Les traitements traditionnels et les compléments alimentaires chez le patient atteint de cancer: État des lieux en Tunisie
Bibliographic record
Abstract
Contexte : Les médecines alternatives et complémentaires connaissent à nos jours un véritable essor dans le monde entier, surtout chez le patient atteint d’un cancer qui cherche à améliorer son bien-être physique et moral. Objectifs : Réaliser un état des lieux des traitements traditionnels et des compléments alimentaires chez le patient atteint de cancer et évaluer l’incidence de ces approches sur la prise en charge anticancéreuse. Méthodologie : Il s’agit d’une étude prospective transversale à visée descriptive réalisée à l’hôpital de jour d’oncologie d’un centre hospitalier Tunisien. La collecte des données s’est déroulée du 1er février au 30 mars 2022. Résultats : Chez la population à l’étude, la prévalence d’utilisation des médecines complémentaires était de 71 %, avec une prédominance féminine et une moyenne d’âge de 54 ans. La phytothérapie occupait la première place (69,7 %); avec des pourcentages qui variaient entre 20 % et 40 %, on trouvait les produits d’origine animale, le régime alimentaire, la massothérapie et les compléments alimentaires; dans une moindre mesure on a noté la médecine des ventouses (12,4 %) et les thérapies du corps-esprit (rokia charria, activité sportive, etc.), à 10 %. Les plantes les plus consommées qui ont été recensées sont la Nigella sativa L. (44,9 %) suivie de l’Ephedra foeminea Forssk. (42,7 %) et du Curcuma longa L. (32,6 %). Parmi les interactions herbe-médicament recensées, 33,4 % ont été classées contre-indiquées par rapport à 56,7 % qui ont été classées comme bénéfiques. Conclusions : L’enquête a révélé une prévalence importante de l’utilisation de la médecine douce, ce qui nécessite une grande vigilance et des études plus approfondies. Mots-clés : médecine complémentaire et alternative, phytothérapie, oncologie intégrative, cancer, interaction ABSTRACT Context: Alternative and complementary medicines are currently experiencing a real boom worldwide, especially among cancer patients who are looking to improve their physical and mental well-being. Objectives: To provide an overview of the use of traditional treatments and dietary supplements by cancer patients and to assess the impact of these approaches on cancer care. Methods: This prospective cross-sectional descriptive study was conducted at the oncology day hospital of a Tunisian medical centre. Data were collected from February 1 to March 30, 2022. Results: In the study population, the prevalence of complementary medicine use was 71%; users were predominantly female, and average age was 54 years. Herbal medicine was most commonly used (69.7%); animal-derived products, diet, massage therapy, and dietary supplements were also common, with percentages ranging between 20% and 40%. Cupping therapy (12.4%) and mind-body therapies (such as rokia charia and physical activity; 10%) were noted to a lesser extent. Of the plants identified, the most frequently consumed was Nigella sativa L. (44.9%), followed by Ephedra foeminea Forssk. (42.7%) and Curcuma longa L. (32.6%). Among the identified herb-drug interactions, 33.4% were classified as contraindicated, while 56.7% were classified as beneficial. Conclusions: The survey revealed a significant prevalence of alternative medicine use, which requires careful attention and further research. Keywords: complementary and alternative medicine, herbal medicine, integrative oncology, cancer, interaction
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".