Living Systematic Review Guides Prostate Cancer Treatment Options

Written by: Beth Dougherty

As science and clinical medicine advance, oncologists increasingly face the challenge of information overload. It can be hard for oncologists, especially those in community practices who cover many cancers, to keep up with the influx of new therapies, biomarkers, and clinical trial results.

The go-to solution has been the systematic review. Researchers team up to gather evidence from clinical trial results in a particular area, synthesize it, and provide guidance. This guidance becomes published clinical guidelines. 

Those guidelines, however, can quickly become obsolete.

“Once you finish a systematic review, new studies come in, and your work is outdated,” says prostate cancer oncologist Irbaz Bin Riaz, MD, PhD, “We are always chasing our tails.”

Riaz, who completed this work as a post-doctoral fellow at Dana-Farber in the lab of Eliezer Van Allen, MD, decided to take a more modern approach. He and colleagues from multiple institutions have applied the principles of a “living” systematic review and meta-analysis to oncology for the first time. 

The review not only points to important guidance for the treatment of patients with metastatic castration-sensitive prostate cancer, but also, its clinical guidance will evolve over time. In principle, a living systematic review never gets outdated because it uses advanced computational tools to continually pull in new evidence, analyze it, and recommend guidance.”The world is increasingly enabled by technology, data science, and real-time interpretation,” says Van Allen, chief of the Division of Population Sciences. “The time is right to apply these tools to clinical evidence to create systematic reviews that are sustainable and continually relevant.”

Irbaz Bin Riaz, MD, PhD, and Eliezer Van Allen, MD.

Rapidly evolving options in prostate cancer

Riaz focused on metastatic castration-sensitive prostate cancer, which is experiencing a rapidly changing treatment landscape. About a decade ago, the standard treatment for patients was hormone therapy called androgen deprivation therapy (ADT). Since then, multiple clinical trials have shown improved efficacy with treatment options that include combining ADT with chemotherapy, combining ADT with androgen pathway inhibitors (APIs), called doublet hormone therapy, and combining all three, called triplet therapy.

Despite these advances, studies suggest that more than two-thirds of patients are not receiving these combination therapies that improve survival.

There are many factors that influence the uptake of new medicines, says Riaz, who is now at the Mayo Clinic in Phoenix, AZ. “One thing we need to do is improve the guideline development and make it faster and relevant to clinical practice.” 

Clinical guidelines require an interpretation of the available evidence. For example, triplet therapy was only tested against ADT plus chemotherapy in clinical trials, not against ADT plus API therapy. Further, prostate cancer is a heterogeneous disease. Patients with low disease volume might respond differently to treatment than patients with high volume of the disease.   

“There are gaps,” says Riaz. “In an ideal world, every option would be randomized, but it’s not always feasible.”

To fill the gaps for oncologists who want to select the best therapy for individual patients, Riaz designed a systematic review that pulled in evidence from 11 trials involving over 11,000 participants. His meta-analysis enabled a comparison of triplet therapy with doublet hormone therapy while also taking disease volume and whether the metastasis was new or recurrent into consideration.

His results, published in JAMA Oncology, suggest there are two main categories of patients. Those at highest risk have high volume disease with metastases at the time of diagnosis. Those at lower risk have low volume disease that was diagnosed at an earlier time but are experiencing recurrence. 

The meta-analysis suggests that patients at highest risk will likely do better on triplet therapy, which is the most powerful but also the most toxic. Those at lower risk will likely do better on doublet therapy with ADT plus API therapy, which is likely to provide the most benefit without as much toxicity.

For patients who are in the middle of the spectrum, the analysis gives doctors a starting point for a conversation. “We have a choice to make about the risks and toxicity, and that choice is highly individual,” says Riaz.

Click the above to enlarge to see the proposed workflow for the living systematic review (not all steps have been implemented yet).

Living evidence and evolving guidelines

In addition to publishing these findings in a traditional journal, Riaz also made the systematic review available online. Over time, the online review will evolve with results from new trials.

The living systematic review is able to evolve because it is set up as a pipeline that continually flows new data through a process. The process has a human in the loop but also relies on AI and computational tools for automation. First, an automated search pulls appropriate studies into a database for identification and data extraction. Then, data analytics synthesize the new data with the existing data to create a body of evidence. The process flows iteratively to keep the evidence alive and up to date.

The existing pipeline currently relies on computational methods and algorithms to scan, extract, and analyze the data, but could evolve to use generative AI, the technology behind tools like ChatGPT. 

“This effort also underscores the need to understand and improve the data that supports AI in cancer,” says Van Allen.

As a next step, Riaz plans to turn the living evidence into living clinical practice guidelines and decision aids for doctors – aids akin to traditional clinical practice guidelines, only more fluid. Riaz, who will continue collaborating with Van Allen and others, is also working with colleagues at the American Society of Clinical Oncology, which develops and publishes traditional clinical practice guidelines, to modernize clinical practice guidelines and practice algorithms.

“That’s where the strength comes in, where the use of artificial intelligence and informatics can really help,” says Riaz. “We need to move to more modern methods so that doctors can use the latest evidence to help more patients faster.”