Pretreatment Variables (pretreatment + variable)

Distribution by Scientific Domains


Selected Abstracts


Factors predictive of 5-year survival after transarterial chemoembolization for inoperable hepatocellular carcinoma,

BRITISH JOURNAL OF SURGERY (NOW INCLUDES EUROPEAN JOURNAL OF SURGERY), Issue 3 2003
C. B. O'Suilleabhain
Background: Transarterial chemoembolization (TACE) is widely used for unresectable hepatocellular carcinoma (HCC), but the long-term survival benefit remains unclear. Methods: Pretreatment variables were analysed for factors predictive of actual 5-year survival from a prospective database of patients with inoperable HCC treated by TACE between 1989 and 1996. Results: Complete 5-year follow-up (median 91 months) was obtained for 320 patients who underwent a median of 4 (range 1,41) TACEs. Median tumour size was 9 (range 1,28) cm. There were 25 5-year survivors (8 per cent), including eight with tumours larger than 10 cm in diameter and three with portal vein branch involvement. On univariate analysis, female gender (P = 0·037), absence of ascites (P = 0·028), platelet count below 150 ×109 per litre (P = 0·011), albumin concentration greater than 35 g/l (P = 0·04), ,-fetoprotein level below 1000 ng/ml (P = 0·007), unilobar tumour (P = 0·027), fewer than three tumours (P = 0·015), absence of venous invasion (P = 0·011), and tumour diameter less than 8 cm (P = 0·021) were significant predictors of 5-year survival. Albumin concentration greater than 35 g/l (P = 0·011), unilobar tumour (P = 0·012) and ,-fetoprotein level below 1000 ng/ml (P = 0·014) were independent prognostic factors on multivariate analysis. Conclusion: Five-year survival is possible with TACE for inoperable HCC, even in some patients with advanced tumours. Unilobar tumours, ,-fetoprotein level below 1000 ng/ml and albumin concentration greater than 35 g/l were factors predictive of 5-year survival. Copyright © 2003 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd. [source]


Empirical-likelihood-based difference-in-differences estimators

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 2 2008
Jing Qin
Summary., Recently there has been a surge in econometric and epidemiologic works focusing on estimating average treatment effects under various sets of assumptions. Estimation of average treatment effects in observational studies often requires adjustment for differences in pretreatment variables. Rosenbaum and Rubin have proposed the propensity score method for estimating the average treatment effect by adjusting pretreatment variables. In this paper, the empirical likelihood method is used to estimate average treatment effects on the treated under the difference-in-differences framework. The advantage of this approach is that the common marginal covariate information can be incorporated naturally to enhance the estimation of average treatment effects. Compared with other approaches in the literature, the method proposed can provide more efficient estimation. A simulation study and a real economic data analysis are presented. [source]


Poor radiotherapy compliance predicts persistent regional disease in advanced head/neck cancer,

THE LARYNGOSCOPE, Issue 3 2009
Urjeet A. Patel MD
Abstract Objective: To determine if poor compliance to chemoradiation results in an increased rate of persistent neck disease. Study Design: Retrospective, cohort study in an urban, tertiary-care medical center. Methods: The study included patients with N+ stage III/IV squamous cell carcinoma of the upper aerodigestive tract treated with curative-intent chemoradiation, who underwent subsequent planned neck dissection. Main outcome measure was persistent regional disease evidenced by identifiable carcinoma in neck dissection specimens. Variables including age, gender, race, primary site, initial T, N staging, imaging results, and treatment compliance were assessed and correlated to positive neck dissection pathology. Results: Of 40 patients, 18 (45%) had persistent carcinoma in neck dissection specimens while 22 (55%) demonstrated complete response in the neck. There were 14 patients (35%) who were poorly compliant to radiotherapy (,14 days treatment interruption) and the remaining 26 patients (65%) were considered compliant (<14 missed days). Only 23% of compliant patients had positive pathology while 79% of noncompliant patients had positive pathology (hazard ratio: 9.9). Noncompliance was the only variable that had a statistically significant correlation to positive pathology results (P = .002). Multivariate logistic regression showed all other variables to be insignificant in predicting pathology. Conclusions: This study found that poorly compliant patients are at significantly higher risk of persistent neck disease. Poor compliance may help identify patients who will most benefit from neck dissection after chemoradiation. This variable was more predictive than pretreatment variables and posttreatment CT scan. Further studies investigating patterns of failure after chemoradiotherapy in the poorly compliant patient population are warranted. Laryngoscope, 2009 [source]


An interinstitutional and interspecialty comparison of treatment outcome data for patients with prostate carcinoma based on predefined prognostic categories and minimum follow-up,

CANCER, Issue 10 2002
Frank A. Vicini M.D.
Abstract BACKGROUND The optimal management of patients with clinically localized prostate carcinoma remains undefined due in part to the absence of well-designed, prospective, randomized trials. The current study was conducted to compare and contrast outcomes with different forms of therapy for patients with prostate carcinoma who were treated at several institutions using predefined prognostic categories. METHODS A retrospective study of 6877 men with prostate carcinoma who were treated between 1989 and 1998 at 7 different institutions with 6 different types of therapy was conducted. Five-year actuarial rates of prostate specific antigen (PSA) failure were calculated based on predefined prognostic categories, which included combinations of pretreatment PSA level, tumor stage, and Gleason score. In addition, outcome was calculated using consistent biochemical failure definitions and a minimum, median length of follow-up. RESULTS Substantial differences in outcome were observed for the same type of treatment and at the same institution, depending on the number of prognostic variables used to define treatment groups. However, estimates of 5-year PSA outcomes after all forms of therapy for low-risk and intermediate-risk patient groups were remarkably similar (regardless of the type of treatment) when all three pretreatment variables were used to define prognostic categories. For patients in high-risk groups, the 5-year PSA outcomes were suboptimal, regardless of the treatment technique used. CONCLUSIONS The current data suggest that interinstitutional and interspecialty comparisons of treatment outcome for patients with prostate carcinoma are possible but that results must be based on all major prognostic variables to be meaningful. Analyzed in this fashion, 5-year PSA results were similar for patients in low-risk and intermediate-risk groups, regardless of the form of therapy. Findings from prospective, randomized trials using survival (cause specific and overall) as the end point for judging treatment efficacy and longer follow-up will be needed to validate these findings and to identify the most appropriate management option for patients with all stages of disease. Cancer 2002;95:2126,35. © 2002 American Cancer Society. DOI 10.1002/cncr.10919 [source]


Psychological Treatment and Medication for the Mood and Anxiety Disorders: Moderators, Mediators, and Domains of Outcome

CLINICAL PSYCHOLOGY: SCIENCE AND PRACTICE, Issue 1 2005
David J. MiklowitzArticle first published online: 11 MAY 200
Studies that combine pharmacotherapy with psychological treatment for the mood and anxiety disorders must consider the role of moderators (pretreatment variables that specify the conditions under which treatments are effective) and mediators (change mechanisms in the causal pathways between treatments and outcomes) in explaining the impact of experimental treatments. This article gives examples of the kinds of moderators and mediators,both psychosocial and biological,that are important to examine in combination treatment studies. It conceptualizes outcome as involving multiple domains, including mood and anxiety symptoms, life functioning, and illness costs. Research should also examine the appropriate sequencing of pharmacological and psycho-social interventions and how this sequencing may vary from disorder to disorder. [source]