Ben Brown

The past 2 decades have witnessed rapid strides in the field of cancer medicine by understanding the complex interactions of epigenetics, genotype, germline mutations, environmental factors, and social determinants of health resulting in the evolution of the field of precision medicine (PM).

 This understanding has also led to emerging targeted therapies and the expansion of personalized medicine.

Clinical trial accrual in adult cancer patients is less than 3% across the adult cancer patient population.

 The figures are even worse in minorities and women.

 In a 2020 analysis of the global participation in clinical trials, the FDA highlighted the vast difference and disparities between the enrolled participants. The FDA report revealed that out of close to 290,000 trial participants worldwide, 76% were White, 11% were Asian, and only 7% were Black.

 Comparing these statistics to the global population of 8 billion people, 60% of the participants reside in Asia, 16% in Africa, 10% in Europe, and approximately 8% in Latin America (World Population Review).

Similarly, a review of 379 clinical trials funded by the US National Institute of Mental Health published in 1995-2004 found that all racial or ethnic groups except White individuals and African Americans were underrepresented, and only about 48% of the studies provided complete racial or ethnic information.

 Thus, data for global populations are lacking, and current guidelines and clinical decisions are based on insufficiently diverse trials and studies.

Existing models of clinical trials programs lean on large academic centers and tertiary care centers to execute clinical trials. This has inherent challenges when it comes to improving diversity. It can also make disparities worse. More than 70% of the US population lives more than 2 hours from large academic and tertiary institutions, making localized participation challenging for many. Additional barriers include time away from work, child care needs, and transportation costs.

Implications of Lack of Diversity in Clinical Trials

When used in a real-world population, newer drugs that are developed based on clinical trials that lack these types of diversity can lead to treatments that are not effective universally and can carry unexpected toxicities due to biological differences in genomic map and pharmacogenomics in underrepresented minorities. Pharmacological difference based on sex and race may lead to either reduced activities or increased toxicities.

 Females have a 1.5- to 1.7-fold greater risk of developing an adverse drug reaction. Several drugs have been withdrawn from the market for sexbased adverse events (AEs).

The cancer drug fluorouracil has different toxicity profiles and AEs. These AEs were observed at a higher rate in African American individuals.

 Ixazomib (Ninlaro), approved by the FDA in 2015 for the treatment of multiple myeloma, had only 1.8% Black participants in the phase 3 clinical trial despite African Americans having higher incidence and prevalence of this disease than European Americans.

Establishing diversity in clinical trials is essential to achieving health equity by ensuring historically underrepresented patient populations have equal access to and efficacy from new and investigative therapies that can help improve outcomes. Taking a real-world data (RWD)–based approach can help unlock the ability to find new sites and diverse patient populations while keeping the focus on the trusted patient-provider connection often found in community practices. This can help bridge the current diversity gaps.

Advantages of Using Just-in-Time Clinical Trials

The COVID-19 pandemic has created an alternative path to rapid accrual using data and remote monitoring technologies to improve trial accrual efforts and lead to successful completion, and subsequent drug approvals. Expanding the availability of clinical trials to providers irrespective of their academic and institutional affiliations could expand the diverse populations who might benefit from the treatment. This can be accomplished by establishing a RWD registry as the first step.

Just-in-time trials (JITs) create an immediate opportunity to advance a well-defined path forward to reducing cancer health disparities by helping all patients increase access to clinical trials for precision medicines— especially patients with more diverse racial, ethnic, and socioeconomic backgrounds. JIT trials unlock opportunities hiding in plain sight, leveraging patient registries using RWD and real-world evidence (RWE), patient-centered technologies coupled with standardized processes, remote support, centralized internal review boards (IRBs), and no redundancy (

). JIT is about modernizing and changing the way clinical trial sponsors think about and approach clinical trials today.

The concept of developing JIT trials is a recent one. It is particularly well adopted as a companion to the implementation of PM. To initiate them, pharmaceutical companies would need to open a study site only where patients are located, rather than opening multiple sites, which adds a burden to already stretched resources. JIT is based on providing the right access to a trial at the right time rather than opening hundreds of sites and not accruing a single patient. JIT reduces demands for huge paperwork for each study and labor-intensive archaic paperwork creating an unnecessary burden on sites with limited resources. The biggest argument for the use of JIT trials is reducing costs.

The frequency and distribution of cancer health disparities (CHDs) are uneven across races. It is undisputed that African Americans, Hispanics and non-White individuals are disproportionately burdened by 4 drivers of CHDs: access to screening, testing, clinical trials, and treatment. There are over 45 types of cancer that do not have any recommended screening methods; there are no screens commercially available for melanoma or for cancer of the stomach, kidney, pancreas, or ovaries, and limited screens are available for lung cancer. Seventy-one percent of cancer-related deaths in the US are in cancers with no recommended screening guidelines for the broad population. Increasing access to both screening and testing is a strategic imperative only if they are used. JIT trials begin with creating RWD by harnessing demographic, clinical, racial, socioeconomic, pathological, radiological stage, genomics, biomarker, and pharmacogenomics data in ways that affect medical management in over 30% of patients.

 This is how we make precision medicine more precise.

The next step is for contract research organizations (CROs) to harness this kaleidoscope of well-phenotyped patient data and systematically increase accrual of minorities into clinical trials. Reducing CHDs by increasing access to screening and access to testing simultaneously creates a positive feedback loop that drives increased adoption of clinical trials, even more so JITs. Pharmaceutical manufacturers now use data from molecularly targeted biomarker testing, incorporated in patient registries using RWE to improve standard-of-care treatment, develop new, novel targeted therapies, and address health care disparities. This is measurable progress for all stakeholders in cancer care.

JIT provider networks are critical infrastructure and must be used to reduce CHDs by increasing access to clinical trials. Addressing widespread CHDs requires CROs and clinical trial sponsors to adopt and use JIT provider networks (FIGURE). Proprietary patient registries, with the help of the pharmaceutical industry or decentralized research organizations (DROs), can screen for patients, process paperwork, and enroll patients into trials from all participating sites.

The opportunity to avoid considerable fixed costs, expenses, and under- or no enrollment at multiple sites creates an attractive value proposition for all parties involved. The acceleration of all aspects of clinical trial site readiness is unparalleled through a differentiated JIT study start-up process.

JITs can accomplish in 2 weeks what many trial sites are unable to accomplish in 2 months.

JIT trials can collapse and consolidate into days—and into 6 steps or less—a systematic process that begins first by fast-tracking patients identified from registry, confirming the eligibility of the patient, and coordinating communications with the clinical team to rapidly assess and evaluate authorization for participation in the clinical trial 

Next, for step 2, upon authorization, the DRO sends scope of work and protocols to the site, preceding the execution of confidential disclosure agreements (CDAs) and all regulatory paperwork.

Now, a complete protocol package is sent to the site by the DRO. By the fifth or sixth day, the DRO performs a positive site screening. This step is imperative if the site has not participated in DRO or sponsor trial in the past 12 months. The sponsor team will now approve or reject the site and begin rapid enrollment of patients.

In approximately 1 week, the site can process the full protocol package and obtain approval from centralized IRB, as well as execution of clinical trial agreement, budget approval, and submission of all regulatory documents. The site is now ready for required training and vendor qualifications as well as delivery of supplies.

The site is notified of regulatory documents receipt, and that all requirements are fulfilled. Generally, in less than 10 days, the site is ready to receive the study drug.

Upon receipt of the study drug, the site is ready for step 5, a site initiation visit; following this, the site is open for enrollment.

Finally, the site is ready for patient authorization of informed consent, upon which the patient fulfills all inclusion/exclusion criteria, and, in less than 14 days, patient treatment begins.

In summary, JIT trials provide a rapid solution to a series of problems facing clinical trial sponsors, oncologists, patients, and society.

In what ways might we reduce the 4 drivers of cancer health disparities in a scalable, systematic, and repeatable way? True diversity in clinical trials demands doing things differently today, not tomorrow or in the future.

The promise of PM requires making PM more precise, and JIT trials are 1 tool capable of rapidly increasing access to clinical trials to develop drugs that treat the diverse and unique tapestry of patients across the US, especially patients with more diverse racial, ethnic, and socioeconomic backgrounds.

1. National Institutes of Health. What is PM? Medline Plus. Accessed July 23, 2022. https://bit.ly/3Q0OzFD

2. Khoury MJ, Galea S. Will precision medicine improve population Health? 

. 2016;316(13):1357-1358. doi:10.1001/jama.2016.12260

3. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. 

. 2016;50(3):398-401. doi:10.1016/j.amepre.2015.08.031

4. 2015–2019: drug trials snapshots summary report. US FDA. Accessed July 23, 2022. https://bit.ly/3PHlwaB

5. Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. 

. 2002;94(5):334-357. doi:10.1093/jnci/94.5.334.

6. Anderson GD. Sex and racial differences in pharmacological response: where is the evidence? pharmacogenetics, pharmacokinetics, and pharmacodynamics. 

 (Larchmt). 2005;14(1):19-29. doi:10.1089/jwh.2005.14.19

7. Zopf Y, Rabe C, Neubert A, et al. Women encounter ADRs moreoften than do men. 

. 2008;64(10):999-1004. doi:10.1007/s00228-008-0494-6.

8. Mak WW, Law RW, Alvidrez J, Pérez-Stable EJ. Gender and ethnic diversity in NIMH-funded clinical trials: review of a decade of published research. 

. 2007;34(6):497-503. doi:10.1007/s10488-007-0133-z.

9. McCollum AD, Catalano PJ, Haller DG, et al. Outcomes and toxicity in african-american and caucasian patients in a randomized adjuvant chemotherapy trial for colon cancer. 

. 2002;94(15):1160-1167. doi:10.1093/jnci/94.15.1160.

10. Drug Trials Snapshots: Ninlaro. U.S. FDA. Accessed July 23, 2022. https://bit.ly/3PYarl9

Articles

Just-in-time trials are 1 tool capable of rapidly increasing access to clinical trials to develop drugs that treat the diverse and unique tapestry of patients across the United States, especially patients with more diverse racial, ethnic, and socioeconomic backgrounds.

Can Just-in-Time Clinical Trials Reduce Disparities in Participation?

The rapid progression of novel immune-based treatment strategies in solid tumors—beginning with the approval of immune checkpoint inhibitors (ICIs) for melanoma in 2011 and subsequent approval of numerous agents in the ICI therapeutic category—has revolutionized treatment of advanced cancers that were deemed invariably fatal until the past decade.

 Faster development of novel biomarker-driven targeted therapies has accelerated hope and optimism about converting advanced solid tumors into chronic diseases. These advances have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

One critical enigma facing clinicians is how to differentiate between pseudoprogression (PSP), true disease progression (TDP), and hyperprogression (HPD). These phenomena are observed in patients treated with ICIs targeting CTLA-4, PD-1, or PD-L1 that are approved for use across multiple types of advanced cancers. The lack of consensus or an analytic framework to decipher and differentiate between early indications of PSP, TDP, and HPD may expose patients to avoidable harm.

Another challenge centers around selecting the most appropriate therapeutic intervention when broad-based genomic profiling results reveal multiple actionable biomarkers vs actionable genomic driver mutations such as those found in 

, and a number of other targetable pathogenic genomic alterations. Selecting the right drug at the right time for patients is further complicated by these considerations:

The disparate timing of receiving results from PD-1/PD-L1 immunohistochemistry testing vs next-generation sequencing (NGS) testing 

 Determining the adequacy of NGS panel testing with negative results, whether using a whole exome sequencing or comprehensive genomic profiling approach

For this review we will confine our discussion to the clinical impact associated with the determination of PSP, TDP, and HPD following ICI therapy. Even the definitions of TDP, PSP, and HPD have not reached uniform consensus, so we will focus on clinical implications.

Although an accurate consensus has not been reached on defining PSP or HPD, differentiating between those clinical states is critically important. PSP indicates efficacy of ICI therapy, whereas HPD portrays ineffective treatment with ICIs resulting in a rapid negative clinical outcome in most cases. PSP is a type of response to ICI therapy accompanied by an apparent initial increase in tumor size or new lesions, which potentially appear upon radiological assessment, followed by an eventual decrease in tumor burden. Although this response favors patients receiving ICI therapy, a lack of awareness can lead to premature discontinuation of treatment because of an incorrect clinical interpretation of disease progression.

The incidence of ICI therapy–associated PSP varies from 3.70% to 15% in different tumor types.

 PSP is a relatively uncommon response defined as an initial increase of tumor size followed by a measurable response to treatment. ICI therapy–associated PSP results from an exacerbated immune cell infiltration in the tumor bed (T cells expressing CD103+ and CD8+).

Another postulated mechanism of PSP described by Cohen et al11 occurred in a case of PSP involving brain metastases in a patient with melanoma after treatment with pembrolizumab (Keytruda). The histology revealed an inflammatory reaction identified as isolated clusters of tumor cells surrounded by reactive astrocytosis and inflammatory cells.

 PSP associated with ICI therapy carried a higher likelihood of 1-year survival when compared with TPD.

 Failure to distinguish PSP from TPD may result in premature discontinuation of treatment with ICI, leading to adverse outcomes. It is crucial to distinguish between TPD and PSP.

HPD can be defined as an accelerated tumor growth pattern after exposure to ICI therapy, with an increase in the absolute mass of tumor cells in a relatively short time. Possible explanations of HPD in response to ICI may include the expansion of PD-1–positive regulatory T cells, exhaustion of compensatory T cells, modulation of protumorigenic immune cell subsets, and activation of aberrant inflammation cell cycle signaling.

 HPD may be observed as a rapid escalation in the size and bulk of masses of measurable tumor volume, the appearance of numerous new lesions, and/or rapid deterioration in organ function leading to symptomatic disease progression (similar to jaundice from a rise in bilirubin and liver enzymes), and/or shortness of breath from the progression of metastases in the lungs or deterioration of brain metastases leading to worsening central nervous system symptoms. Efforts have been made to define HPD based on tumor growth rate (TGR), tumor growth kinetics (TGK), and other RECIST parameters to better define HPD. However, such efforts are often in isolation and limited to institution-based criteria.

 published a study after exhaustive and systematic analysis to define HPD. They concluded that the clinical interpretation of HPD appears diverse, with the incidence of HPD varying from 5.9% to 43.1% across studies examined in their meta-analysis. They also highlighted the critical unmet need for establishing uniform and clinically relevant criteria based on currently available evidence to define HPD. One of the most compelling reasons to identify true HPD is the association of patients with HPD with extremely poor prognosis. Several studies reported worse progression-free survival and overall survival in the subgroup analysis of patients with HPD.

 Earlier identification of patients with HPD could lead to quicker adjustment of therapeutic selection to improve the dismal clinical outcomes currently associated with HPD. Because there remains no clear consensus around the definition of HPD at the time of writing this article, we simply define HPD as resulting in the rapid clinical acceleration of tumor growth resulting in shortened patient survival.

With the rapid strides in immune-based treatment options in patients with advanced solid tumors in the past decade, we have seen significant clinical improvement in patient quality of life and quantitative improvement of clinical outcomes. However, increased utilization of ICI therapies has also led to the recognition of new clinical challenges associated with a small but not insignificant number of patients, where failure to distinguish between TPD, PSP, and HPD clearly has an impact on patient lives. It is critical that our research communities start paying more attention to and providing clinical guidance around the following issues:

Recognition of HPD as a critical clinical phenomenon and not just a concept characterized by acceleration of measurable and quantifiable disease by radiologic assessment 

With the reported incidence of HPD being higher compared with PSP, emphasizing the importance of identifying HPD as early as possible, because it can occur within weeks of starting ICI therapy and result in higher mortality 

Establish clear criteria that may facilitate and support conclusive assessment of HPD vs either true PD or PSP, which may include assessment of TGR, TGK, number and increase in metastatic lesions, growth in the size of the target lesions, and additional RECIST-defined criteria

Create a consensus of baseline timing of imaging studies prior to starting ICI treatment as it can impact interpretation of subsequent studies either as a standard of care or symptom directed protocols to make it easier to correlate to pretreatment findings to distinguish between TPD, PSP, and HPD 

Continue research to establish whether HPD is related to specific cancer subtypes or other patient comorbidities, including preexisting conditions

 Identify whether HPD is therapeutic agent specific or class specific (ie, like anti– CTLA, anti–PD-1, or anti–PD-L1 therapies)

Although ICI approaches are now a mainstay in therapy, challenges to optimal benefit, such as PSP, TDP, and HPD, require continued vigilance.

1. Balar AV, Weber JS. PD-1 and PD-L1 antibodies in cancer: current status and future directions. 

. 2017;66(5):551-564. doi:10.1007/s00262-017-1954-6 

2. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. 

. 2018;359(6382):1350-1355. doi:10.1126/science.aar4060 

3. Nishino M. Pseudoprogression and measurement variability. 

. 2016;34(28):3480-3481. doi:10.1200/JCO.2016.67.6759

4. Reckamp KL. Real-world pseudoprogression: an uncommon phenomenon. 

. 2018;13(7):880-882. doi:10.1016/j. jtho.2018.05.011 

5. Doherty MK, Jao K, Shepherd FA, Hazrati LN, Leighl NB. Central nervous system pseudoprogression in a patient treated with PD-1 checkpoint inhibitor. 

. 2015;10(10):e100-e101. doi:10.1097/JTO.0000000000000587 

6. Lewis GD, Jonasch E, Shah AY, et al. Renal cell carcinoma brain metastasis with pseudoprogression and radiation necrosis on nivolumab after previous treatment with stereotactic radiosurgery: an illustrative case report and review of the literature. 

. 2018;8(5):e262-e265. doi:10.1016/j.prro.2018.03.003 

7. Fujimoto D, Yoshioka H, Kataoka Y, et al. Pseudoprogression in previously treated patients with non–small cell lung cancer who received nivolumab monotherapy. 

. 2019;14(3):468-474. doi:10.1016/j.jtho.2018.10.167 

8. Ribas A, Wolchok JD, Robert C, et al. P0116 Updated clinical efficacy of the anti–PD-1 monoclonal antibody pembrolizumab (MK-3475) in 411 patients with melanoma. 

. 2015;51(suppl 2):e24. doi:10.1016/j.ejca.2015.06.072

9. Nishino M, Giobbie-Hurder A, Manos MP, et al. Immune-related tumor response dynamics in melanoma patients treated with pembrolizumab: identifying markers for clinical outcome and treatment decisions. 

. 2017;23(16):4671-4679. doi:10.1158/1078- 0432.CCR-17-0114 

10. Rocha P, Hardy-Werbin M, Naranjo D, et al. CD103+CD8+ lymphocytes characterize the immune infiltration in a case with pseudoprogression in squamous NSCLC. 

. 2018;13(10):e193-e196. doi:10.1016/j.jtho.2018.05.008 

11. Cohen JV, Alomari AK, Vortmeyer AO, et al. Melanoma brain metastasis pseudoprogression after pembrolizumab treatment. 

. 2016;4(3):179-182. doi:10.1158/2326-6066.CIR-15-0160 

12. Kurra V, Sullivan RJ, Gainor JF, et al. Pseudoprogression in cancer immunotherapy: rates, time course and patient outcomes. 

. 2016;34(suppl 15):6580. doi:10.1200/JCO.2016.34.15_suppl.6580

13. Frelaut M, Le Tourneau C, Borcoman E. Hyperprogression under immunotherapy. 

. 2019;20(11):2674. doi:10.3390/ ijms20112674

14. Park HJ, Kim KW, Won SE, et al. Definition, incidence, and challenges for assessment of hyperprogressive disease during cancer treatment with immune checkpoint inhibitors: a systematic review and meta-analysis. 

. 2021;4(3):e211136. doi:10.1001/ jamanetworkopen.2021.1136 

15. Champiat S, Dercle L, Ammari S, et al. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti–PD-1/ PD-L1. 

. 2017;23(8):1920-1928. doi:10.1158/1078- 0432.CCR-16-1741 

16. Saâda-Bouzid E, Defaucheux C, Karabajakian A, et al. Hyperprogression during anti–PD-1/PD-L1 therapy in patients with recurrent and/or metastatic head and neck squamous cell carcinoma.

. 2017;28(7):1605-1611. doi:10.1093/annonc/mdx178 

17. Ferrara R, Mezquita L, Texier M, et al. Hyperprogressive disease in patients with advanced non–small cell lung cancer treated with PD-1/ PD-L1 inhibitors or with single-agent chemotherapy. 

. 2018;4(11):1543-1552. doi:10.1001/jamaoncol.2018.3676 

18. Sasaki A, Nakamura Y, Mishima S, et al. Predictive factors for hyperprogressive disease during nivolumab as anti-PD1 treatment in patients with advanced gastric cancer. 

. 2019;22(4):793- 802. doi:10.1007/s10120-018-00922-8

Advances in the field have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

Ben Brown | Authors

Articles

Can Just-in-Time Clinical Trials Reduce Disparities in Participation?

Differentiating Pseudoprogression From Hyperprogression in Patients Treated With Immunotherapies