Sixty years ago, the physicist Thomas Kuhn published a landmark piece, which was highly influential in the history, sociology, and philosophy of science: “The Structure of Scientific Revolutions.”1 In his work, Kuhn challenged the prevailing view that scientific progress is achieved through what he called “normal” science: an accumulation of results derived from gradual experimentation. He proposed instead that scientific progress is brought about by revolutionary changes—paradigm shifts.
Looking back, the adoption of low-dose CT (LDCT) as a lung cancer screening tool, seems to fit the Kuhn paradigm shift theory. The prevailing nihilistic view that screening for lung cancer cannot work, based largely on flawed trials involving chest radiography as a screening tool, has now been replaced by widespread recommendations for LDCT-based screening programs. LDCT-based lung cancer screening is now recommended by some national health authorities, medical societies, and is currently reimbursed by healthcare providers in a number of countries. In fact, resistance from established paradigms, as Kuhn foresaw in his book, lingers, despite overwhelming evidence supporting the new paradigm.
Find More at WCLC 2022
Learn more about efforts to improve lung cancer screening during ES01—Implementation and Continuous Optimization of Lung Cancer Screening. The session will take place from 10:45-11:45 CEST on Sunday, August 7, in Hall C1.
The scientific advisory board of the European Union recently issued a position statement with the following: “There is strong scientific evidence for adding low-dose CT lung cancer screening for current and ex-smokers to the repertoire of population-wide organized screening programs across the EU, particularly considering the high number of deaths caused by the disease every year. This should go hand-in-hand with smoking cessation interventions to maximize benefits and increase cost-effectiveness.”2
Emphasis is placed on the combination of primary (smoking cessation) and secondary (LDCT) prevention to tackle the unacceptable death toll lung cancer causes in the EU. That notwithstanding, the document calls for more research to optimize screening and devotes a whole chapter to the development of biomarkers.
Screening for lung cancer is imperfect. Unmet clinical needs persist in this regard, including the refinement of selection criteria and follow up of screening findings. Updated 2021 USPSTF recommendations are proof of this by expanding age criteria and reducing cumulative tobacco exposure for eligibility.3The USPSTF committee recognized that factors beyond age and smoking history may be relevant to further refine risk but cited insufficient evidence to assess whether risk prediction models can help. Both the USPSTF and the European Union document singled out the need for more research.
Specifically, there is a call for research to identify biomarkers that can accurately identify people at high risk and minimize false positive results, explore technologies that can discriminate between benign and malignant nodules, and employ risk prediction models to select patients for lung cancer screening. The search for robust biomarkers capable of reinforcing and optimizing this novel strategy, could potentially lead to yet another revolutionary paradigm shift in the history of our fight against lung cancer. Many candidates have been postulated, including blood-based biomarkers, urine-based biomarkers, and exhaled breath.4
Unfortunately, clinical validation takes time, funding, and effort. The contribution of different independent screening cohorts will be necessary to identify biomarkers that can make a difference. Indeed, only a global collective validation effort will be able to meet the challenge of developing a robust and clinically useful biomarker capable of making LDCT-based lung cancer screening better and more efficient. Radiomics variables, together with risk models, can also be combined with the best performing biomarkers when aiming for nodule characterization within screening. The combination of biomarkers and risk models seem to be the way to go when the objective is refining selection criteria for individuals to undergo screening.
Fahrmann et al., have recently reported in the Journal of Clinical Oncology on just such an approach.5The combination of a simple blood-based biomarker panel, combined with a risk model calculation, could go a long way to meeting the clinical need facing lung cancer screening inclusion criteria today. In their work, the authors test a plasma-based molecular tool for improving lung cancer risk assessment. They performed a validation study using Prostate, Lung Colorectal, Ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of four previously studied plasma proteins in combination with a lung cancer risk prediction model (PLCOm2012). This combination was compared with current USPSTF screening criteria. The 4MP levels were analyzed in 1,299 sera collected before lung cancer diagnosis and 8,709 control (non-case) sera. Their conclusion is that this blood-based biomarker panel in combination with PLCOm2012 significantly improves lung cancer risk assessment for lung cancer screening.
Fahrmann’s and other groups testing alternative biomarker panels has shown the potential for high accuracy and acceptable cost effectiveness. The present study includes some added complexity in the design and interpretation of the results since it performs comparisons with the two USPSTF criteria (the first one and the 2021 update). That notwithstanding, the biomarkers included in the 4MP are well known to the lung cancer clinician or researcher, and have been employed also in nodule characterization, another unmet clinical need and surrogate endpoint in lung cancer screening biomarker research. In fact, the same authors compared previously the performance of 4MP in comparison with measuring nodule size.6
The risk assessment findings in this recent JCO paper are provocative and merit prospective validation.
Several biomarker panels are currently being explored as LDCT companions for both risk assessment and nodule characterization. The latest developments include cell-free DNA sequencing, methylation, and fragmentomics. Unfortunately, prospectively designed implementation is lacking. New screening cohorts need to collect biological samples and include biomarker exploratory research in their protocols to validate biomarkers prospectively. Perhaps now that a revolution in lung cancer diagnosis has arrived, it is time for some good old ¨normal¨ science to provide the evidence to move forward, refine risk assessment, and validate robust biomarkers as companions to the revolutionary LDCT based paradigm.
- 1. Kuhn, T.S. The Structure of Scientific Revolutions: 50th Anniversary Edition. 4th edition. (University of Chicago Press, 2012).
- 2. SAPEA, Science Advice for Policy by European Academies. (2022). Improving cancer screening in the European Union. Berlin: SAPEA. Pg.13 https://doi.org/10.26356/cancerscreening
- 3. US Preventive Services Task Force, Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, DavisEM, Donahue KE, Doubeni CA, Kubik M, Landefeld CS, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, StevermerJ, Tseng CW, Wong JB. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2021 Mar 9;325(10):962-970. doi: 10.1001/jama.2021.1117. PMID: 33687470.
- 4. Seijo LM, Peled N, Ajona D, Boeri M, Field JK, Sozzi G, Pio R, Zulueta JJ, Spira A, Massion PP, Mazzone PJ,Montuenga LM. Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges. J Thorac Oncol. 2019Mar;14(3):343-357. doi: 10.1016/j.jtho.2018.11.023. Epub 2018 Dec 4. PMID: 30529598; PMCID: PMC6494979.
- 5. Fahrmann JF, Marsh T, Irajizad E, Patel N, Murage E, Vykoukal J, Dennison JB, Do KA, Ostrin E, Spitz MR, Lam S,Shete S, Meza R, Tammemägi MC, Feng Z, Hanash SM. Blood-Based Biomarker Panel for Personalized Lung Cancer RiskAssessment. J Clin Oncol. 2022 Mar 10;40(8):876-883. doi: 10.1200/JCO.21.01460. Epub 2022 Jan 7. PMID: 34995129;PMCID: PMC8906454.
- 6. Ostrin EJ, Bantis LE, Wilson DO, Patel N, Wang R, Kundnani D, Adams-Haduch J, Dennison JB, Fahrmann JF, ChiuHT, Gazdar A, Feng Z, Yuan JM, Hanash SM. Contribution of a Blood-Based Protein Biomarker Panel to theClassification of Indeterminate Pulmonary Nodules. J Thorac Oncol. 2021 Feb;16(2):228-236. doi: 10.1016/j.jtho.2020.09.024. Epub 2020 Oct 31. PMID: 33137463; PMCID: PMC8218328.
