SEARCH · Search PubMed

Results for “linear mixed model”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16Linked to original sources

PubMed2005

Random-effects models in investigating the effect of vitamin A in childhood diarrhea.

PURPOSE: By adopting more appropriate and powerful statistical methods that fully exploit longitudinal structure, we re-analyze and extend previously published results from a large community trial to investigate the effect of vitamin A supplementation on the prevalence and severity of diarrhea in young children. METHODS: Generalized linear mixed models were used to allow for repeated measures in a reanalysis of a double-blind, randomized, placebo-controlled community trial conducted in a cohort of children in northeastern Brazil during 1 year. The response variable was weekly number of days with diarrhea for each child, and Markov Chain Monte Carlo methods were used to estimate model parameters. RESULTS AND CONCLUSIONS: Random effects suitably accounted for the underlying heterogeneity between and within children, and our longitudinal analysis shows a significant beneficial effect of vitamin A supplementation that was inconclusive in previously reported simple summary analyses of these data. Risk for diarrhea infection was estimated to be 1.57 times greater for a child administered a placebo as opposed to vitamin A (95% credible interval, 1.17-2.12). Additionally, we identified previously unreported temporal effects in these data, showing a decreasing daily probability of diarrhea for both groups during the trial and treatment-time interaction.

Bayes Theorem↗

PubMed2003

Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study.

The relationship between elevated blood pressure and cardiovascular and cerebrovascular disease risk is well accepted. Both systolic and diastolic hypertension are associated with this risk increase, but systolic blood pressure appears to be a more important determinant of cardiovascular risk than diastolic blood pressure. Subjects for this study are derived from the Framingham Heart Study data set. Each subject had five records of clinical data of which systolic blood pressure, age, height, gender, weight, and hypertension treatment were selected to characterize the phenotype in this analysis. We modeled systolic blood pressure as a function of age using a mixed modeling methodology that enabled us to characterize the phenotype for each individual as the individual's deviation from the population average rate of change in systolic blood pressure for each year of age while controlling for gender, body mass index, and hypertension treatment. Significant (p = 0.00002) evidence for linkage was found between this normalized phenotype and a region on chromosome 1. Similar linkage results were obtained when we estimated the phenotype while excluding values obtained during hypertension treatment. The use of linear mixed models to define phenotypes is a methodology that allows for the adjustment of the main factor by covariates. Future work should be done in the area of combining this phenotype estimation directly with the linkage analysis so that the error in estimating the phenotype can be properly incorporated into the genetic analysis, which, at present, assumes that the phenotype is measured (or estimated) without error.

Age Factors↗

PubMed2004

Prognostic factors for alveolar regeneration: bone formation at teeth and titanium implants.

OBJECTIVES: There is a limited understanding of the effect of defect characteristics on alveolar bone healing. The objectives of this study were to assess the effect of alveolar bone width and space provision on bone regeneration at teeth and titanium implants, and to test the hypothesis that the regenerative potentials at teeth and implants are not significantly different. METHODS: Critical size, 5-6-mm, supra-alveolar, periodontal defects were surgically created in 10 young adult dogs. Similarly, critical size, 5-mm, supra-alveolar, peri-implant defects were created in four dogs. A space-providing expanded polytetrafluoroethylene device was implanted for guided tissue regeneration/guided bone regeneration. The animals were euthanized at 8 weeks postsurgery. Histometric analysis assessed alveolar bone regeneration (height) relative to space provision by the device and the width of the alveolar crest at the base of the defect. Statistical analysis used the linear mixed models. RESULTS: A significant correlation was found between bone width and wound area (r=0.55892, p<0.0001). Generally, bone width and wound area had statistically significant effects on the extent of bone regeneration (p<0.0005 and p<0.0001, respectively). Bone regeneration was linearly correlated with the bone width at periodontal (p<0.001) and implant (p=0.04) sites, and with the wound area at periodontal (p<0.0001) and implant (p=0.03) sites. The relationships of bone regeneration with these two variables were not significantly different between teeth and implants (bone width: p=0.83; wound area: p=0.09). When adjusted for wound area, bone regeneration was significantly greater at periodontal than at implant sites (p=0.047). CONCLUSIONS: The horizontal dimension of the alveolar bone influences space provision. Space provision and horizontal dimension of the alveolar bone appear to be important determinants of bone regeneration at teeth and implants. The extent of alveolar bone formation at implant sites is limited compared with that at periodontal sites.

Alveolar Bone Loss↗

PubMed2004

Evaluation of a group-based substance abuse treatment program for adolescents.

The effectiveness of adolescent substance abuse treatment has been repeatedly demonstrated, but specific treatment approaches have rarely been sufficiently documented to permit replication. This study evaluated the effectiveness of a manual-guided, outpatient, group-based treatment program for adolescents (N = 194) who were mild-to-moderate substance abusers. In addition to evaluating the group-based treatment model, the study was designed to compare the effectiveness of two approaches to preparing youth to engage in treatment, whereby adolescents received one of two types of treatment induction, either motivational interviewing or counseling overview. Self-reported pretreatment substance use and criminal behaviors were compared with these behaviors 6 and 12 months following treatment entry using a General Linear Mixed Model analytic approach that controlled for the effects of potential confounding variables and examined individual and program factors that might explain treatment response. Participants significantly reduced marijuana use at 6 months, and these reductions were largely sustained at 12 months. No changes in alcohol use or criminal involvement were obtained. Further examination of marijuana use indicated differential treatment response based on participants' emotional abuse history, family satisfaction, school adjustment, and pretreatment substance use frequency. This treatment approach appears promising for marijuana-abusing youth.

Adolescent↗

PubMed2005

A hierarchical Binomial-Poisson model for the analysis of a crossover design for correlated binary data when the number of trials is dose-dependent.

The differential reinforcement of a low-rate 72-seconds schedule (DRL-72) is a standard behavioral test procedure for screening a potential antidepressant compound. The data analyzed in the article are binary outcomes from a crossover design for such an experiment. Recently, Shkedy et al. (2004) proposed to estimate the treatments effect using either generalized linear mixed models (GLMM) or generalized estimating equations (GEE) for clustered binary data. The models proposed by Shkedy et al. (2004) assumed the number of responses at each binomial observation is fixed. This might be an unrealistic assumption for a behavioral experiment such as the DRL-72 because the number of responses (the number of trials in each binomial observation) is expected to be influenced by the administered dose level. In this article, we extend the model proposed by Shkedy et al. (2004) and propose a hierarchical Bayesian binomial-Poisson model, which assumes the number of responses to be a Poisson random variable. The results obtained from the GLMM and the binomial-Poisson models are comparable. However, the latter model allows estimating the correlation between the number of successes and number of trials.

Algorithms↗

PubMed2006

Disconnect between inflammation and joint destruction after treatment with etanercept plus methotrexate: results from the trial of etanercept and methotrexate with radiographic and patient outcomes.

OBJECTIVE: To determine the relationship between disease activity and radiographic progression of joint destruction in patients with rheumatoid arthritis (RA) treated with methotrexate (MTX), those treated with etanercept, and those treated with the combination of MTX plus etanercept. METHODS: Baseline, 12-month, and 24-month data from the Trial of Etanercept and Methotrexate with Radiographic and Patient Outcomes database were analyzed. The dependent variable was the 1-year change in the modified Sharp/van der Heijde score (Sharp score); therefore, 2 interval changes per patient were available. Interval change in the Sharp score was modeled by time (years), treatment, disease activity, and the interaction (disease activity x treatment). Disease activity was reflected by the time-averaged Disease Activity Score (taDAS) and the time-averaged C-reactive protein (taCRP) level, which were calculated per 1-year interval. Generalized mixed linear modeling (GMLM) was used to adjust for within-patient correlation. RESULTS: GMLM confirmed a significant interaction between treatment and the taCRP level and taDAS with respect to the change in Sharp score (P = 0.012 and P = 0.03, respectively). In patients treated with MTX alone, radiographic progression increased with an increasing taCRP level or taDAS, although progression rates were low in patients whose disease was in remission and in those with low-to-moderate disease activity. This relationship was less clear in patients treated with etanercept and was absent in those who received combination therapy. CONCLUSION: Combination therapy with MTX plus etanercept uncouples the classic relationship between disease activity and radiographic progression in patients with RA.

Antirheumatic Agents↗

PubMed2000

Evaluation of pseudoenhancement of renal cysts during contrast-enhanced CT.

OBJECTIVE: The purpose of our study was to evaluate renal cyst pseudoenhancement during helical CT in a phantom model and in patients. MATERIALS AND METHODS: Iodine baths containing water-filled spheres and cylinders were constructed to simulate cysts in enhancing renal parenchyma. Iodine concentration, cyst size and location, collimation, and peak kilovoltage were varied and cyst attenuation was measured. Data were analyzed with the mixed linear models and Mantel-Haenszel tests. Subsequently, a paired t test compared CT attenuation values before and after contrast material enhancement in 40 patients with 68 renal cysts (radiographic stability >3 months). RESULTS: The attenuation values of phantom cysts increased when placed in a contrast media bath (p = 0.001). The increase in attenuation values became more pronounced with increasing iodine concentrations, decreasing peak kilovoltage, and smaller sphere sizes. In patients, mean cyst attenuation increased 3.4 +/- 6.2 H after administration of contrast material (p = 0.00002). The attenuation did not increase more than 10 H in any of the 37 cysts larger than 2 cm found in patients. Eight (26%) of the 31 cysts smaller than 2 cm found in patients increased by at least 10 H. CONCLUSION: In a phantom model, at simulated physiologic levels of renal enhancement, cysts may pseudoenhance by more than 10 H. Similarly, in patients, cysts may also pseudoenhance; however, most pseudoenhancement does not exceed 10 H. In patients, pseudoenhancement of at least 10 H is more likely in cysts smaller than 2 cm.

Humans↗

PubMed2005

A Bayesian threshold-normal mixture model for analysis of a continuous mastitis-related trait.

Mastitis is associated with elevated somatic cell count in milk, inducing a positive correlation between milk somatic cell score (SCS) and the absence or presence of the disease. In most countries, selection against mastitis has focused on selecting parents with genetic evaluations that have low SCS. Univariate or multivariate mixed linear models have been used for statistical description of SCS. However, an observation of SCS can be regarded as drawn from a 2- (or more) component mixture defined by the (usually) unknown health status of a cow at the test-day on which SCS is recorded. A hierarchical 2-component mixture model was developed, assuming that the health status affecting the recorded test-day SCS is completely specified by an underlying liability variable. Based on the observed SCS, inferences can be drawn about disease status and parameters of both SCS and liability to mastitis. The prior probability of putative mastitis was allowed to vary between subgroups (e.g., herds, families), by specifying fixed and random effects affecting both SCS and liability. Using simulation, it was found that a Bayesian model fitted to the data yielded parameter estimates close to their true values. The model provides selection criteria that are more appealing than selection for lower SCS. The proposed model can be extended to handle a wide range of problems related to genetic analyses of mixture traits.

Animals↗

PubMed2006

Continuous time Markov models for binary longitudinal data.

Longitudinal data usually consist of a number of short time series. A group of subjects or groups of subjects are followed over time and observations are often taken at unequally spaced time points, and may be at different times for different subjects. When the errors and random effects are Gaussian, the likelihood of these unbalanced linear mixed models can be directly calculated, and nonlinear optimization used to obtain maximum likelihood estimates of the fixed regression coefficients and parameters in the variance components. For binary longitudinal data, a two state, non-homogeneous continuous time Markov process approach is used to model serial correlation within subjects. Formulating the model as a continuous time Markov process allows the observations to be equally or unequally spaced. Fixed and time varying covariates can be included in the model, and the continuous time model allows the estimation of the odds ratio for an exposure variable based on the steady state distribution. Exact likelihoods can be calculated. The initial probability distribution on the first observation on each subject is estimated using logistic regression that can involve covariates, and this estimation is embedded in the overall estimation. These models are applied to an intervention study designed to reduce children's sun exposure.

Biometry↗

PubMed2005

The optimal analysis of MRI data to quantify the distribution of a microbicide.

OBJECTIVE: The objective of this study was to systematically review the use of MRI for the evaluation of deployment characteristics of vaginal microbicides and to understand the relationship of gel spread with potential influencing factors. METHODS: Data from four clinical trials that used MRI to assess the deployment of a vaginal gel were combined. A linear mixed model best represented the spread of gel over time. Significant covariates that influence vaginal gel spread are baseline dimensions of the vagina, time from insertion, gel type, ambulation and volume of gel. RESULTS: These data demonstrate that MRI has outstanding intraperson validity and reproducibility. Therefore, paired design, using linear modeling adjusting for significant covariates, is the most efficient study design for comparison of products or volumes. Division of the vagina into two distinct anatomical regions best explains difference in gel spread, i.e., upper area (above the pelvic diaphragm) and lower area (below pelvic diaphragm). CONCLUSION: We conclude that the concept of spread from the cervix to the introits, in one dimension, is inadequate to explain spread of gel due to the complex shape of the vagina.

Adolescent↗

PubMed2003

Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling.

This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time. Generalized linear mixed models were fitted using Gibbs sampling in WinBUGS, and the additive polygenic random effects estimated using these models were then used as continuous phenotypes in a variance components linkage analysis. The first-stage analysis provided evidence for general genetic effects on both the baseline and slope of blood pressure, and the linkage analysis found evidence of several genes, again for both baseline and slope.

Adult Children↗

PubMed2006

Estimation of dynamical model parameters taking into account undetectable marker values.

BACKGROUND: Mathematical models are widely used for studying the dynamic of infectious agents such as hepatitis C virus (HCV). Most often, model parameters are estimated using standard least-square procedures for each individual. Hierarchical models have been proposed in such applications. However, another issue is the left-censoring (undetectable values) of plasma viral load due to the lack of sensitivity of assays used for quantification. A method is proposed to take into account left-censored values for estimating parameters of non linear mixed models and its impact is demonstrated through a simulation study and an actual clinical trial of anti-HCV drugs. METHODS: The method consists in a full likelihood approach distinguishing the contribution of observed and left-censored measurements assuming a lognormal distribution of the outcome. Parameters of analytical solution of system of differential equations taking into account left-censoring are estimated using standard software. RESULTS: A simulation study with only 14% of measurements being left-censored showed that model parameters were largely biased (from -55% to +133% according to the parameter) with the exception of the estimate of initial outcome value when left-censored viral load values are replaced by the value of the threshold. When left-censoring was taken into account, the relative bias on fixed effects was equal or less than 2%. Then, parameters were estimated using the 100 measurements of HCV RNA available (with 12% of left-censored values) during the first 4 weeks following treatment initiation in the 17 patients included in the trial. Differences between estimates according to the method used were clinically significant, particularly on the death rate of infected cells. With the crude approach the estimate was 0.13 day-1 (95% confidence interval [CI]: 0.11; 0.17) compared to 0.19 day-1 (CI: 0.14; 0.26) when taking into account left-censoring. The relative differences between estimates of individual treatment efficacy according to the method used varied from 0.001% to 37%. CONCLUSION: We proposed a method that gives unbiased estimates if the assumed distribution is correct (e.g. lognormal) and that is easy to use with standard software.

AIDS-Related Opportunistic Infections↗

PubMed2005

Missing forms and dropout in the TME quality of life substudy.

OBJECTIVE: Missing forms may pose problems in health related quality of life (QOL) studies, because the absence of a QOL measure may be related to the patient's health and hence to the patient's QOL itself. Studying patterns of missingness, dropout, and the possible impact of missing data on QOL measures is an important step in reporting outcomes of QOL studies. We study patterns of dropout and evaluate the impact of missing forms in the TME QOL substudy. METHODS: Patients with rectal cancer, randomized to receive either radiotherapy plus total mesorectal excision (TME) or TME only were included in the TME trial. QOL was evaluated in 1302 Dutch patients, before treatment, and 3, 6, 12, 18 and 24 months after surgery. Here only the visual analogue score (VAS) was studied. RESULTS: At baseline, differences between VAS scores were found with respect to whether the QOL forms were dated before or after radiotherapy and surgery. Differences were small between different statistical methods accounting for dropout; only a cross-sectional analysis gave biased results. CONCLUSION: The results of the sensitivity analysis indicated that a linear mixed model analysis is a reliable and attractive approach for this study.

Analysis of Variance↗

PubMed2005

Analysis of interval-censored longitudinal data with application to onco-haematology.

The analysis of repeated measurements on a biomarker, either alone or jointly with the analysis of time to the event of interest, is an area of active research. Nevertheless, we are not yet able to deal in complete generality with these complex data, which frequently consist of error-prone, sparse and intermittent values. In many cancer studies, they arise in the framework of clinical trials and thus their relationship with prognosis is a primary focus. In such a setting, the Cox model is regarded as the standard technique for analysis. The aim of this work is to illustrate an alternative approach to the analysis of studies in which the biomarker values are complicated by interval censoring and an event occurs when the biomarker itself passes a certain threshold. We propose a linear mixed model with a Gaussian stochastic process that allows for interval-censored data and can be used both to track the biomarker trajectory and to estimate the probability of event occurrence. It is developed within the classic approach to longitudinal data analysis that was previously adapted for left-censored data, only. We apply this method to a study on the minimal residual disease (MRD) in childhood leukaemia. MRD is an interval-censored measurement of residual leukaemic cells that was scheduled at 9 time-points during treatment. The aim is to investigate the relationship between MRD and the disease process. Relapse, the event of interest, may conveniently be represented as MRD over a pre-defined threshold. Our focus is on modelling the probability of relapse conditional on MRD observed prior to it. Results show that the approach is promising as it allows proper description of the data, while maintaining flexibility of modelling, feasibility of computations and interpretability of results.

Biomarkers↗

PubMed1997

Pit-1 gene polymorphism, milk yield, and conformation traits for Italian Holstein-Friesian bulls.

The growth hormone factor-1/pituitary-specific transcription factor Pit-1 is responsible for the expression of growth hormone in mammals. Mutations in Pit-1 have been found in growth hormone disorders of mice and humans. We studied the eventual association between Pit-1 polymorphism using the HinfI enzyme and the milk yield and conformation traits of 89 Italian Holstein-Friesian bulls. A strategy employing polymerase chain reaction was used to amplify a 451-bp fragment from semen DNA. Digestion of polymerase chain reaction products with HinfI revealed two alleles: allele A was not digested (451-bp fragment), and allele B was cut at one restriction site, generating two fragments of 244 and 207 bp. Three patterns were observed; frequencies were 2.2, 31.5, and 66.3% for AA, AB, and BB, respectively. Fixed and mixed linear models were fitted on daughter yield deviations for milk yields and on deregressed proofs for conformation traits. Predictions were weighted using the inverse of the estimated variance of records. The models used contained mean and gene substitution effects for Pit-1 A allele as fixed effects and random sire effect for the mixed model. The A allele was found to be superior for milk and protein yields, inferior for fat percentage, and superior for body depth, angularity, and rear leg set, which is difficult to explain. A canonical transformation revealed that Pit-1 had three actions, one linked to milk yield traits and angularity, a second linked to body depth and rear leg set, and a third linked to lower fat yields and to higher angularity.

Animals↗

PubMed2000

Impact of HMO market structure on physician-hospital strategic alliances.

OBJECTIVE: To assess the impact of HMO market structure on the formation of physician-hospital strategic alliances from 1993 through 1995. The two trends, managed care and physician-hospital integration have been prominent in reshaping insurance and provider markets over the past decade. STUDY DESIGN: Pooled cross-sectional data from the InterStudy HMO Census and the Annual Survey conducted by the American Hospital Association (AHA) between 1993 and the end of 1995 to examine the effects of HMO penetration and HMO numbers in a market on the formation of hospital-sponsored alliances with physicians. Because prior research has found nonlinear effects of HMOs on a variety of dependent variables, we operationalized HMO market structure two ways: using a Taylor series expansion and cross-classifying quartile distributions of HMO penetration and numbers into 16 dummy indicators. Alliance formation was operationalized using the presence of any alliance model (IPA, PHO, MSO, and foundation) and the sum of the four models present in the hospital. Because managed care and physician-hospital integration are endogenous (e.g., some hospitals also sponsor HMOs), we used an instrumental variables approach to model the determinants of HMO penetration and HMO numbers. These instruments were then used with other predictors of alliance formation: physician supply characteristics, the extent of hospital competition, hospital-level descriptors, population size and demographic characteristics, and indicators for each year. All equations were estimated at the MSA level using mixed linear models and first-difference models. PRINCIPAL FINDINGS: Contrary to conventional wisdom, alliance formation is shaped by the number of HMOs in the market rather than by HMO penetration. This confirms a growing perception that hospital-sponsored alliances with physicians are contracting vehicles for managed care: the greater the number of HMOs to contract with, the greater the development of alliances. The models also show that alliance formation is low in markets where a small number of HMOs have deeply penetrated the market. First-difference models further show that alliance formation is linked to HMO consolidation (drop in the number of HMOs in a market) and hospital downsizing. Alliance formation is not linked to changes in hospital costs, profitability, or market competition with other hospitals. CONCLUSIONS: Hospitals appear to form alliances with physicians for several reasons. Alliances serve to contract with the growing number of HMOs, to pose a countervailing bargaining force of providers in the face of HMO consolidation, and to accompany hospital downsizing and restructuring efforts. IMPLICATIONS FOR POLICY, DELIVERY, OR PRACTICE: Physician-hospital integration is often mentioned as a provider response to increasing cost-containment pressures due to rising managed care penetration. Our findings do not support this view. Alliances appear to serve the hospital's interest in bargaining with managed care plans on a more even basis.

Delivery of Health Care, Integrated↗

PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗

PubMed2006

Modeling prostate specific antigen kinetics in patients on active surveillance.

PURPOSE: Prostate specific antigen doubling time was used to stratify patients into groups at low and high risk for progression. The prostate specific antigen kinetics in these 2 groups were modeled. MATERIALS AND METHODS: In this prospective, single-arm cohort study patients with favorable clinical parameters (stage T1b-T2b N0M0, Gleason score 7 or less, prostate specific antigen 15 ng/ml or less) were conservatively treated with watchful waiting. Evolution of serial prostate specific antigen measurements over time was estimated from a general linear mixed model of the natural log of prostate specific antigen. The corresponding average and individual prostate specific antigen doubling times were also calculated. RESULTS: Since November 1995 a total of 231 patients had at least 6 months of followup and at least 3 prostate specific antigen measurements. Based on prostate specific antigen doubling time and repeat biopsy, 93 patients fulfilled the criteria for high risk of disease progression and 138 were defined as low risk. Given the baseline status of these individuals, 2 reference average lines (high risk and low risk) were derived to model the evolution of prostate specific antigen levels and permit more rational decision making regarding the need for definitive intervention. The average prostate specific antigen doubling time was 2.97 years (95% CI 2.2-4.4) in patients allocated to the high risk group and 6.54 years (95% CI 4.8-12.3) in those at low risk. CONCLUSIONS: By applying the dynamic prognostic rule in combination with serial biopsy, a rational decision for definitive intervention based on the risk of disease progression could be optimally recommended about 2.3 years after initiated surveillance.

Aged↗