A multinational phase III adjuvant study of immediate (I) versus deferred (D) chemotherapy (C)/hormone therapy (HT) after radical prostatectomy (RP): TAX-3501.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 4570-4570 ◽  
Author(s):  
Mario A. Eisenberger ◽  
Michael W. Kattan ◽  
Cora N. Sternberg ◽  
Ronald De Wit ◽  
Jonathan I Epstein ◽  
...  
Keyword(s):  
Type I Error ◽  
Systemic Treatment ◽  
Small Sample Size ◽  
Small Sample ◽  
Phase Iii ◽  
Type I ◽  
Grade 5 ◽  
Predicted Probability ◽  
Phase Iii Study ◽  
Central Pathology

4570 Background: TAX 3501 was designed to test I or D C/HT after RP. No adequately designed prospectively randomized surgical systemic adjuvant studies have ever been successfully completed. Methods: TAX-3501 was a randomized phase III study. Eligibility included post-operative predicted probability of 5-year freedom from progression of <60% (Kattan et al) after central pathology review, no prior C/HT, undetectable PSA, M0, normal hematology/chemistries, signed consent. Pts were randomized within 120 days after RP to I or D (at 1st progression) Rx with HT (leuprolide acetate 22.5mg S.C. q.3 months x 6 ) +/- C (docetaxel 75mg/m2 q.3wks x 6). F/U included a physical exam, PSA, CBC/chemical profile, serum T, scans yearly or at progression (PSA≥ 0.4ng/ml, clinical or radiographic and death). Main objectives comparing PFS and 5-year progression-free rates after systemic treatment (2 × 2 factorial design, 4 arms). 1,696 subjects would provide 90% power to detect the targeted treatment effect at a 5% 2-sided type I error level. Results: From 12/2005-9/2007399 pts were registered, 228 randomized after central path review ICHT=55, IHT=55, DCHT=56, DHT=62, median age 62 (41-76), pre-op PSA (ng/ml) 9.38 (2.2 - 90.0), Gleason score- 8,T3a (19.6%),R+(65%),S.V.+(50%),N+(19.7%%), all had undetectable post op PSA. Predicted probability of no progression was 21% on 228pts. Study was terminated by sponsor (9/2007) due to poor accrual F/U continued from 2007-2010. Small sample size precludes reliable analyzes 37/118 (31.3%) on the D arms received CHT/HT (all PSA progressions); ICHT 10/55, IHT 14/55, DCHT 9/56, DHT 8/62 met progression endpoint after I/D Rx (1/31 bone). AEs were characteristic and reversible (no grade 5). Leading causes of accrual impediment were inadequate site selection, no consensus regarding patient and treatment selection for this pt population, physician and patient bias re: treatment and evolving changes in the adjuvant treatment landscape during follow-up time (adjuvant RT). Conclusions: The role of adjuvant systemic treatment after RP remains undefined. Clinical trials in this pt population are challenging. Supported by Sanofi NCT000283062.

Transformasi Terhadap Min bagi Menguji Taburan Terpencong

2012 ◽  
Author(s):  
Nor Haniza Sarmin ◽  
Md Hanafiah Md Zin ◽  
Rasidah Hussin
Keyword(s):  
Key Words ◽  
Simulation Study ◽  
Bias Correction ◽  
Type I Error ◽  
Small Sample Size ◽  
Small Sample ◽  
Skewed Distribution ◽  
Type I ◽  
Skewed Distributions ◽  
Chi Square

Suatu transformasi terhadap min dilakukan menggunakan penganggar pembetulan kepincangan bagi mendapatkan statistik untuk menguji min hipotesis taburan terpencong. Penghasilan statistik ini melibatkan pengubahsuaian pemboleh ubah . Kajian simulasi yang dijalankan terhadap taburan yang terpencong iaitu taburan eksponen, kuasa dua khi dan Weibull ke atas Kebarangkalian Ralat Jenis I menunjukkan bahawa statistik t3 sesuai untuk ujian satu hujung sebelah kiri dan saiz sampel yang kecil (n=5). Kata kunci: Min; statistik; taburan terpencong; penganggar pembetulan kepincangan; kebarangkalian Ralat Jenis I A transformation of mean has been done using a bias correction estimator to produce a statistic for mean hypothesis of skewed distributions. The statistic found involves a modification of the variable . A simulation study that has been done on some skewed distributions i.e. esponential, chi-square and Weibull on the Type I Error shows that t3 is suitable for the left-tailed test and a small sample size (n=5). Key words: Mean; statistic; skewed distribution; bias correction estimator; Type I Error

scholarly journals Taking population stratification into account by local permutations in rare-variant association studies on small samples

2020 ◽  
Author(s):  
J. Mullaert ◽  
M. Bouaziz ◽  
Y. Seeleuthner ◽  
B. Bigio ◽  
J-L. Casanova ◽  
...  
Keyword(s):  
Sample Size ◽  
Rare Variant ◽  
Population Stratification ◽  
Type I Error ◽  
Small Sample Size ◽  
Association Studies ◽  
Small Sample ◽  
Small Samples ◽  
Type I ◽  
Rare Variant Association

AbstractMany methods for rare variant association studies require permutations to assess the significance of tests. Standard permutations assume that all individuals are exchangeable and do not take population stratification (PS), a known confounding factor in genetic studies, into account. We propose a novel strategy, LocPerm, in which individuals are permuted only with their closest ancestry-based neighbors. We performed a simulation study, focusing on small samples, to evaluate and compare LocPerm with standard permutations and classical adjustment on first principal components. Under the null hypothesis, LocPerm was the only method providing an acceptable type I error, regardless of sample size and level of stratification. The power of LocPerm was similar to that of standard permutation in the absence of PS, and remained stable in different PS scenarios. We conclude that LocPerm is a method of choice for taking PS and/or small sample size into account in rare variant association studies.

scholarly journals A Machine Learning Approach to Assess Differential Item Functioning in Psychometric Questionnaires Using the Elastic Net Regularized Ordinal Logistic Regression in Small Sample Size Groups

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Vahid Ebrahimi ◽  
Zahra Bagheri ◽  
Zahra Shayan ◽  
Peyman Jafari
Keyword(s):  
Sample Size ◽  
Type I Error ◽  
Small Sample Size ◽  
Error Rates ◽  
Small Sample ◽  
Elastic Net ◽  
Small Samples ◽  
Type I ◽  
Item Functioning ◽  
Size Groups

Assessing differential item functioning (DIF) using the ordinal logistic regression (OLR) model highly depends on the asymptotic sampling distribution of the maximum likelihood (ML) estimators. The ML estimation method, which is often used to estimate the parameters of the OLR model for DIF detection, may be substantially biased with small samples. This study is aimed at proposing a new application of the elastic net regularized OLR model, as a special type of machine learning method, for assessing DIF between two groups with small samples. Accordingly, a simulation study was conducted to compare the powers and type I error rates of the regularized and nonregularized OLR models in detecting DIF under various conditions including moderate and severe magnitudes of DIF ( DIF = 0.4   and   0.8 ), sample size ( N ), sample size ratio ( R ), scale length ( I ), and weighting parameter ( w ). The simulation results revealed that for I = 5 and regardless of R , the elastic net regularized OLR model with w = 0.1 , as compared with the nonregularized OLR model, increased the power of detecting moderate uniform DIF ( DIF = 0.4 ) approximately 35% and 21% for N = 100   and   150 , respectively. Moreover, for I = 10 and severe uniform DIF ( DIF = 0.8 ), the average power of the elastic net regularized OLR model with 0.03 ≤ w ≤ 0.06 , as compared with the nonregularized OLR model, increased approximately 29.3% and 11.2% for N = 100   and   150 , respectively. In these cases, the type I error rates of the regularized and nonregularized OLR models were below or close to the nominal level of 0.05. In general, this simulation study showed that the elastic net regularized OLR model outperformed the nonregularized OLR model especially in extremely small sample size groups. Furthermore, the present research provided a guideline and some recommendations for researchers who conduct DIF studies with small sample sizes.

Comparing the Performance of Multivariate Multilevel Modeling to Traditional Analyses With Complete and Incomplete Data

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 100-109 ◽  
Author(s):  
Ryoungsun Park ◽  
Keenan A. Pituch ◽  
Jiseon Kim ◽  
Hyewon Chung ◽  
Barbara G. Dodd
Keyword(s):  
Missing Data ◽  
Multilevel Modeling ◽  
Error Rate ◽  
Type I Error ◽  
Small Sample Size ◽  
Univariate Analysis ◽  
Small Sample ◽  
Type I ◽  
Type I Error Rate ◽  
Dependent Variables

Abstract. A multivariate multilevel model (MVMM) extends standard multilevel modeling by including multiple dependent variables and thus could be used in place of traditional multivariate analyses. For a two-group study with two correlated dependent variables, a simulation study was conducted to compare the performance of MVMM to traditional MANOVA and a series of univariate analyses. The results showed that MVMM provides for virtually always greater power than other analyses, even for conditions that have been previously shown to favor univariate analysis. Further, this power advantage can be substantial even when no missing data are present and is often much greater when data are missing. While the Type I error rate for the overall multivariate null hypothesis can be somewhat elevated with MVMM, especially with small sample size and a large proportion of missing data, the Type I error rate for the test of a specific dependent variable is accurate.

A phase III study of pemetrexed (Pem) plus carboplatin (Cb) plus bevacizumab (Bev) followed by maintenance pem plus bev versus paclitaxel (Pac) plus cb plus bev followed by maintenance bev in stage IIIb or IV nonsquamous non-small cell lung cancer (NS-NSCLC): Overall and age group results.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 8004-8004 ◽  
Author(s):  
Mark A. Socinski ◽  
Jyoti D. Patel ◽  
Edward B. Garon ◽  
Ramaswamy Govindan ◽  
Craig H. Reynolds ◽  
...  
Keyword(s):  
Type I Error ◽  
Safety Data ◽  
Sensory Neuropathy ◽  
Progression Free Survival ◽  
Phase Iii ◽  
Type I ◽  
Cox Models ◽  
Phase Iii Study ◽  
Grade 3 ◽  
Ecog Ps

8004 Background: This study compared Pem+Cb+Bev followed by Pem+Bev maintenance (Pem arm) to Pac+Cb+Bev followed by Bev maintenance (Pac arm). The primary endpoint of improved overall survival (OS) for the Pem arm was not met. Methods: Advanced NS-NSCLC pts, ECOG PS 0/1, were randomized to 4 cycles of induction Pem+Cb+Bev with folic acid+vitamin B12 or Pac+Cb+Bev (Pem 500 mg/m2or Pac 200 mg/m2; Cb AUC 6; Bev 15 mg/kg) every 3 weeks. Eligible pts received maintenance Pem+Bev or Bev. OS, progression-free survival (PFS), overall response (ORR), and toxicity were evaluated. A hazard ratio (HR) of 0.80 required 676 OS events/900 pts with 2-sided type-I error .05 and at least 80% power for superiority of Pem over Pac arm. Exploratory Cox models estimated treatment HRs with 95% confidence intervals (CIs) for each age subgroup analyzed: ≤ or >65, 70 (prespecified) and ≤ or >75 yrs (not prespecified). Results: 939 pts (median age, 64.7) were randomized. Median (m) OS for ITT pem and pac arms was 12.6 vs 13.4 mos (HR 1.00, p=0.949); mPFS was 6.0 vs 5.6 mos (HR 0.83, p=0.012) Subgroup efficacy is shown in the Table; ≤ or >65 data were similar to ITT. Pem pts had significantly more drug-related grade 3/4 thrombocytopenia, anemia (except >75 yrs) and fatigue (except >70 and >75 yrs). Pac pts had significantly more grade 3/4 neutropenia (except >70 and >75 yrs), sensory neuropathy (except >75 yrs) and grade 1/2 alopecia. Results parallel overall safety data. Conclusions: OS was not significantly different in any of the age subgroups. PFS was significantly longer in Pem arm overall and for pts ≤70, but was similar for pts >70, >75 yrs. Toxicity profiles differed; subgroup safety data paralleled overall data. Clinical trial information: NCT00762034. [Table: see text]

scholarly journals Perioperative Outcomes Following Kidney-Pancreas Transplantation in Alberta, Canada: Research Letter

2021 ◽  
Vol 8 ◽  
pp. 205435812110293
Author(s):  
Danielle E. Fox ◽  
Robert R. Quinn ◽  
Paul E. Ronksley ◽  
Tyrone G. Harrison ◽  
Hude Quan ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Postoperative Care ◽  
Pancreas Transplantation ◽  
Type I Diabetes ◽  
Small Sample Size ◽  
Small Sample ◽  
Perioperative Outcomes ◽  
Type I ◽  
Patient Safety Indicators ◽  
Significant Difference

Background: Simultaneous kidney-pancreas transplantation (SPK) has benefits for patients with kidney failure and type I diabetes mellitus, but is associated with greater perioperative risk compared with kidney-alone transplantation. Postoperative care settings for SPK recipients vary across Canada and may have implications for patient outcomes and hospital resource use. Objective: To compare outcomes following SPK transplantation between patients receiving postoperative care in the intensive care unit (ICU) compared with the ward. Design: Retrospective cohort study using administrative health data. Setting: In Alberta, the 2 transplant centers (Calgary and Edmonton) have different protocols for routine postoperative care of SPK recipients. In Edmonton, SPK recipients are routinely transferred to the ICU, whereas in Calgary, SPK recipients are transferred to the ward. Patients: 129 adult SPK recipients (2002-2019). Measurements: Data from the Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD) were used to identify SPK recipients (procedure codes) and the outcomes of inpatient mortality, length of initial hospital stay (LOS), and the occurrence of 16 different patient safety indicators (PSIs). Methods: We followed SPK recipients from the admission date of their transplant hospitalization until the first of hospital discharge or death. Unadjusted quantile regression was used to determine differences in LOS, and age- and sex-adjusted marginal probabilities were used to determine differences in PSIs between centers. Results: There were no perioperative deaths and no major differences in the demographic characteristics between the centers. The majority of the SPK transplants were performed in Edmonton (n = 82, 64%). All SPK recipients in Edmonton were admitted to the ICU postoperatively, compared with only 11% in Calgary. There was no statistically significant difference in the LOS or probability of a PSI between the 2 centers (LOS for Edmonton vs Calgary:16 vs 13 days, P = .12; PSIs for Edmonton vs Calgary: 60%, 95% confidence interval [CI] = 0.50-0.71 vs 44%, 95% CI = 0.29-0.59, P = .08). Limitations: This study was conducted using administrative data and is limited by variable availability. The small sample size limited precision of estimated differences between type of postoperative care. Conclusions: Following SPK transplantation, we found no difference in inpatient outcomes for recipients who received routine postoperative ICU care compared with ward care. Further research using larger data sets and interventional study designs is needed to better understand the implications of postoperative care settings on patient outcomes and health care resource utilization.

Phase III study of local or systemic therapy INtensification DIrected by PET in prostate CAncer patients with post-prostaTEctomy biochemical recurrence (INDICATE): ECOG-ACRIN EA8191.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. TPS5098-TPS5098
Author(s):  
Neha Vapiwala ◽  
Yu-Hui Chen ◽  
Steve Y. Cho ◽  
Fenghai Duan ◽  
Christos Kyriakopoulos ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Systemic Therapy ◽  
Biochemical Recurrence ◽  
Radiographic Progression ◽  
Systemic Treatment ◽  
Phase Iii ◽  
Type I ◽  
Treatment Intensification ◽  
Free Survival ◽  
Prostate Bed

TPS5098 Background: Radiation therapy (RT) to the prostate bed and pelvic nodes with short-term androgen deprivation therapy (STAD) is considered a standard of care (SOC) salvage therapy (ST) paradigm for prostate cancer (PC) patients (pts) with post-prostatectomy (RP) biochemical recurrence (BCR). Fluciclovine-PET/CT imaging is FDA-approved in this setting, with improved accuracy for detection of metastases not identified with conventional imaging (CIM). Given PET's greater sensitivity and specificity, its findings are increasingly but variably applied to justify modification or omission of SOC therapies without high-level evidence of clinical benefit. PET may help identify candidates for local or systemic treatment intensification of the otherwise non-tailored SOC approach. Improved systemic control and disease detection with molecular imaging have led to increasing use of focally ablative metastasis-directed RT, to delay or enhance systemic therapy through increased local control. There is also interest in earlier use of systemic therapy; apalutamide (Apa) is a nonsteroidal antiandrogen with established efficacy in improving overall and radiographic progression-free survival (PFS) for non-metastatic castration-resistant and metastatic castration-sensitive PC. This study will evaluate whether pts with PET-detected lesions benefit from such local or systemic treatment intensification approaches. Methods: PC pts with post-RP BCR (PSA>0.5ng/mL; >0.2ng/mL if within 12 mos of RP) and no metastases on CIM who are candidates for SOC ST (RT to prostate bed and pelvic nodes with STAD) are eligible. Prior to study registration, pts undergo SOC baseline PET (18F-fluciclovine but PSMA radiotracers permitted pending commercial availability). Based on institutional clinical interpretation of the SOC PET, pts will be placed in Cohort 1 (PET-negative) or 2 (PET-positive for extra-pelvic metastases). Cohort 1 will be randomized to SOC ST +/- Apa for 6 months and Cohort 2 will be randomized to SOC ST and Apa +/- metastasis-directed RT to PET-positive lesions. The primary endpoint is PFS, defined as time from randomization to radiographic progression on CIM, symptomatic disease or death. Primary objectives are to evaluate whether addition of Apa to SOC ST and addition of metastasis-directed RT to SOC ST and Apa could prolong PFS in Cohorts 1 and 2, respectively. For Cohort 1, 480 pts will be randomized with 85% power to distinguish 5-year PFS rate of 90% (Apa arm) vs. 80% (SOC arm) using one-sided stratified log-rank test with type I error of 0.025. For Cohort 2, 324 pts will be randomized with 85% power to distinguish 5-year PFS rate of 76.5% in the experimental arm from 61.5% in the control arm. Secondary endpoints include overall and event-free survival, toxicity, and PET progression. Clinical trial information: NCT04423211.

scholarly journals Cluster Wild Bootstrapping to Handle Dependent Effect Sizes in Meta-Analysis with a Small Number of Studies

2021 ◽  
Author(s):  
Megha Joshi ◽  
James E Pustejovsky ◽  
S. Natasha Beretvas
Keyword(s):  
Effect Size ◽  
Type I Error ◽  
Meta Analysis ◽  
Error Rates ◽  
Small Sample ◽  
Type I ◽  
Hypothesis Tests ◽  
Type I Error Rates ◽  
Meta Analyses ◽  
Small Sample Correction

The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some meta-analyses also include multiple studies conducted by the same lab or investigator, creating another potential source of dependence. An increasingly popular method to handle dependence is robust variance estimation (RVE), but this method can result in inflated Type I error rates when the number of studies is small. Small-sample correction methods for RVE have been shown to control Type I error rates adequately but may be overly conservative, especially for tests of multiple-contrast hypotheses. We evaluated an alternative method for handling dependence, cluster wild bootstrapping, which has been examined in the econometrics literature but not in the context of meta-analysis. Results from two simulation studies indicate that cluster wild bootstrapping maintains adequate Type I error rates and provides more power than extant small sample correction methods, particularly for multiple-contrast hypothesis tests. We recommend using cluster wild bootstrapping to conduct hypothesis tests for meta-analyses with a small number of studies. We have also created an R package that implements such tests.

scholarly journals Improved Small Sample Inference Methods for a Mixed-Effects Model for Repeated Measures Approach in Incomplete Longitudinal Data Analysis

Stats ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 174-188
Author(s):  
Yoshifumi Ukyo ◽  
Hisashi Noma ◽  
Kazushi Maruo ◽  
Masahiko Gosho
Keyword(s):  
Clinical Trial ◽  
Repeated Measures ◽  
Type I Error ◽  
Mixed Effects ◽  
Error Rates ◽  
Small Sample ◽  
Mixed Effects Model ◽  
Model Complexity ◽  
Type I ◽  
Inference Methods

The mixed-effects model for repeated measures (MMRM) approach has been widely applied for longitudinal clinical trials. Many of the standard inference methods of MMRM could possibly lead to the inflation of type I error rates for the tests of treatment effect, when the longitudinal dataset is small and involves missing measurements. We propose two improved inference methods for the MMRM analyses, (1) the Bartlett correction with the adjustment term approximated by bootstrap, and (2) the Monte Carlo test using an estimated null distribution by bootstrap. These methods can be implemented regardless of model complexity and missing patterns via a unified computational framework. Through simulation studies, the proposed methods maintain the type I error rate properly, even for small and incomplete longitudinal clinical trial settings. Applications to a postnatal depression clinical trial are also presented.

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