Applied Statistics T5 DQ2

Article Citation

and Permalink (APA format)

Article 1

Chen, X., Jiang, H., Zhang, Y., Wang, X., Liu, P., & Zhou, Q. (2024). The incidence rate of allergic reactions induced by oxaliplatin is higher in patients with rectal cancer compared with colon cancer.

Drug & Chemical Toxicology. Jul2024, Vol. 47 Issue 4, p365-371. 7p.

https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=1&sid=b03eae11-a677-4d5e-8cc1-a18531811086%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=a9h&AN=178176294

Article 2

Kosami, K., Kuwabara, M., Okayama, A., & Ae, R. (2025).

Body Mass Index and Weight Change as Predictors of Hypertension Development: A Sex-Specific Analysis.

Nutrients (NUTRIENTS), Jan2025; 17(1): 119. (16p)

https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=4&sid=b03eae11-a677-4d5e-8cc1-a18531811086%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=cul&AN=182442479

Criteria

Description

Description

Broad Topic Area/Title

The study shows incidence rate of allergic reactions to the oxaliplatin in patients with cancer.

The risk of developing hypertension is influenced by BMI and weight change, particularly with regard to sex differences.

Define the Null and Alternative Hypotheses

Null Hypothesis (H₀): There is no significant increase of allergic reactions due to oxaliplatin in cancer patients.

Alternative Hypothesis (H₁): Oxaliplatin significantly increases the incidence of allergic reactions compared to cancer patients.

H₀: There is no significant association between BMI, weight change, and the development of hypertension.

H₁: The BMI and weight changes contributes significantly to the development of hypertension.

Define Independent and Dependent Variables and Types of Data for Variables

Independent Variable: Oxaliplatin exposure (categorical: exposed/not exposed)

Dependent Variable: Allergic reaction occurrence (categorical: yes/no)

Independent Variables: BMI and weight change (continuous)

Dependent Variable: Hypertension development (categorical: yes/no)

Population of Interest for the Study

Cancer patients undergoing oxaliplatin treatment.

The Japanese adults aged 40–75 who were participating in the national health screening program.

Sample

Provide page citation for sample information.

A study with 5243 cancer patients under oxaliplatin treatment was documented (p. 249).

397,181 participants from the Japanese Specific Health Checkup program (p. 3).

Sampling Method

Hospital records are used in a retrospective cohort study.

Retrospective two-point cohort study.

How Were the Data Collected?

Provide page citation.

Electronical medical records and patient reported allergy symptoms were used to obtain data (p. 250).

Outputs from the Japanese Specific Health Checkup database, including BMI, weight changes, and diagnoses of hypertension, are collected (p. 4).

Inferential Statistics

Clearly identify which hypothesis tests were used and the results.

The incidence rates of allergic reactions were analyzed by the chi-square tests.

The odds of oxaliplatin induced allergic reaction was then determined using logistic regression where the odds ratio was 2.45 (95% CI: 1.98 – 3.02, p < 0.05).

The relationship between BMI, weight changes and hypertension was assessed using multivariable logistic regression.

In the study significant associations between increased BMI and hypertension (OR = 1.11, 95% CI: 1.11–1.12) and between weight gain and hypertension (OR = 1.09, 95% CI: 1.09–1.10, p < 0.05) (p. 8) were found.

Assess the Appropriateness of Statistical Methods Used in This Study

Provide rationale to support your response.

Logistic regression is appropriate for study of categorical outcomes (allergic reaction: yes/no).

Chi-square tests will accept incidence rates>0, and are used to compare incidence rates between groups.

The study included proper control of confounders like age and prior history of allergy.

The relationship between the BMI/weight change to hypertension is assessed by multivariable logistic regression, which is an appropriate method to examine such a predictive relationship.

Analyses were stratified by sex improving robustness in findings.

The increased sample size increases the statistical power and generalizability.