Understanding P-Values: A Critical Tool for Evaluating Prostate Cancer Research

What Every Prostate Cancer Patient Should Know About Statistical Significance

Written for the Informed Prostate Cancer Support Group (IPCSG) Newsletter

As prostate cancer patients and their families navigate the complex world of clinical research, understanding how to interpret study results becomes crucial for making informed treatment decisions. A recent comprehensive review published in the Red Journal (International Journal of Radiation Oncology) highlights why the p-value—a statistical measure that determines whether research findings are "significant"—deserves our attention, especially given the ongoing debates in the medical community about its proper use and interpretation.

The P-Value in Context: Two Prostate Cancer Trials Tell the Story

Consider this real-world scenario from recent prostate cancer research: Two major clinical trials examined whether adding radiotherapy to the prostate improves survival for men with low-volume metastatic disease. Both studies found nearly identical benefits—a hazard ratio of 0.68, meaning a 32% reduction in death risk with radiotherapy.

The first trial, with 819 suitable patients, reported a p-value of 0.007 and was declared "statistically significant." The second trial, with only 160 suitable patients, showed the exact same benefit but had a p-value of 0.20 and was labeled "negative." This apparent contradiction illustrates why understanding p-values matters for patients evaluating treatment options.

What Is a P-Value and Why Should You Care?

The p-value represents "the probability that the observed data, or a more extreme outcome, would have occurred by chance—that is, due to sampling variation—when the null hypothesis is true." In simpler terms, when researchers test whether a treatment works, they start with the assumption that it doesn't work (the null hypothesis). A p-value tells us how likely it would be to see the results we observed if the treatment truly had no effect.

The conventional threshold of p<0.05 means there's less than a 5% chance the results occurred by random chance alone, or, if we ran the same study 20 times, we'd expect to get a result once just from pure chance. This threshold was introduced by statistician Ronald Fisher in 1925 as a "convenient convention" for practical significance testing, roughly corresponding to 2 standard deviations from the mean.

The Current Debate: Moving Beyond "Significant" vs. "Not Significant"

The medical research community is actively debating the role of p-values. A 2019 Nature commentary supported by over 800 scientists, including statisticians and medical researchers, argued against the conventional use of "statistical significance," while in 2021, the American Statistical Association stated that "the use of P-values and significance testing, properly applied and interpreted, are important tools that should not be abandoned."

Critics argue that treating results as either "statistically significant" or "not significant" oversimplifies what should be viewed as a continuous measure of evidence. This binary interpretation can be misleading, as a p-value of 0.049 would be considered "significant" while 0.051 would not, despite the minimal difference.

Key Lessons for Prostate Cancer Patients

1. Statistical Significance vs. Clinical Significance

Not all statistically significant findings are clinically meaningful, and not all "non-significant" results lack clinical importance. In the BC2001 bladder cancer trial, concurrent chemotherapy improved 5-year overall survival from 35% to 48%—a 13% absolute improvement that most patients and clinicians would consider clinically significant. However, the p-value was 0.16, making it "statistically non-significant" because the trial wasn't powered adequately for this endpoint.

2. Sample Size and Statistical Power Matter

Statistical power is "the probability of rejecting the null hypothesis when it is false," and it's closely linked to a study's sample size. Larger studies have more power to detect real effects and associations. When interpreting results, consider both the p-value and whether the study was adequately powered to detect meaningful differences.

3. Look Beyond the P-Value

When evaluating research results, patients should consider:

• Effect size: How large is the actual benefit or harm?
• Confidence intervals: What range of effects is compatible with the data?
• Clinical context: Does the finding make sense given other research?
• Study quality: Was the trial well-designed and adequately powered?

Recent Prostate Cancer Research Highlights

The importance of proper statistical interpretation becomes clear when examining recent prostate cancer advances:

STAMPEDE Trial Long-Term Results

The STAMPEDE trial's final analysis confirmed that prostate radiotherapy improves overall survival in men with newly diagnosed, low-burden metastatic prostate cancer, but not in men with high-burden disease. The magnitude of the survival benefit is substantial and clinically relevant, with the hazard ratio improving from 0.68 to 0.64 for men in the low metastatic disease group with additional follow-up.

FDA Expansion of PSMA-617 Treatment

In March 2025, the FDA expanded approval of 177Lu-PSMA-617 to be used earlier in treatment, based on the PSMAfore phase 3 trial results showing prolonged progression-free survival compared to second hormonal therapy alone.

Advancing Treatment Options

Recent developments include updates on studies describing the potential use of Pluvicto (177Lu-PSMA-617) before chemotherapy in people with PSMA-PET scan-positive metastatic castration-resistant prostate cancer, and results from a separate trial showing possible benefit for a second 177Lu-containing radioligand therapy.

Practical Recommendations for Patients

1. Ask about effect sizes: When discussing study results with your oncologist, ask not just whether results were "significant," but how large the actual benefit or risk was.
2. Consider confidence intervals: These show the range of plausible effects and indicate the precision of the estimate.
3. Understand study limitations: Ask whether the trial was large enough to detect the differences that matter to you.
4. Look for consistency: Multiple studies showing similar results provide stronger evidence than a single trial.
5. Consider your individual situation: Population-based results may not apply directly to your specific case.

The Future of Statistical Interpretation in Medicine

Medical research experts increasingly emphasize that "statistical significance, ascertained through statistical tests using the P value, indicates that an observed difference or association is unlikely to be due to chance alone," while clinical relevance "focuses on the practical implications of a finding in real-world contexts."

Rather than abandoning statistical significance testing, many experts advocate for education and reform in how p-values are used, reported, and interpreted. The focus should be on using p-values as one piece of evidence alongside effect sizes, confidence intervals, and clinical judgment.

Conclusion

Understanding p-values empowers prostate cancer patients to better evaluate research findings and engage in informed discussions with their healthcare providers. While the statistical debates continue in medical journals, the practical message for patients remains clear: look beyond simple "significant" or "not significant" labels to understand the full picture of what research results mean for your individual situation.

As we advance into an era of personalized medicine and increasingly sophisticated treatments, statistical literacy becomes not just helpful but essential for navigating the complex landscape of prostate cancer care.

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Sources and References

1. The Significance of the P-Value. International Journal of Radiation Oncology, Biology, Physics. Red Journal article on p-value interpretation in clinical research.
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3. Clinical Significance: Are You Only Relying on the P-value? ScienceOpen (July 2024). Available at: https://www.scienceopen.com/hosted-document?doi=10.18772/26180197.2024.v6n2a10
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7. Radiotherapy to the prostate for men with metastatic prostate cancer in the UK and Switzerland: Long-term results from the STAMPEDE randomised controlled trial. PMC (2022). Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC9173627/
8. 2025/2024 Advanced Prostate Cancer Newsletter. ZERO Prostate Cancer. Available at: https://zerocancer.org/newsletters/advanced-prostate-cancer/2024-2025
9. FDA Expands New Treatment for Metastatic Prostate Cancer: Targets a Protein Called PSMA. Memorial Sloan Kettering Cancer Center (March 2022). Available at: https://www.mskcc.org/news/fda-approves-promising-therapy-advanced-prostate
10. The Lancet Commission on prostate cancer: planning for the surge in cases. The Lancet (April 2024). Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)00651-2/fulltext
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14. ASTRO 2024: Radiotherapy of the Primary Tumor and All Metastatic Lesions in Oligometastatic Prostate Cancer: 5-Year Results of Prolong Study. UroToday. Available at: https://www.urotoday.com/conference-highlights/astro-2024/astro-2024-prostate-cancer/155246-astro-2024-radiotherapy-of-the-primary-tumor-and-all-metastatic-lesions-in-oligometastatic-prostate-cancer-5-year-results-of-prolong-study.html
15. Metastasis-Directed Radiotherapy Represents Significant Advancement in Prostate Cancer. OncLive (April 2024). Available at: https://www.onclive.com/view/metastasis-directed-radiotherapy-represents-significant-advancement-in-prostate-cancer
16. The Significance of the P-Value - International Journal of Radiation Oncology, Biology, Physics

This article was prepared for educational purposes based on current medical literature and ongoing research. Always consult with your healthcare team before making treatment decisions.