Svoboda | Graniru | BBC Russia | Golosameriki | Facebook
Next Article in Journal
Progressing Vulvar Melanoma Caused by Instability in cKIT Juxtamembrane Domain: A Case Report and Review of Literature
Previous Article in Journal
Real-World Adherence to Toxicity Management Guidelines for Immune-Related Adverse Events
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Health Literacy and Clinical Trial Participation in French Cancer Patients: A National Survey

by
Youssoufa M. Ousseine
1,2,
Anne-Déborah Bouhnik
1 and
Julien Mancini
3,*
1
INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l’Information Médicale, Equipe CANBIOS Labellisée Ligue Contre le Cancer, Aix Marseille University, 13009 Marseille, France
2
Santé Publique France, French National Public Health Agency, CEDEX, 94415 Saint-Maurice, France
3
APHM, INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l’Information Médicale, Equipe CANBIOS Labellisée Ligue Contre le Cancer, Hop Timone, BioSTIC, Biostatistique et Technologies de l’Information et de la Communication, Aix Marseille University, 13005 Marseille, France
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2022, 29(5), 3118-3129; https://doi.org/10.3390/curroncol29050253
Submission received: 24 March 2022 / Revised: 26 April 2022 / Accepted: 26 April 2022 / Published: 28 April 2022

Abstract

:

Simple Summary

Inadequate health literacy (HL) can impair many aspects of communication, including the invitation to participate in clinical research. This study aimed to assess the relationship between HL and trial participation in French cancer patients. Our results showed that 37.6% were classified as having limited HL. One in ten (10.3%) respondents reported having been previously invited to participate in a clinical trial. Of these, 75.5% had enrolled. Limited HL was associated with fewer trial invitations but not with enrollment once invited. Addressing HL is necessary to create a more inclusive health system and to reduce inequalities not only in access to innovative cancer care, but to health inequalities in general.

Abstract

Few studies have explored the relationship between health literacy (HL) and trial participation. In this context, we aimed to study this relationship in French cancer patients. We used data from the French national VIe après le CANcer (VICAN) survey. Two questionnaire items focused on previous invitations to participate in clinical trials and subsequent enrollment. The Single Item Literacy Screener was used to measure functional HL. In total, 1954 cancer patients responded to both VICAN surveys (two and five years after diagnosis). Mean age was 54.1 ± 12.7 years at diagnosis, and 37.6% were classified as having limited HL. One in ten (10.3%) respondents reported having been previously invited to participate in a clinical trial. Of these, 75.5% had enrolled. Limited HL was associated with fewer trial invitations but not with enrollment once invited. Multivariate analysis confirmed the negative effect of limited HL on clinical trial invitation (adjOR = 0.55 (0.39 to 0.77), p < 0.001) after adjustment for multiple characteristics. Patients with limited HL received fewer invitations to participate in trials but were likely to enroll when asked. Addressing HL is necessary to create a more inclusive health system and to reduce inequalities not only in access to innovative cancer care, but to health inequalities in general.

1. Introduction

Promoting participation in clinical trials is essential to ensure continuous advances in cancer care. Inviting patients to participate is often linked to a lack of or failed standard therapeutic. Given the uncertain efficacy of experimental treatments, even in the late stage of phase III trials, participation is not always associated with better clinical outcomes [1]. Nevertheless, inviting people to participate can be considered a standard of care because it usually ensures that patients will receive a promising new treatment. More generally, patient participation in research can have other positive effects. For example, it may be psychologically rewarding [2] or it may increase satisfaction with care through consent and data collection processes [3].
Given these potential benefits of clinical trials and the need for research findings that can be generalized [4], not inviting a patient to participate may be considered inequity [5]. Most of the research conducted thus far on inequity in clinical trial participation has focused on non-modifiable factors [6] such as age, ethnicity, or socioeconomic indicators [7,8,9,10,11] rather than modifiable factors such as knowledge and attitudes towards clinical trials and health literacy (HL) [12,13,14]. Understanding the term clinical trial and the vocabulary associated with trials is important for patient engagement. Previous studies have shown that many patients do not understand what a clinical trial is, and this is a barrier to participating in clinical trials [13,14]. Misunderstanding could be related to poor promotion of the information, but it is also strongly related to a low HL. HL is defined as “people’s knowledge, motivation and competences to access, understand, appraise, and apply health information in order to make judgments and take decisions in everyday life concerning healthcare, disease prevention and health promotion to maintain or improve quality of life during the life course” [15]. To the best of our knowledge, the impact of a patient’s HL on the decision to invite him/her to participate in clinical trials has not been specifically studied, despite the fact that inequities resulting from low HL are dynamic and can be successfully tackled. More specifically, although low HL has been conceptualized as a risk factor for health, HL itself has been conceptualized as a personal asset that can be developed. This can be seen in the great number of HL-improvement programs targeted at adults [16]. Moreover, age and other psychological factors are determinants, which may influence physicians’ decisions to invite patients to participate. For example, physicians might be reluctant to suggest participation to older patients, fearing refusal or agreement despite not understanding the true implications of participation, or on the contrary, that too much time would be needed to obtain consent.
Besides the inequity in the invitation to participate because of low HL, it is also important to better understand why patients with low HL who are invited to participate in clinical trials decide not to do so. The decision not to participate might be linked to one or more dimensions of HL, including the acquisition, understanding, and use of information about clinical trials [17]. Several confounding factors may also play a role in clinical trial participation (i.e., invitation or decision to participate). Low HL patients are, on average, older, reside more often in rural areas, and are more likely to have economic difficulties [18,19]. These factors may prevent them from frequenting a comprehensive cancer center [20]. Furthermore, other clinical determinants (tumor type or stage) related to a lack of prevention and insufficient screening [21] may influence clinical trial participation.
In order to better understand potential inequities in clinical trial invitation and participation in cancer patients, as well as the factors associated with these inequities, we studied the role of HL in a sample of French cancer patients participating in the VICAN survey, while accounting for age, economic hardship, cancer type, care center, and area of residency. We hypothesized that low HL was associated with not being invited to participate in clinical trials.

2. Methods

2.1. Study Design and Participants

VICAN (VIe après le CANcer, or Life after Cancer) is a French national longitudinal survey studying patients’ living conditions, psychosocial outcomes, and health conditions two years (VICAN2) and five years (VICAN5) after cancer diagnosis [22]. All French-speaking patients, living in France for at least two years, and diagnosed with a first malignant cancer between January and December 2011 were eligible.
The target population included individuals aged 18–82 years at the time of cancer diagnosis. Twelve cancer sites (Table 1) accounting for 88% of cancer incidence in France were included. Patients were registered in the Long Duration Disease File (Affection Longue Durée (ALD)) of the three main French Health Insurance Schemes, which cover over 90% of the population. The costs for diseases listed in the ALD file are fully reimbursed by the state.
A stratified random sample of eligible patients was invited to participate in a computer-assisted telephone interview. A postal questionnaire was also proposed to patients with lung or upper aero-digestive tract cancers, to account for possible difficulties in responding orally. A medical survey was completed by the health care provider (HCP) who initiated the patient’s cancer treatment. Other medical information was collected from the national medico-administrative databases. The first wave of data collection took place in 2012, two years after diagnosis (VICAN2), and included 4347 cancer survivors. The second wave took place in 2015 and 2016, five years after diagnosis (VICAN5), and included 4174 individuals, 2009 of whom had already participated in VICAN2. The analyses presented here only concern the latter group (Figure 1).
For theses analyses, a weighting procedure was applied to obtain a representative sample in terms of age, gender, socioeconomic condition, cancer site, and tumor progression since diagnosis [22].

2.2. Variables

2.2.1. Clinical Trial Invitation and Participation (Main Outcomes)

Previous clinical trial invitations and participation were self-reported in VICAN2 using the following two questions taken from an earlier cancer patient survey [11]: “Have you ever been asked to participate in a clinical trial?”, and for those who answered “yes”, “Did you agree to participate?” As participation in clinical trials was expected to mainly occur in the first years after diagnosis in this group of survivors, these two questions were asked only in the VICAN2 survey to limit recall bias. A definition of a clinical trial was provided alongside the first question (Appendix A), in order to ensure that respondents did not refer to observational research, especially given that biobank consent forms are widely available in comprehensive cancer centers [23].

2.2.2. Independent Variables

Exposure variable: Functional HL was evaluated by the single item literacy screener (SILS) question: “How often do you have someone help you read hospital materials?” The SILS has proven its ability to predict functional HL evaluated using other self-reported measures [24] and objectively using the short version of the Test of Functional Health Literacy in Adults (S-TOFHLA) [25]. In line with a previous HL study [26], patients were considered to have low HL if they responded “rarely”, “sometimes”, “often” or “always” to the SILS question. HL was then divided into two categories: limited HL (“rarely”, “sometimes”, “often” or “always”) and adequate HL (“never”).
Sociodemographic characteristics: Age at diagnosis, gender, education level, cancer management center and area of residence (rural/small town/city vs. large town/city) were collected. The simplified deprivation index of the area of residence (IDS) was also determined using the town/city of residence (or ZIP code for larger towns/cities). It was developed as the first component of a principal component analysis of four socioeconomic variables (share of laborers in the active population aged 15 to 64 years, share of unemployed in the active population aged 15 to 64 years, share of graduates with a bachelor’s degree (minimum) in the population aged 15 or more not attending school and median household tax income) [27]. The IDS was divided into three categories of residence according to the quartiles (Q) in the sample, with higher values indicating higher deprivation (low deprivation: IDS < 1st quartile (Q1), high deprivation IDS > 3rd quartile (Q3), and medium deprivation Q1 ≤ IDS ≤ Q3). For example, survivors with low deprivation lived in areas with fewer laborers, less unemployment, many graduates, and high household incomes.
Financial resources were collected using the income per consumption unit (ICU). The ICU corresponds to total income (here, self-reported income) of the household divided by the number of consumption units (CU) in the household. This makes it possible to establish the disposable income per individual within the household. The number of CU is calculated from the OECD scale by summing the different individuals in the household using a different weight according to age: 1 for the first adult in the household (here, the respondent), 0.5 for other persons aged 14 years and over, and 0.3 for children under 14 years. The ICU was divided into three categories according to the quartiles in the sample, with higher values indicating greater financial resources (<Q1, Q1–Q3, >Q3).
Medical characteristics: Cancer type and metastatic status at the time of diagnosis were collected. Data from patient questionnaires, medical surveys completed by physicians, and from medico-administrative databases were combined [22] to define an individual chronic comorbidity score. This comorbidity score was constructed from the drugs reimbursed for 22 chronic diseases [28]. It was calculated as a weighted average of the chronic diseases identified for a cancer patient over a one-year period. Diseases with a high probability of hospitalization or death had the highest weights.

2.3. Statistical Methods

After univariate analyses using usual statistical tests (χ² test for categorical variables and ANOVA or Student’s t test for continuous variables), a multivariate binary logistic regression was used to model the probability of having been invited to participate in a clinical trial.
All variables with a p value < 0.20 in univariate analyses were eligible for the multivariate model. Age, type of residence area, cancer site and comorbidities were all systematically kept in the model. The first three factors can lead to disparity in access to clinical trials [29], while comorbidities are often associated with invitations to participate in trials [30]. The final multivariate model was built using a backward approach based on the log likelihood ratio test. Analyses were performed using SPSS 20.0 (IBM). All tests were two-sided, and the statistical significance threshold was p < 0.05.

3. Results

Of the 2009 individuals who responded to both VICAN surveys, 1954 (97.3%) responded to the SILS question and to the two questions about clinical trial invitation and participation (Figure 1). Non-respondents’ characteristics are described in a previous study [31].
The main patient characteristics are displayed in Table 1.
Over one-third of patients (37.6%) were classified as having limited HL. One in ten patients reported that they had been invited to participate in a clinical trial. Among them, 74.5% had agreed to participate (7.7% of the total sample). One of five patients (22.8%) were over 65 years old. This group was less likely to have been invited to participate (12.5% vs. 23.9% for persons <65 years old, p < 0.001). However, most of those who were invited (88%) agreed to participate (5.6% of the over 65 years old). Women were significantly more likely to have been invited to participate than men (12.3% vs. 6.5% in men, p < 0.001). This figure was no longer significant (9.7% vs. 8.5%, p = 0.335) after excluding the four gender-specific cancers surveyed (breast, cervix, endometrium, and prostate). Invitations to participate in clinical trials were more likely to occur in comprehensive cancer centers (26.2%) than other management centers (private centers 7.2%, public academic centers or community centers 10.5%, p < 0.001). The invitation to participate did not differ according to education level. However, participants with adequate HL were more likely to have been invited to participate than those with limited HL (12.2% vs. 7.1%, p < 0.001). Patients with adequate HL and those with limited HL had similar agreement rates after being invited to participate (75.8% vs. 74.5%, p = 0.409) (Figure 2).
Multivariate analysis confirmed the negative effect of limited HL on the invitation to participate in a clinical trial (Table 2).
In multivariate analysis, other sociodemographic factors associated with not being invited were older age, having fewer financial resources, and not living in a large town/city. As for univariate analyses, education level and comorbidities were not associated with the invitation to participate. Finally, being treated in a comprehensive cancer center and for lung cancer or non-Hodgkin lymphoma were associated with a higher likelihood of being invited to participate in a clinical trial.

4. Discussion

To the best of our knowledge, this is the first national French study to examine the relationship between HL and both the invitation to participate in a clinical trial and patients’ agreement to do so. Limited HL was not uncommon in the cancer patients surveyed, and it was associated with a substantially lower likelihood of being invited to participate. After adjusting for multiple confounders and potential markers of ineligibility, the effect remained in multivariate analysis. This suggests that physicians might avoid proposing trial participation to patients who they believe are more difficult to adequately inform. Most patients in our sample who had been invited to take part in a clinical trial reported that they agreed to participate. No difference in agreement was observed according to HL level.
Interest in HL is recent in France, and the only reliable available estimate of its prevalence showed that 44% of the general population have limited HL [32]. It is therefore not surprising that 37% of cancer survivors in our study had limited HL. The estimated percentage of limited HL for French cancer survivors that we found is also consistent with limited HL rates observed for various states in an American study validating the SILS in patients with pathologies different from cancer (40% in hemodialysis patients in North Carolina [25] and 37.8% in diabetic patients in Ohio [33]). Furthermore, the rate of participation in our study was consistent with cancer trial participation rates reported in France.
Only one in ten patients (10.3%) in the present study reported that they had been invited to participate in a clinical trial. Of those invited, most (75.5%) agreed. This low overall participation rate (7.7%) is consistent with the rates estimated by the French national cancer institute (INCa) for 2010 (between 7.5% and 8.5%, or 11% when the estimate was based only on the incidence rate) [34].
Consistent with previous research in the United States of America and in other European countries [7], our results highlighted several inequities related to socioeconomic status and age. Patients with fewer financial resources were less likely to be invited to participate in clinical trials after adjustment for all the other characteristics. Participation in France does not generate financial compensation for participants. This would suggest that for some patients, indirect costs [35] may be a barrier to being invited. This financial-based inequity and other inequities related to living in a rural area or being provided care in small local private care centers have recently been remedied through the organization and funding of équipes mobiles (mobile clinical research teams), the aim being to increase research in all care centers in the country and to help patients who agree to participate in clinical trials to reach reference centers by covering their transportation and housing costs.
Our study showed that the type of cancer care was strongly related with the invitation to participate in clinical trials. This is consistent with the international literature [36] and with previous French data showing that 39% of participants in a cancer-based trial was recruited in comprehensive cancer centers [34]. In addition, a French study on patients with stomach cancer showed that invitations to participate in clinical trials were less likely in private institutions that had fewer human resources dedicated to clinical research [37]. To remedy this, structural solutions must be put in place such that community and public academic centers can refer patients with treatment failure to comprehensive centers to ensure equitable access to clinical trials. Moreover, we found that patients living in a large town/city were more likely to have been invited to participate in a clinical trial. This is in line with findings from previous studies on geographical disparities in cancer clinical trial participation [38,39], and it could be partly explained by easier access to comprehensive centers that tend to be located in or near large towns/cities.
Efforts have also recently been made to increase the participation of older cancer patients in clinical trials. Our results confirm that this sub-population was less likely to have been invited to participate in a clinical trial, even after adjustment for major comorbidities. This would suggest that non-eligibility might not fully explain why older people are less likely to be invited. The 5.6% of patients over 65 years old in our study who were invited to/agreed to participate is consistent with previous estimates and with France’s national objective to increase participation to 5% in elderly patients [34]. Another possible explanation as to why older patients were less likely to be invited was that they might have been perceived as having a lower HL level. However, the age effect persisted after accounting for HL level. Accordingly, we can suppose that advanced age is a major factor in inequality in access to clinical trials. The hypothesis that subjective elements (e.g., compliance, attachment, comprehension, etc.) may explain this result cannot be dismissed.
After multiple adjustments, limited HL remained associated with a lower likelihood of being invited to participate in a clinical trial, highlighting that HL is a source of inequity for all cancer patients irrespective of age. This confirms our study hypothesis and the—albeit scarce—literature showing that low HL could be a barrier to participation in cancer clinical trials. Although health literacy was significantly associated with an invitation to participate, education level was not. This suggests that physicians are more sensitive to their patients’ level of understanding than to their level of education. One might argue that not suggesting participation to those perceived as having low HL might be something positive, if the research actors involved are not able to obtain full informed consent. This is particularly relevant in terms of oncology 3.0, where consent forms continue to increase in length and complexity. However, it seems more reasonable to consider limited HL as a social inequity that must be combated.
Although HL is associated with the invitation to participate in clinical trials, this does not rule out a possible literacy bias. Some patients might not be invited to participate in clinical trials independent of HL but in relation to other factors, including misunderstanding of clinical trials, socioeconomic [40], contextual, or other. Thus, our results should be interpreted with caution and should underline interest to consider, in the future, a holistic approach to improve patient’s understanding of clinical trials [14] in order to increase participation of all population categories. A lack of knowledge about clinical trials can influence trial participation (i.e., invitation and agreement) [41], and specific interventions have been proposed to improve this situation [42]. Such interventions include: (i) patient education to improve clinical trial knowledge, (ii) early distribution to the patient of a list of questions about the clinical trial in order to stimulate discussion with the physician when discussing possible participation [42,43], (iii) simplifying information documents to make them easier to read and understand for low HL patients [44,45], (iv) developing standardized patient decision aids to improve cancer trial recruitment [46], (v) and creating patient guides to help patients with limited HL to better understand clinical trials. Patient guides have already been shown to help overcome barriers to screening for cancer [47]. All things considered, we believe that multilevel interventions are likely to be the most effective method to increase participation [48].
Our study has limitations. We did not measure the reasons why patients agreed to participate in a clinical trial (e.g., to further research, new therapeutic offer, etc.) or the differences between the level of offer and demand. However, previous results have shown that older patients, for example, are interested in participating in research [49]. Moreover, HL was measured using a single item screening tool evaluating only functional HL [24], and we cannot exclude the possibility of a relationship whereby those invited to participate received complex consent documents and were therefore more likely to declare difficulties understanding hospital materials. However, such a relationship would only have led to an underestimation of the association between the invitation to participate in clinical trials and adequate HL. Finally, trial invitation was self-reported and might have been prone to recall bias.

5. Conclusions

Stronger efforts must be made to ensure that the invitation to participate is not exclusively targeted at those with a better socioeconomic position and greater HL, given that disadvantaged populations, often with limited HL, are more affected by cancer. Addressing HL is necessary to create a more inclusive health system and to reduce inequalities in access to innovative cancer care.

Author Contributions

Conceptualization, A.-D.B. and J.M.; methodology, Y.M.O., A.-D.B., and J.M.; software, Y.M.O.; validation, A.-D.B. and J.M.; formal analysis, Y.M.O.; investigation, A.-D.B.; resources, A.-D.B. and J.M.; data curation, A.-D.B.; writing—original draft preparation, Y.M.O.; writing—review and editing, Y.M.O., A.-D.B., and J.M.; visualization, Y.M.O.; supervision, J.M.; project administration, A.-D.B.; funding acquisition, A.-D.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the French National Institute of Cancer (Institut National du Cancer, INCa), grant number “Contrat de recherche et développement no 05-2011”.

Institutional Review Board Statement

The study methodology was approved by three national ethics commissions: CCTIRS (no 11-143), ISP (no C11-63) and CNIL (no 911290). Confidentiality is assured for all participants with regard to any personal responses and information provided, as all data collected are anonymized. Informed consent was obtained from all individual participants included in the study.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors want to thank all members of the VICAN group.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

English translation of the questions in the VICAN surveys regarding clinical trial invitation and participation.
A Clinical Trial is a scientific study evaluating a new drug not yet available or a new treatment approach. It is conducted in a hospital with volunteers who provide written signed consent to participate.
Have you ever been invited to participate in a Clinical Trial?
□ Yes    □ No    □ I don’t remember
If yes: Did you agree to participate?
□ Yes    □ No   □ I don’t remember

References

  1. Djulbegovic, B.; Kumar, A.; Glasziou, P.P.; Perera, R.; Reljic, T.; Dent, L.; Raftery, J.; Johansen, M.; Di Tanna, G.L.; Miladinovic, B.; et al. New Treatments Compared to Established Treatments in Randomized Trials. Cochrane Database Syst. Rev. 2012, 10, MR000024. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Pellegrini, I.; Chabannon, C.; Mancini, J.; Viret, F.; Vey, N.; Julian-Reynier, C. Contributing to Research via Biobanks: What It Means to Cancer Patients. Health Expect. Int. J. Public Particip. Health Care Health Policy 2014, 17, 523–533. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Julian-Reynier, C.; Genève, J.; Dalenc, F.; Genre, D.; Monnier, A.; Kerbrat, P.; Largillier, R.; Serin, D.; Rios, M.; Roché, H.; et al. Assessment of Care by Breast Cancer Patients Participating or Not Participating in a Randomized Controlled Trial: A Report with the Patients’ Committee for Clinical Trials of the Ligue Nationale Contre Le Cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2007, 25, 3038–3044. [Google Scholar] [CrossRef] [PubMed]
  4. Unger, J.M.; Cook, E.; Tai, E.; Bleyer, A. The Role of Clinical Trial Participation in Cancer Research: Barriers, Evidence, and Strategies. Am. Soc. Clin. Oncol. Educ. Book ASCO Am. Soc. Clin. Oncol. Meet. 2016, 35, 185–198. [Google Scholar] [CrossRef]
  5. Michaels, M.; Blakeney, N.; Langford, A.T.; Ford, M.E. Five Principles for Effective Cancer Clinical Trial Education within the Community Setting. J. Cancer Educ. Off. J. Am. Assoc. Cancer Educ. 2015, 30, 197–203. [Google Scholar] [CrossRef]
  6. Gross, C.P.; Filardo, G.; Mayne, S.T.; Krumholz, H.M. The Impact of Socioeconomic Status and Race on Trial Participation for Older Women with Breast Cancer. Cancer 2005, 103, 483–491. [Google Scholar] [CrossRef]
  7. Murthy, V.H.; Krumholz, H.M.; Gross, C.P. Participation in Cancer Clinical Trials: Race-, Sex-, and Age-Based Disparities. JAMA 2004, 291, 2720–2726. [Google Scholar] [CrossRef]
  8. Behrendt, C.E.; Hurria, A.; Tumyan, L.; Niland, J.C.; Mortimer, J.E. Socioeconomic and Clinical Factors Are Key to Uncovering Disparity in Accrual onto Therapeutic Trials for Breast Cancer. J. Natl. Compr. Cancer Netw. JNCCN 2014, 12, 1579–1585. [Google Scholar] [CrossRef] [Green Version]
  9. Ford, J.G.; Howerton, M.W.; Lai, G.Y.; Gary, T.L.; Bolen, S.; Gibbons, M.C.; Tilburt, J.; Baffi, C.; Tanpitukpongse, T.P.; Wilson, R.F.; et al. Barriers to Recruiting Underrepresented Populations to Cancer Clinical Trials: A Systematic Review. Cancer 2008, 112, 228–242. [Google Scholar] [CrossRef]
  10. Simon, M.S.; Du, W.; Flaherty, L.; Philip, P.A.; Lorusso, P.; Miree, C.; Smith, D.; Brown, D.R. Factors Associated with Breast Cancer Clinical Trials Participation and Enrollment at a Large Academic Medical Center. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2004, 22, 2046–2052. [Google Scholar] [CrossRef]
  11. Mc Grath-Lone, L.; Day, S.; Schoenborn, C.; Ward, H. Exploring Research Participation among Cancer Patients: Analysis of a National Survey and an in-Depth Interview Study. BMC Cancer 2015, 15, 618. [Google Scholar] [CrossRef] [Green Version]
  12. Mosconi, P.; Roberto, A.; Cerana, N.; Colombo, N.; Didier, F.; D’Incalci, M.; Lorusso, D.; Peccatori, F.A.; Network of Clinicians and Participants (1). Knowledge and Attitudes towards Clinical Trials among Women with Ovarian Cancer: Results of the ACTO Study. J. Ovarian Res. 2022, 15, 45. [Google Scholar] [CrossRef]
  13. Kearns, C.; Feighery, R.; Mc Caffrey, J.; Higgins, M.; Smith, M.; Murphy, V.; O’Reilly, S.; Horgan, A.M.; Walshe, J.; McDermott, R.; et al. Understanding and Attitudes toward Cancer Clinical Trials among Patients with a Cancer Diagnosis: National Study through Cancer Trials Ireland. Cancers 2020, 12, 1921. [Google Scholar] [CrossRef]
  14. Rudnas, B.; Montanari, E.; Dall’Agata, M.; Petracci, E.; Nanni, O. Patients’ Understanding of Clinical Research: An Italian Cancer Patient Survey. Tumori J. 2019, 105, 31–37. [Google Scholar] [CrossRef]
  15. Sørensen, K.; Van den Broucke, S.; Fullam, J.; Doyle, G.; Pelikan, J.; Slonska, Z.; Brand, H. Health Literacy and Public Health: A Systematic Review and Integration of Definitions and Models. BMC Public Health 2012, 12, 80. [Google Scholar] [CrossRef] [Green Version]
  16. Muscat, D.M.; Smith, S.; Dhillon, H.M.; Morony, S.; Davis, E.L.; Luxford, K.; Shepherd, H.L.; Hayen, A.; Comings, J.; Nutbeam, D.; et al. Incorporating Health Literacy in Education for Socially Disadvantaged Adults: An Australian Feasibility Study. Int. J. Equity Health 2016, 15, 84. [Google Scholar] [CrossRef] [Green Version]
  17. Kaplan, C.P.; Nápoles, A.M.; Narine, S.; Gregorich, S.; Livaudais-Toman, J.; Nguyen, T.; Leykin, Y.; Roach, M.; Small, E.J. Knowledge and Attitudes Regarding Clinical Trials and Willingness to Participate among Prostate Cancer Patients. Contemp. Clin. Trials 2015, 45, 443–448. [Google Scholar] [CrossRef]
  18. Halverson, J.; Martinez-Donate, A.; Trentham-Dietz, A.; Walsh, M.C.; Strickland, J.S.; Palta, M.; Smith, P.D.; Cleary, J. Health Literacy and Urbanicity among Cancer Patients. J. Rural Health Off. J. Am. Rural Health Assoc. Natl. Rural Health Care Assoc. 2013, 29, 392–402. [Google Scholar] [CrossRef] [Green Version]
  19. Sudore, R.L.; Mehta, K.M.; Simonsick, E.M.; Harris, T.B.; Newman, A.B.; Satterfield, S.; Rosano, C.; Rooks, R.N.; Rubin, S.M.; Ayonayon, H.N.; et al. Limited Literacy in Older People and Disparities in Health and Healthcare Access. J. Am. Geriatr. Soc. 2006, 54, 770–776. [Google Scholar] [CrossRef]
  20. Huang, L.C.; Ma, Y.; Ngo, J.V.; Rhoads, K.F. What Factors Influence Minority Use of National Cancer Institute-Designated Cancer Centers? Cancer 2014, 120, 399–407. [Google Scholar] [CrossRef] [Green Version]
  21. Bennett, C.L.; Ferreira, M.R.; Davis, T.C.; Kaplan, J.; Weinberger, M.; Kuzel, T.; Seday, M.A.; Sartor, O. Relation between Literacy, Race, and Stage of Presentation among Low-Income Patients with Prostate Cancer. J. Clin. Oncol Off. J. Am. Soc. Clin. Oncol. 1998, 16, 3101–3104. [Google Scholar] [CrossRef] [PubMed]
  22. Bouhnik, A.-D.; Bendiane, M.-K.; Cortaredona, S.; Sagaon Teyssier, L.; Rey, D.; Berenger, C.; Seror, V.; Peretti-Watel, P.; members of VICAN Group. The Labour Market, Psychosocial Outcomes and Health Conditions in Cancer Survivors: Protocol for a Nationwide Longitudinal Survey 2 and 5 Years after Cancer Diagnosis (the VICAN Survey). BMJ Open 2015, 5, e005971. [Google Scholar] [CrossRef] [PubMed]
  23. Mancini, J.; Pellegrini, I.; Viret, F.; Vey, N.; Daufresne, L.-M.; Chabannon, C.; Julian-Reynier, C. Consent for Biobanking: Assessing the Understanding and Views of Cancer Patients. J. Natl. Cancer Inst. 2011, 103, 154–157. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Ousseine, Y.M.; Durand, M.-A.; Bouhnik, A.-D.; Smith, A.B.; Mancini, J. Multiple Health Literacy Dimensions Are Associated with Physicians’ Efforts to Achieve Shared Decision-Making. Patient Educ. Couns. 2019, 102, 1949–1956. [Google Scholar] [CrossRef]
  25. Brice, J.H.; Foster, M.B.; Principe, S.; Moss, C.; Shofer, F.S.; Falk, R.J.; Ferris, M.E.; DeWalt, D.A. Single-Item or Two-Item Literacy Screener to Predict the S-TOFHLA among Adult Hemodialysis Patients. Patient Educ. Couns. 2014, 94, 71–75. [Google Scholar] [CrossRef]
  26. Powers, B.J.; Trinh, J.V.; Bosworth, H.B. Can This Patient Read and Understand Written Health Information? JAMA 2010, 304, 76–84. [Google Scholar] [CrossRef]
  27. Rey, G.; Jougla, E.; Fouillet, A.; Hémon, D. Ecological Association between a Deprivation Index and Mortality in France over the Period 1997–2001: Variations with Spatial Scale, Degree of Urbanicity, Age, Gender and Cause of Death. BMC Public Health 2009, 9, 33. [Google Scholar] [CrossRef] [Green Version]
  28. Huber, C.A.; Szucs, T.D.; Rapold, R.; Reich, O. Identifying Patients with Chronic Conditions Using Pharmacy Data in Switzerland: An Updated Mapping Approach to the Classification of Medications. BMC Public Health 2013, 13, 1030. [Google Scholar] [CrossRef] [Green Version]
  29. Baquet, C.R.; Ellison, G.L.; Mishra, S.I. Analysis of Maryland Cancer Patient Participation in National Cancer Institute-Supported Cancer Treatment Clinical Trials. J. Health Care Poor Underserved 2009, 20, 120–134. [Google Scholar] [CrossRef]
  30. Unger, J.M.; Hershman, D.L.; Fleury, M.E.; Vaidya, R. Association of Patient Comorbid Conditions with Cancer Clinical Trial Participation. JAMA Oncol. 2019, 5, 326–333. [Google Scholar] [CrossRef]
  31. Ousseine, Y.M.; Bouhnik, A.; Peretti-Watel, P.; Sarradon-Eck, A.; Memoli, V.; Bendiane, M.; Durand, M.; Mancini, J. The Impact of Health Literacy on Medico-social Follow-up Visits among French Cancer Survivors 5 Years after Diagnosis: The National VICAN Survey. Cancer Med. 2020, 9, 4185–4196. [Google Scholar] [CrossRef]
  32. The HLS19 Consortium of the WHO Action Network M-POHL. International Report on the Methodology, Results, and Recommendations of the European Health Literacy Population Survey 2019–2021 (HLS19) of M-POHL.; Austrian National Public Health Institute: Vienna, Austria, 2021; Available online: https://m-pohl.net/sites/m-pohl.net/files/inline-files/HLS19_International%20Report%20%28002%29_0.pdf (accessed on 3 March 2021).
  33. Jeppesen, K.M.; Coyle, J.D.; Miser, W.F. Screening Questions to Predict Limited Health Literacy: A Cross-Sectional Study of Patients with Diabetes Mellitus. Ann. Fam. Med. 2009, 7, 24–31. [Google Scholar] [CrossRef]
  34. Institut National Du Cancer. Bilan National Des Activités En Recherche Clinique 2003–2010; Collection Rapports & Synthèses; INCa: Boulogne-Billancourt, France, 2012. [Google Scholar]
  35. Chino, F.; Zafar, S.Y. Financial Toxicity and Equitable Access to Clinical Trials. Am. Soc. Clin. Oncol. Educ. Book Am. Soc. Clin. Oncol. Annu. Meet. 2019, 39, 11–18. [Google Scholar] [CrossRef]
  36. Colon-Otero, G.; Smallridge, R.C.; Solberg, L.A.; Keith, T.D.; Woodward, T.A.; Willis, F.B.; Dunn, A.N. Disparities in Participation in Cancer Clinical Trials in the United States. Cancer 2008, 112, 447–454. [Google Scholar] [CrossRef]
  37. Frérot, M.; Jooste, V.; Binquet, C.; Fournel, I.; Bedenne, L.; Bouvier, A.-M. Factors Influencing Inclusion in Digestive Cancer Clinical Trials: A Population-Based Study. Dig. Liver Dis. Off. J. Ital. Soc. Gastroenterol. Ital. Assoc. Study Liver 2015, 47, 891–896. [Google Scholar] [CrossRef]
  38. Kanarek, N.F.; Tsai, H.-L.; Metzger-Gaud, S.; Damron, D.; Guseynova, A.; Klamerus, J.F.; Rudin, C.M. Geographic Proximity and Racial Disparities in Cancer Clinical Trial Participation. J. Natl. Compr. Cancer Netw. 2010, 8, 1343–1351. [Google Scholar] [CrossRef]
  39. Vanderpool, R.C.; Kornfeld, J.; Mills, L.; Byrne, M.M. Rural-Urban Differences in Discussions of Cancer Treatment Clinical Trials. Patient Educ. Couns. 2011, 85, e69–e74. [Google Scholar] [CrossRef] [Green Version]
  40. Sharrocks, K.; Spicer, J.; Camidge, D.R.; Papa, S. The Impact of Socioeconomic Status on Access to Cancer Clinical Trials. Br. J. Cancer 2014, 111, 1684–1687. [Google Scholar] [CrossRef] [Green Version]
  41. Byrne, M.M.; Tannenbaum, S.L.; Glück, S.; Hurley, J.; Antoni, M. Participation in Cancer Clinical Trials: Why are Patients not Participating? Med. Decis. Mak. Int. J. Soc. Med. Decis. Mak. 2014, 34, 116–126. [Google Scholar] [CrossRef]
  42. Meropol, N.J.; Wong, Y.-N.; Albrecht, T.; Manne, S.; Miller, S.M.; Flamm, A.L.; Benson, A.B.; Buzaglo, J.; Collins, M.; Egleston, B.; et al. Randomized Trial of a Web-Based Intervention to Address Barriers to Clinical Trials. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2016, 34, 469–478. [Google Scholar] [CrossRef]
  43. Mancini, J.; Butow, P.N.; Julian-Reynier, C.; Dring, R.; Festy, P.; Fenaux, P.; Vey, N. Question Prompt List Responds to Information Needs of Myelodysplastic Syndromes Patients and Caregivers. Leuk. Res. 2015, 39, 599–605. [Google Scholar] [CrossRef] [PubMed]
  44. Kim, E.J.; Kim, S.H. Simplification Improves Understanding of Informed Consent Information in Clinical Trials Regardless of Health Literacy Level. Clin. Trials Lond. Engl. 2015, 12, 232–236. [Google Scholar] [CrossRef] [PubMed]
  45. Mancini, J.; Briggs, A.; Elkin, E.B.; Regan, J.; Hickey, C.; Targett, C.; Ager, R.; Masuda, S.; Bach, P.B.; Sabbatini, P.J. The Impact of Patient Education on Consideration of Enrollment in Clinical Trials. J. Community Support. Oncol. 2018, 16, e81–e88. [Google Scholar] [CrossRef]
  46. Torres, S.; de la Riva, E.E.; Tom, L.S.; Clayman, M.L.; Taylor, C.; Dong, X.; Simon, M.A. The Development of a Communication Tool to Facilitate the Cancer Trial Recruitment Process and Increase Research Literacy among Underrepresented Populations. J. Cancer Educ. Off. J. Am. Assoc. Cancer Educ. 2015, 30, 792–798. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Percac-Lima, S.; Ashburner, J.M.; Zai, A.H.; Chang, Y.; Oo, S.A.; Guimaraes, E.; Atlas, S.J. Patient Navigation for Comprehensive Cancer Screening in High-Risk Patients Using a Population-Based Health Information Technology System: A Randomized Clinical Trial. JAMA Intern. Med. 2016, 176, 930–937. [Google Scholar] [CrossRef] [PubMed]
  48. Hamel, L.M.; Penner, L.A.; Albrecht, T.L.; Heath, E.; Gwede, C.K.; Eggly, S. Barriers to Clinical Trial Enrollment in Racial and Ethnic Minority Patients with Cancer. Cancer Control 2016, 23, 327–337. [Google Scholar] [CrossRef] [Green Version]
  49. Mancini, J.; Jansen, J.; Julian-Reynier, C.; Bechlian, D.; Vey, N.; Chabannon, C. Preferences of Older Adults with Cancer for Involvement in Decision-Making about Research Participation. J. Am. Geriatr. Soc. 2014, 62, 1191–1193. [Google Scholar] [CrossRef]
Figure 1. Flowchart of participants.
Figure 1. Flowchart of participants.
Curroncol 29 00253 g001
Figure 2. Clinical trial invitation rate and participation according to health literacy (HL) level.
Figure 2. Clinical trial invitation rate and participation according to health literacy (HL) level.
Curroncol 29 00253 g002
Table 1. Main patient characteristics as a function of invitation to participate in a clinical trial (N = 1954).
Table 1. Main patient characteristics as a function of invitation to participate in a clinical trial (N = 1954).
Overall
Population
Invited to Participate in a Clinical Trial
%No (89.7%)%Yes (10.3%)%p Value
Age at diagnosis (years)≤65 77.276.187.5<0.001
>65 22.823.912.5
Cancer management centerPrivate center50.852.536.0<0.001
Comprehensive cancer center10.58.727.0
Public academic or community center31.731.632.5
Missing/unknown7.07.34.5
GenderMan35.937.423.0<0.001
Woman65.162.677.0
Education levelNo diploma6.66.75.50.214
<upper secondary school certificate43.043.538.2
≥upper secondary school certificate50.449.856.3
Health literacyLimited37.638.925.90.001
Adequate62.461.174.1<
Area of residenceRural/Small town/city (<200,000 inhabitants65.967.056.50.005
Large city (≥200,000 inhabitants)32.931.843.0
Missing/unknown1.21.20.5
Deprivation indexLow (<Q1)24.724.228.50.299
Intermediate (Q1–Q3)50.350.350.5
High (>Q3)24.524.921.0
Missing/unknown0.50.6
Financial resourcesLow (<Q1)22.323.215.00.028
Intermediate (Q1–Q3)46.546.447.0
High (>Q3)24.623.931.0
Missing/unknown6.66.57.0
Cancer typeBreast43.441.956.2<0.001
Lung3.63.27.5
Prostate16.717.87.0
Upper aero-digestive tract 3.53.44.0
Bladder2.93.3
Kidney3.73.92.0
Thyroid5.65.93.0
Non-Hodgkin lymphoma3.33.15.0
Melanoma4.84.75.5
Cervical2.32.23.5
Endometrial1.01.00.5
Colorectal9.19.65.0
Metastases at diagnosisNo98.398.497.50.266
Yes1.71.62.5
Individual chronic condition scoreMean (SD)0.73 (0.38)0.73 (0.38)0.76 (0.36)0.204
Q1: first quartile; Q3: third quartile.
Table 2. Variables associated with the invitation to participate in a clinical trial (binary logistic regression, N = 1954).
Table 2. Variables associated with the invitation to participate in a clinical trial (binary logistic regression, N = 1954).
Trial Invitation
Adjusted Odds
Ratio
95% Confidence Intervalp Value
LowerUpper
Health literacy levelLimited0.550.390.770.001
Adequate1
Age (years)≤651
>650.600.370.970.039
Management CenterPrivate1
Public academic or community center1.430.992.060.055
Comprehensive cancer center3.622.375.54<0.001
Missing/unknown0.820.391.690.594
Area of residenceRural/Small town/city (<200,000 residents)0.670.490.920.014
Large city (≥200,000 residents)1
Missing/unknown0.510.083.390.490
Financial resourcesLow (<Q1)0.540.330.880.014
Intermediate (Q1–Q3)0.820.571.180.301
High (>Q3)1
Missing/unknown1.030.532.020.918
Cancer typeBreast1.820.903.660.095
Lung3.781.559.220.003
Prostate0.840.361.960.689
Upper aero-digestive tract 2.160.825.640.117
Bladder0.090.004.560.232
Kidney0.940.283.180.921
Thyroid0.780.262.320.655
Non-Hodgkin lymphoma2.881.127.450.029
Melanoma1.860.734.750.195
Cervical2.600.907.470.076
Endometrial0.560.047.240.658
Colorectal1
Individual chronic condition score, per one-point increase 1.310.862.000.212
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ousseine, Y.M.; Bouhnik, A.-D.; Mancini, J. Health Literacy and Clinical Trial Participation in French Cancer Patients: A National Survey. Curr. Oncol. 2022, 29, 3118-3129. https://doi.org/10.3390/curroncol29050253

AMA Style

Ousseine YM, Bouhnik A-D, Mancini J. Health Literacy and Clinical Trial Participation in French Cancer Patients: A National Survey. Current Oncology. 2022; 29(5):3118-3129. https://doi.org/10.3390/curroncol29050253

Chicago/Turabian Style

Ousseine, Youssoufa M., Anne-Déborah Bouhnik, and Julien Mancini. 2022. "Health Literacy and Clinical Trial Participation in French Cancer Patients: A National Survey" Current Oncology 29, no. 5: 3118-3129. https://doi.org/10.3390/curroncol29050253

Article Metrics

Back to TopTop