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| EDITORIAL |
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| Year : 2022 | Volume
: 2
| Issue : 1 | Page : 1-2 |
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Transitional oncology and the evidence hyperloop
US Vishal Rao
Editor in Chief, JPO Department of Head and Neck Oncology, HealthCare Global Cancer Center, Bengaluru, Karnataka, India
| Date of Submission | 11-Feb-2022 |
| Date of Decision | 15-Mar-2022 |
| Date of Acceptance | 16-Mar-2022 |
| Date of Web Publication | 03-May-2022 |
Correspondence Address:
Prof. Dr. U S Vishal Rao
Department of Head and Neck Oncology, Centre for Academic Research, HealthCare Global Cancer Centre, Bengaluru, Karnataka
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/jpo.jpo_10_22
How to cite this article:
Vishal Rao U S. Transitional oncology and the evidence hyperloop. J Precis Oncol 2022;2:1-2 |
Translational oncology is a multidisciplinary concept marked by its transformative approach to evidence, which implies that evidence is envisaged and derived at the bench and applied at the bedside. However, there are several key concepts, ideas, and innovations that are modified or lost by the time the science transitions from the bench to bedside. Consequently, some of the intended benefits of transitional evidence do not reach the end user, i.e., the patient.
Typically, translational oncology, from its conceptual stage at the bench to the consequent stage at the bedside, is a very time and resource-consuming process typically spanning close to 17 years. The conceptualization of a hypothesis begins with laboratory research that paves the way for clinical research to assess safety and efficacy in the form of Phase 0 to Phase II studies.[1],[2] Postclinical validation, the hypotheses are subjected to stringent testing through clinical Phase III and Phase IV trials for stipulating clinical guidelines.[2] Completion of all these steps corroborates the clinical practice which as mentioned above takes 17 years on an average. During this process of translating a bench-side hypothesis into clinical practice, a lot of science is inadvertently diluted, thereby defeating the purpose of the intended clinical use to benefit the patients.[3]
There is an evolving thought rooted in reversal, i.e., a bedside-to-bench research that seeks to build evidence using the science that is being modified and lost in the process of the translational research. Extracting meaningful evidence from the bedside practices and generating new scientific hypotheses thereby helps create a hyperloop of evidence.
While the bedside-to-bench paradigm[4] has largely been contemplated in theory, the COVID-19 pandemic provided a classic real-time case study of how data from the bedside can effectively drive research hypotheses. The case study adequately and adroitly demonstrated the hyperloop of evidence between translational and transitional research. Bedside data[5] has played a pivotal role in helping clinicians comprehend various aspects of the virus, including its natural history, mutagenicity, immune response in terms of cytokine storms, different causes of death, correct treatment planning and procedures, moderation of drug use, preventive safety measures, and even in coming to terms and living with it.[6] The pandemic has helped build a vital bridge between two ends, on the one side are the practicing hypotheses that have gone through rigorous and phased testing; on the other side are the intensivists and clinicians who have had to think on their toes as to what might work based on bedside experience. The pandemic case study has underlined the acute need to bridge concepts, ideas, innovations, theories, and discoveries lost in transit, as also to reconnect them either through bench to bedside or bedside to bench research in a collective manner. Only a holistic, solution-centric ecosystem can connect these gaps.
The Association of Transitional Oncology defines the term “transitional oncology” as one that should be able to address such missing sciences and make them integral to evidence-based medicine. The association has proposed that transitional oncology must look at all concepts that are either in vogue or have been contemplated and have suffered loss in transition due to a lack of connect, either from bench to bedside or from bedside to bench. Transitional oncology is being proposed as a potent paradigm to address the missing gaps in science by approaching existing problems using newer aspects, concepts, and ideas toward achieving better oncological outcomes.
| Toward Serving the Larger Cause of Personalized and Precision Medicine | |  |
In November of 2017, the Lancet Commission published an incisive paper[7] called the Future cancer research priorities in the USA, highlighting the key recommendations of the 2016 Blue Ribbon Panel, which was setup by NIH to fund the future of cancer research. This discussion leads highlighted five focus areas: immunotherapy, precision medicine, personalized medicine, big data, and enabling technologies. Today, a lot of science and concepts are centered on the key aspect of personalized medicine and precision medicine in oncology. The oncology fraternity must hence study transitional oncology in a broader perspective to understand and encompass the “science missed in transition” toward serving the cause of personalized and precision medicine.
For practicing clinicians, it is often difficult to keep track of emerging evidence from the bench to bedside and even more complicated to fathom what might have been lost in the process. It is important for clinicians to acknowledge the current era of clinical science which is marked by fusion medicine. Today, an interventional radiologist assumes the key role of a navigation surgeon as an integral member of the OT team.[8] Clinical scientists must actively strive to bridge the bench to bedside gap, thereby making science more accessible and relevant to patients. Transitional oncology must create a hyperloop between bench and bedside so that clinical decisions become fast and efficient toward achieving both cancer ground shot and cancer moonshot! Among other things, clinicians must:
- Re-examine the bedside small data to appreciate the fact how systematically accrued small data becomes highly relevant to the big data and thus helps generate relevant hypothesis. Statistical outliers are often ignored in conventional oncology research paradigms, but rich data often emerges out of the deep understanding of these outliers.
- Study bedside observations and experiences to become more focused and less linear. There is a need to develop strategies to include data derived from bedside medicine and curate relevant questions for a comprehensive analysis of patient experiences, patient outcomes, and biological behaviors.
- Apply learnings to the bench in the form of newer and deeper hypotheses or the negation or enhancement of old theories that were prior assumed to be proven.
This approach will pave a fresh path to debunking old theories, disrupting the status quo, and reimagining evidence-based medicine in the light of precision oncology. How does one reimagine evidence-based medicine? When a clinician talks to the patient in terms of a percentage success rate of a surgery or a medical oncologist talk about response rates of different drugs, they are relying heavily on one section of the evidence. Transitional oncology would change this lopsided pattern of communication. Everything-based medicine is slowly moving toward creating a judicious balance between statistical significance and clinical significance in the era of precision oncology.
Given the compelling need for integrated oncology, which includes information obtained from bioinformatics, computational biology, pharmacogenomics, and clinical responses, we will need to look at new ways to curate evidence based on small data, which need not rely only on statistical significance, but also at clinical significance. These evolving methods will go a long way toward constituting a new benchmark in evidence-based medicine.
| References | | |
| 1. | Glass DJ, Hall N. A brief history of the hypothesis. Cell 2008;134:378-81.  |
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| 3. | van der Laan AL, Boenink M. Beyond bench and bedside: Disentangling the concept of translational research. Health Care Anal 2015;23:32-49. |
| 4. | Balasubramaniam V, Lee LK, Javier JR. A new paradigm in bench to bedside research, with a stop in the dusty pharmaceutical cabinet? Pediatr Res 2021;89:1604-5. |
| 5. | Ji L, Cao C, Gao Y, Zhang W, Xie Y, Duan Y, et al. Prognostic value of bedside lung ultrasound score in patients with COVID-19. Crit Care 2020;24:700. |
| 6. | Boero E, Rovida S, Schreiber A, Berchialla P, Charrier L, Cravino MM, et al. The COVID-19 Worsening Score (COWS) – A predictive bedside tool for critical illness. Echocardiography 2021;38:207-16. |
| 7. | Jaffee EM, Dang CV, Agus DB, Alexander BM, Anderson KC, Ashworth A, et al. Future cancer research priorities in the USA: A Lancet Oncology Commission. Lancet Oncol 2017;18:e653-706. |
| 8. | Smith KA, Kim HS. Interventional radiology and image-guided medicine: Interventional oncology. Semin Oncol 2011;38:151-62. |
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