Maurie Markman, MD, discusses the obstacles between implementing clinical trial data into practice.
There should be little or no debate with the statement that clinical trials serve as the primary source of data employed to favorably affect outcomes for patients who receive a diagnosis of cancer. However, much can be said regarding well-described deficiencies in the existing trial process and, unfortunately, the often ineffective efforts to improve this critical component of cancer care and research. This includes the time required to design, initiate, and complete highly clinically relevant studies, the staggering costs required to complete many studies (particularly phase 3 randomized trials), never-ending debates regarding meaningful study end points, and the exclusion of individuals who represent the real-world demographics of patients receiving cancer care (eg, age, common comorbidities).
One must add to this list the smaller size of molecularly defined patient subgroups within individual cancer types, which make it more difficult to conduct “gold-standard” randomized studies within a reasonable period of time. Further, there is the questionable relevance of existing and rather antiquated trial-based toxicity scales developed in a long-past era where standard systemic antineoplastic drug therapy focused almost exclusively on the short-term intermittent intravenous delivery of several cycles of cytotoxic agents. As advanced cancers increasingly become serious “chronic illnesses,” with treatments including combination regimens with oral and daily dosing strategies potentially delivered over a period of years rather than a few weeks or months, the critical question of objectively measuring the actual effects on patient-reported outcomes and experienced quality of life becomes ever more important.
Additional issues regarding cancer clinical trials need to be considered, including how truly paradigm-changing study results in a specific setting might be optimally implemented in routine practice. Equally important is how clinicians should view trial outcomes when several alternative strategies may be employed but no direct comparative data exist to assist in the decision-making process.
This commentary highlights a particular concern that has received limited discussion in the oncology literature. How does one interpret unexpected, perhaps highly provocative, but less than conclusive peer-reviewed study results that may be of considerable direct relevance to patient welfare? An example might include settings where it was uncertain when, if ever, formal regular approval from the FDA would occur. How might oncologists consider using these published data to potentially optimize the opportunity for a favorable clinical outcome for an individual patient?
A recent example of this phenomenon from outside the oncology realm is that of the potential use of high-titer COVID-19 convalescent plasma to prevent or treat the complications of a serious viral infection. Although widely discussed in the medical and lay literature, data from several well-designed randomized trials published in high-impact peer-reviewed journals failed to demonstrate the benefits of this strategy.1-3 However, a more recent report from a randomized trial involving 1225 participants from 23 study sites concluded that “early administration of high-titer SARS-CoV-2 convalescent plasma reduced outpatient hospitalizations by more than 50%. Hightiter convalescent plasma is an effective outpatient COVID-19 treatment with the advantages of low cost, wide availability, and rapid resilience to variant emergence from viral genetic drift in the face of a changing pandemic.”4
Of course, these various trials were conducted at somewhat different times with diverse study populations. But the question being addressed in this commentary is how should individual clinicians and the medical community interpret these outcomes and how might the results affect the treatment of serious COVID-19 infections?
Turning to the cancer arena it is not difficult to find recent examples of intriguing study results that either seriously challenge or raise concerns regarding the current clinical paradigm but unfortunately do not yet provide a definitive answer to the questions they address.
For the purpose of this all-too-brief discussion, let us consider the provocative report involving patients with advanced melanoma treated with immunotherapy at a single center from January 1, 2012, to December 31, 2020, recently published in a high-impact oncology journal.5 A total of 481 individuals were treated, but the specific study population analyzed here included only those with stage IV disease (n = 299). In the analysis, patients who had at least 20% of infusions administered after 4:30 pm experienced a shorter median overall survival of 4.8 years (95% CI, 3.9-not estimable) vs not reached among those who received treatment earlier in the day (HR, 2.04; 95% CI, 1.04-4.00; P = .038). The investigators concluded, “This result remained robust to multivariable proportional hazards adjustment.”5
Of note, intriguing preclinical data exist related to the potential relevance of circadian rhythm on immune function, and findings from at least 1 additional small nonrandomized clinical experience supported the conclusions of this report.6
Of course, the study being a nonrandomized retrospective analysis, leads to the usual criticisms associated with all such observational studies. As a result, there appeared the not surprising editorial response that “prospective randomized trials should identify optimal timing of infusions of immune checkpoint inhibitors, which might be sex specific and tailored to individual patients’ circadian biomarkers.”6
There is nothing wrong with this anticipated academic conclusion, but what about the patient with advanced melanoma scheduled to begin therapy tomorrow, or the next day or the next week, with a commercially available checkpoint inhibitor? Should the infusions be scheduled preferentially in the morning rather than the afternoon, even in the absence of definitive evidence-based “gold standard” data from a well-written, rigorously conducted, and analyzed phase 3 randomized study, one subjected to peer review and published in an appropriately high-impact medical journal? Co-pays, insurance approval, formulary committee, added costs to an oncology practice or hospital outpatient program, or inclusion in National Comprehensive Cancer Network guidelines are not standing in the way of this decision.
One might also inquire as to what the oncologist would want if this were a family member or friend, or whether patients in this situation should perhaps be given a summary of the existing data and determine its relevance for themselves.