine until midsecond or third trimester (late initiators): 13.5% had moderate-to-high adherence and 12.6% had low-to-moderate adherence. Factors significantly associated with late initiation and discontinuation were younger age, non-white race, residents of rural counties, fewer outpatient visits, more frequent emergency department visits and hospitalizations, and lower buprenorphine daily dose. CONCLUSIONS: Six buprenorphine treatment trajectories during pregnancy were identified in this population-based Medicaid cohort, with 25% of women initiating buprenorphine late during pregnancy. Understanding trajectories of buprenorphine use and factors associated with discontinuation/nonadherence may guide integration of behavioral treatment with obstetrical/gynecological care to improve buprenorphine treatment during pregnancy.