What analytic software program is used to test trends in cancer statistics for statistical significance?

• A. Joinpoint
• B. SAS
• C. SPSS
• D. R

Answer: (A)

Testing whether cancer trends over time are statistically significant requires a method that can identify if and when the trend changes and judge the significance of those changes. The Joinpoint Regression Program is designed for this purpose. It analyzes time-series cancer rates (often age-adjusted) and fits piecewise linear segments on a log scale, with points where the slope changes called joinpoints. For each segment, it provides the annual percent change and uses permutation tests to determine how many joinpoints are justified, i.e., whether adding another segment materially improves the model. This combination directly answers both where trends shift and whether those shifts are statistically significant, which is exactly what analysts need in cancer statistics.

While general software like SAS, SPSS, or R can perform trend analyses, they require more setup to replicate joinpoint-style testing and don’t come with the same built-in framework for identifying joinpoints and testing their significance in cancer surveillance data. That focused capability makes Joinpoint the standard choice for this specific task.