Issues Related to Categorization of Continuous Independent Variables in Multiple Logistic Regression Analysis in Clinical Trials

Effect of with and without categorization of continuous variables on the number and nature of statistically significant predictors was examined while analyzing clinical trial data. The number of categories required to have consistent statistical inference was also explored. Multiple Logistic Regression Analysis was employed with the dependent variable in the model may be a dichotomous/multi-category in nature while the independent variables （predictors） may be either continuous or categorical or ordinal. Real-life clinical trial data was used to answer the objectives. It was found that there was no hard and fast rule to categorize the continuous variables. Sometimes, it was observed that the set of significant predictors identified might change with the criteria of categorization. Certain variables without categorization produced too large odds ratios to interpret meaningfully. The nature as well as number of significant predictors altered with classification criteria often forcing the authors to categorize variables, it is recommended that the independent variables need not be coded, unless otherwise warranted. Coding is needed when the odds ratio is extremely high. In this situation, two or more categories, including regression analysis. median cut off point, will be sufficient to undertake the logistic

Regression Model to Analyze Differential Response to Treatment in Randomized Controlled Clinical Trial

The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.

Some Practical Issues Related to Univariate Regression Analysis Prior to Multivariate Regression Analysis in Randomized Controlled Clinical Trials

Often many variables have to be analyzed for their importance in terms of significant contribution and predictability in medical research. One of the possible analytical tools may be the Multiple Linear Regression Analysis. However, research papers usually report both univariate and multivariate regression analyses of the data. The biostatistician sometimes faces practical difficulties while selecting the independent variables for logical inclusion in the multivariate analysis. The selection criteria for inclusion of a variable in the multivariate regression is that the variable at the univariate level should have a regression coefficient with p 〈 0.20. However, there is a chance that an independent variable with p 〉 0.20 at univariate regression may become significant in the multivariate regression analysis and vice versa, provided the above criteria is not strictly adhered to. We undertook both univariate and multivariate linear regression analyses on data from two multi-centric clinical trials. We recommend that there is no need to restrict the p value of 〈= 0.20. Because of high speed computer and availability of statistical software, the desired results could be achieved by considering all relevant independent variables in multivariate regression analysis.

Sintilimab (anti-PD-1 antibody) combined with high-dose methotrexate, temozolomide, and rituximab (anti-CD20 antibody) in primary central nervous system lymphoma: a phase 2 study

Primary central nervous system lymphoma(PCNSL)is a rare and frequently fatal lymphoma subtype.The programmed death-1(PD-1)pathway has emerged as a potential therapeutic target,but the effectiveness of PD-1 antibody sintilimab in combination with immunochemotherapy as a frontline treatment for PCNSL remains to be determined.In this phase 2 trial(ChiCTR1900027433)with a safety run-in,we included patients aged 18–70 with newly diagnosed PCNSL.Participants underwent six 21-day cycles of a SMTR regimen,which includes sintilimab(200 mg,Day 0),rituximab(375 mg/m2,Day 0),methotrexate(3.0 g/m2,Day 1 or 1.0 g/m2 for patients aged≥65 years),and temozolomide(150 mg/m2/d,Days 1–5).Among 27 evaluable patients,the overall response rate(ORR)was 96.3%(95%confidence interval:81–99.9%),with 25 complete responses.At a median follow-up of 24.4 months,the medians for duration of response,progression-free survival(PFS),and overall survival were not reached.The most common grade 3–4 treatment-related toxicities were increased levels of alanine aminotransferase(17.9%)and aspartate aminotransferase(14.3%).Additionally,baseline levels of interferon-αand the IL10/IL6 ratio in cerebrospinal fluid emerged as potential predictors of PFS,achieving areas under the curve of 0.88 and 0.84,respectively,at 2 years.Whole-exome sequencing revealed a higher prevalence of RTK-RAS and PI3K pathway mutations in the durable clinical benefit group,while a greater frequency of Notch and Hippo pathway mutations in the no durable benefit group.These findings suggest the SMTR regimen is highly efficacious and tolerable for newly diagnosed PCNSL,warranting further investigation.