What Role Should Genomic Classifier Testing Play in Prostate Cancer?

Genomic classifier (GC) tests do not appear to consistently influence risk stratification or treatment decisions for patients newly diagnosed with prostate cancer considering first-line treatment, according to results of a systematic review.

Of 10 studies that reported risk reclassification after GC using one of three available tests—Decipher, Prolaris, or Oncotype DX Genomic Prostate Score (GPS), very low- or very low-risk patients with prostate cancer were more likely to develop Prostate. Levels rated as the same or lower (GPS: 100% to 88.1%; Decoding: 87.2% to 82.9%; Prolaris: 76.9%) at lower levels reported Amir Alishahi Tabriz, MD, PhD, MPH, of the Center for Moffitt Cancer Center in Tampa, Florida, and colleagues found that observational studies risk bias.

However, a randomized trial ( Age of trial(They showed that GC testing using GPS reclassified 34.5% of very low-risk patients and 29.4% of low-risk patients into the high-risk category, they noted in the study. Annals of internal medicine.

In addition, 14 studies evaluated the impact of GC testing on treatment intensity, with 12 observational studies indicating that GC testing resulted in higher rates of recommending active surveillance (AS) after diagnosis, with a relative change in AS ranging from 7.5% to 61.8%. And two randomized analyzes from the ENACT trial show that patients’ preference for active treatment (prostatectomy or radiation) increased “modestly” when assigned to receive GPS testing.

On the other hand, urologists’ preference for these treatments increased significantly, from 11.4% to 29.3%, for patients who received a GPS test compared to those who did not (15.3% to 14.1%), resulting in an increased odds of active urologists’ preference By 2.55%. Treatment for those assigned to GPS compared to those who were not.

“[A]Although GC tests may influence risk reclassification and treatment selection, differences between observational studies and randomized trials, across GC test type, and patient characteristics complicate understanding the role of these tests in patient care,” concluded Tabriz and colleagues.

“Our findings that reclassification rates vary widely across studies leave unanswered questions about who might benefit most from follow-up GC testing evaluation,” they noted. “This difference may be due to the use of different underlying clinical risk stratification systems as comparators, clinical differences between groups of patients who received the tests, differences in test performance over time or across test types, or inconsistencies in test interpretation.”

The authors noted that evidence regarding the benefit of GC testing among racial and ethnic groups was limited, and that apart from the ENACT trial, only two studies have examined the effect of GC testing on risk reclassification, and only one investigated the effect of GPS. A test on AS selection in black men.

“Some research suggests that a subset of black men may have genetically aggressive tumors that may be missed by traditional clinical risk classifiers,” they wrote, adding that more studies are needed to evaluate the impact of incorporating these tests into risk stratification and clinical assessment of blacks. Men with prostate cancer.

in Editing accompanying the studySyed Arsalan Ahmad Naqvi, MD, and Erbaz Bin Riaz, MD, MBI, PhD, both of the Mayo Clinic in Phoenix, noted that the evidence for GCs as predictive biomarkers has been limited and derived primarily from observational studies or retrospective analyses. Retrospective, “which is susceptible to bias and variation, which undermines its strength and generalizability.”

They added that the pivotal trials that provided evidence that GCs could be used as prognostic biomarkers to guide adjuvant chemotherapy decisions in hormone receptor-positive, early-stage breast cancer were conducted over a decade, while their use in early-stage prostate cancer.

“Ultimately, combining stem cells with AI-based multimodal approaches and prospectively testing them in randomized controlled trials holds the promise of addressing current gaps in clinical utility while keeping pace with the rapidly evolving landscape of precision oncology,” they wrote.

Nineteen studies were included for data extraction in this systematic review, two of which were analyzes of the ENACT randomized trial, and the remaining 17 studies were observational studies. Decoder was used in four studies, GPS in 10 studies, and Prolaris in five studies. With one exception, all studies were conducted in the United States