Health and environment

Are All Patients Equal in front of Precision Medicine?

Photo by STunningART on AdobeStock

Photo by STunningART on AdobeStock

Finding the right treatment for each patient is the very foundation of healthcare. If we push this principle to the extreme, precision medicine is one of the best ways to fight cancer. However, the economists Samuel Kembou and Bruno Ventelou found that, for advanced non-small cell lung cancer, there is inequality in access to this type of personalized treatment in France.

By Samuel Kembou

Samuel Kembou

Université de Lausanne

Bruno Ventelou

Bruno Ventelou

Auteur scientifique, AMSE, CNRS

Lucien Sahl

Lucien Sahl

Journaliste scientifique

What will healthcare look like tomorrow? One approach of particular interest is personalized medicine, also known as precision medicine. This focuses on improving prevention, diagnosis, and treatment based on a patient’s biological makeup, particularly through the use of their genetic information. Artificial intelligence plays a large role in treating the “massive database” of patient information, which helps medical professionals make their decisions. Several countries are investing in this domain with partnerships and ambitious national plans, such as the United Kingdom’s 100,000 Genomes Project.

France is also in the race, particularly with its Genomic Medicine 2025 plan.1  What is the anticipated outcome of the project? Improving patient treatment and follow-up at a reduced cost for society without renouncing one of the basic principles of the French healthcare system: equality for all. However, the economists Samuel Kembou and Bruno Ventelou reveal disparities already exist in France regarding access to personalized medicine.

Tailored Healthcare?

With its ability to be preventative, predictive, and even participative, personalized medicine allows healthcare professionals to identify the most adapted treatment for each patient. By avoiding unnecessary care and improving treatment, the concept is both economically and medically advantageous.

Treatment in personalized medicine generally begins with genetic and molecular analyses to determine what makes each patient unique. From this information, a profile of every individual is compared to others to identify which subpopulation they belong to. From this, adapted treatment can be applied to their personal situation. In other words, personalized medicine collects and analyses data with the goal of categorizing patients to offer the right treatment (or fine-tune the diagnosis) at the right time.

From Healthcare to Social Sciences and Geography

Lung cancer is the most fatal cancer, with 1,796,144 deaths worldwide in 2020.2 This figure can be explained by the fact that this type of cancer has a greater incidence rate (with over 2 million new cases a year) and mortality rate than any other cancer. In France, genomic identification of some associated mutations is part of the standard diagnosis procedures.

To better understand the relationship between incidence, the consequence of mutations, and treatment, the French National Cancer Institute supported an ambitious biomedical research program known as the Biomarkers France study. It aimed to categorize all the mutations of six genes present in patients with the most common form of lung cancer, advanced non-small cell lung cancer (NSCLC), sent to one of twenty-eight different molecular genetic platforms around the country. Carried out between April 2012 and 2013, data from more than 17,500 individuals were collected to study the signature mutations.

Samuel Kembou and Bruno Ventelou used this data to examine the uniformity of access to personalized medicine across the country. To begin, they determined the access rates per region. Then, they used socio-economic, demographic, and administrative data to explain the differences observed in access to personalized medicine (aka genetic testing).

Inequality Among Location

Their analysis revealed that genetic testing was performed on 46.87% of patients aged 20 to 99 years old and 42.82% of patients over 60. However, these averages hide the significant disparities between departments, which we can see in the map of rates of access. The department with the lowest testing rate was Nièvre, three times less than Côtes-d’Armor, with the highest testing rate.

So, how can these differences be explained? To answer these questions, the authors tried identifying which parameters correspond to the various genetic testing rates.

It should be no surprise that healthcare professionals’ presence influences testing. A greater proportion of radiotherapists leads to more testing. Their presence could indicate cutting-edge equipment availability, leading to more testing. However, the more surgeons, the fewer tests in the department. This may be because the presence of surgeons leads to treatments by surgical interventions, which consequently require less genetic testing.

Wealth and Health

There is a link between an individual’s social status and his health. Existing studies demonstrate that less fortunate individuals have a lower life expectancy, associated with a higher risk of cardiovascular diseases and cancer.3  This could be explained by greater exposure to risks like malnutrition or even smoking. A lower socio-economic status is moreover often associated with reduced access to quality care. What does this mean for the various French departments and access to genetic testing?

The economists consider two parameters to measure the economic disadvantage of the various departments. These are the poverty rate and the proportion of residents on Couverture Maladie Universelle Complémentaire (CMU-C).4

The analysis reveals that patients with NSCLC are less likely to receive genetic testing if they live in less deprived departments. This applies to all the departments within mainland France and has no geographic correlation whatsoever.

Therefore, a low department’s economic status is statistically linked to lower genetic testing. It could be that there is a lack of appropriate healthcare options, equipment, or even professionals capable of prescribing and performing this type of testing compared to the needs within that department. The authors recognize that more research is needed to better interpret the data.

  • 3Stringhini, S. et al. Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women. Lancet 389, 1229–1237 (2017).
  • 4A complementary health insurance that is only given to those whose income is below a particular level.

A Look at Physician Practices in Personalized Medicine

Samuel Kembou, Bruno Ventelou, and David Bardey also examined the factors that could encourage practitioners to include personalized medicine in their patient treatment strategy.
Economics is a science practiced without lab coats or test tubes, so how is an experiment performed in an economics lab? Primarily by volunteer subjects whose choices in a real-effort game lead to rewards of various levels according to their performance. In this case, the researchers’ data was the participants’ behavior in these games.
To simulate the interaction between practitioners and patients, they randomly selected pairs to improve the editing of a short text. The first player highlighted portions of the text that were possibly incorrect (symptom description by the patient). The second player was tasked with correcting the errors (treatment by the practitioner). The option of personalized medicine was simulated by the second player’s possibility of receiving more information to identify the areas to correct in the text. With 48 patient roles and 95 practitioner roles (these played exclusively by future physicians recruited from medical schools in the area), the researchers collected data for more than 4,500 pseudo-patient-practitioner interactions. They concluded that adopting personalized medicine depends on both expenses for practitioners (administrative, financial, logistic, and even cognitive) and their financial rewards. Economic measures (primarily compensation schemes) have thus been proposed to push professionals in the medical field to adopt personalized medicine techniques.

Source : Bardey D., Kembou S., Ventelou B., 2021., “Physicians’ Incentives to Adopt Personalised Medicine: Experimental Evidence.” Journal of Economic Behavior & Organization ,191, 686–713

A Broken Promise

The French Constitution “guarantees [...] the protection of healthcare for all”.5  Therefore, the state must ensure access to quality medical treatment and prevention services, without distinction or restriction, to all.

Even the protection of healthcare for all is included in the French Constitution. This work reveals some inequality in accessing personalized medicine for cancer. This reinforces the argument that access to treatment for all is a priority challenge for the healthcare of tomorrow. However, by indicating these blind spots, the researchers allow public authorities to develop solutions through new laws and targeted investments in the healthcare system.


  • 5Preamble to the Constitution of 27 October 1946, the Constitutional Council https://www.conseil

Translated from French by

Natalie Worden


Nzale S. K., Weeks W. B., Ouafik L., Rouquette, I., Beau-Faller M., Lemoine A., Bringuier P.-P., Soriano A.-G. L. C., Barlesi F., Ventelou, B.,2020, « Inequity in access to personalized medicine in France : Evidences from analysis of geo variations in the access to molecular profiling among advanced non-small-cell lung cancer patients: Results from the IFCT Biomarkers France Study ». PLOS ONE, 15(7), e0234387.