Stata se version 13.1 statistical software

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STATA/SE version 13.1 is a general-purpose statistical software package developed by StataCorp. It provides a range of statistical analysis tools and data management capabilities. The software is designed to assist users in data manipulation, statistical modeling, and graphical representation of results.

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6 protocols using stata se version 13.1 statistical software

Modeling Factors Affecting Response and Survival in Hematological Malignancies

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Pearson chi-square (or Fisher’s exact test) and ANOVA (or Kruskal-Wallis’s rank sum) were used to determine difference in the demographics/clinical characteristics among the eras. A Trend test across groups was used to test if there was a trend in the proportion of patients achieving CR/CRp across eras. Univariate and multivariate Logistic regression models were used to model the relationship between response (No CR/CRp vs CR/CRp) and demographics/clinical characteristics.
Overall survival (OS) was calculated as the number of months from the date of diagnosis to death or last follow-up date. Patients who were alive at their last follow-up were censored on that date. Relapse-free survival (RFS) was calculated as the number of months from the date of response to the date of relapse or death. Patients who did not relapse at their last follow-up were censored on that date. The Kaplan-Meier product limit method was used to estimate the median OS. Univariate Cox proportional hazards regression was used to identify any association with each of the variables and OS (or RFS). In this analysis, SCT was treated as a time-dependent variable. Statistical analysis was performed using STATA/SE version 13.1 statistical software.

Badar T., Kantarjian H.M., Nogueras-Gonzalez G.M., Borthakur G., Manero G.G., Andreeff M., Konopleva M., Kadia T.M., Daver N., Wierda W.G., Luthra R., Patel K., Oran B., Champlin R., Ravandi F, & Cortes J.E. (2015). Improvement in clinical outcome of FLT3 ITD mutated acute myeloid leukemia patients over the last one and a half decade. American journal of hematology, 90(11), 1065-1070.

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Factors Associated with ER Presentation and Survival

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We used χ² tests to assess the difference among patient’s characteristics by types of first presentation to diagnosis. Logistic regression models were used to examine the factors associated with the ER presentation. Crude odds ratio (OR), adjusted OR (aOR), and their 95% confidence intervals (CIs) were reported.
We used the Kaplan-Meier method to generate survival curves. Differences between curves were analyzed using the log-rank test. Crude and adjusted Cox regression analysis was performed to evaluate ER presentation related to 1-year cause-specific survival. The proportionality assumption was evaluated using Schoenfeld residuals. Statistical analyses were performed using Stata/SE version 13.1 statistical software (Stata Corp, LP, College Station, Texas).

Ortiz-Ortiz K.J., Ríos-Motta R., Marín-Centeno H., Cruz-Correa M.R, & Ortiz A.P. (2016). Emergency Presentation and Short-Term Survival Among Patients With Colorectal Cancer Enrolled in the Government Health Plan of Puerto Rico. Health services research and managerial epidemiology, 3, 2333392816646670.

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Evaluating Factors Affecting Cancer Diagnosis Stage

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Descriptive statistics and frequency analyses were used to describe the variables of interest. To evaluate the difference in stage at diagnosis and the independent variables of interest, a Chi-square test of Fisher exact tests were used. Logistic regression models were used to estimate the unadjusted odds ratios (ORs), adjusted odds ratios (AORs), and their 95 % confidence intervals (CIs). The likelihood ratio test was used to assess the significance of interaction terms. Likewise, we assessed multicollinearity among independent variables before performing the multivariate logistic regression analysis. Statistical analyses were performed using Stata/SE version 13.1 statistical software (Stata Corp., LP., College Station, TX).
The Institutional Review Board of the University of Puerto Rico, Medical Sciences Campus, reviewed and approved this study.

Ortiz-Ortiz K.J., Ríos-Motta R., Marín-Centeno H., Cruz-Correa M, & Ortiz A.P. (2016). Factors associated with late stage at diagnosis among Puerto Rico’s government health plan colorectal cancer patients: a cross-sectional study. BMC Health Services Research, 16, 344.

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Survival Analysis of Cancer Patients

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Summary statistics were used to describe the study population. Pearson’s χ² test (or Fisher’s exact test) and t-test (or Wilcoxon’s rank sum test) were used to determine difference between groups. OS was calculated as the number of months from start of treatment to death or last follow-up date. Patients who were alive at their last follow-up were censored on that date. The Kaplan-Meier product limit method was used to estimate the median OS for each clinical/demographic factor. Univariate Cox proportional hazards regression was used to identify any association with each of the variables and OS. For each factor, medians, hazard ratios (HRs), their 95% confidence intervals (CI) and proportional hazards regression p-values are presented in tables. Similar analyses were performed for recurrence-free survival (RFS). Statistical analysis was performed using STATA/SE version 13.1 statistical software (Stata Corp. LP, College Station, TX).

Charalampakis N., Nogueras González G.M., Elimova E., Wadhwa R., Shiozaki H., Shimodaira Y., Blum M.A., Rogers J.E., Harada K., Matamoros A J.r., Sagebiel T., Das P., Minsky B.D., Lee J.H., Weston B., Bhutani M.S., Estrella J.S., Badgwell B.D, & Ajani J.A. (2016). The proportion of signet ring cell component in patients with localized gastric adenocarcinoma correlates with the degree of response to preoperative chemoradiation. Oncology, 90(5), 239-247.

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Risk Factors for Therapy-related Myeloid Neoplasms

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Summary statistics were used to describe the study population. Time to development of t-MN was calculated in years from the date of diagnosis of MM to the diagnosis of t-MN. Overall survival (OS) was calculated from the date of diagnosis of t-MN to death or the last follow-up date. Patients who were alive at their last follow-up were censored on that date. The Kaplan-Meier product limit method was used to estimate the median time to event [5 ]. Univariate Cox proportional hazards regression was used to identify any association with each of the variables and time to t-MN [6 ]. For each factor, medians, hazard ratios (HRs), their 95% confidence intervals (CI), and proportional hazards regression p-values are presented in tables. Similar analyses were performed for OS. A p-value of < 0.05 was considered significant for this analysis. Statistical analysis was performed using STATA/SE version 13.1 statistical software (Stata Corp. LP, College Station, TX).

Pemmaraju N., Shah D., Kantarjian H., Orlowski R.Z., Nogueras González G.M., Baladandayuthapani V., Jain N., Wagner V., Garcia-Manero G., Shah J., Ravandi F., Pierce S., Takahashi K., Daver N., Nazha A., Verstovsek S., Jabbour E., De Lima M., Champlin R., Cortes J, & Qazilbash M.H. (2014). Characteristics and outcomes of patients with multiple myeloma (MM) who develop therapy (t)-related myelodysplastic syndrome (MDS), t-chronic myelomonocytic leukemia (CMML), or t-acute myeloid leukemia (AML). Clinical lymphoma, myeloma & leukemia, 15(2), 110-114.

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Survival Outcome Factors Analysis

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Univariate Cox proportional hazards regression was used to identify any association between each factor and the each survival outcome. For each factor, medians, hazard ratios (HR), their 95% confidence intervals (CI), and proportional hazards regression p-values were established. Statistical analysis was performed using STATA/SE version 13.1 statistical software (Stata Corp. LP, College Station, TX).

Neishaboori N., Wadhwa R., Nogueras-González G.M., Elimova E., Shiozaki H., Sudo K., Charalampakis N., Hiremath A., Lee J.H., Bhutani M.S., Weston B., Blum M.A., Rogers J.E., Garris J.L., Rice D.C., Komaki R., Swisher S.G., Skinner H.D., Hofstetter W.L, & Ajani J.A. (2015). Distribution of Resistant Esophageal Adenocarcinoma in the Resected Specimens of Clinical Stage III Patients After Chemoradiation: Its Clinical Implications. Oncology, 89(2), 65-69.

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