Trismo e radioterapia de cabeça e pescoço: revisão sistemática com meta-análise de fatores de risco e ensaio clínico triplo-cego com fotobiomodulação preventiva
Notice bibliographique
Résumé
Patients undergoing radiotherapy (RT) with or without associated chemotherapy (CT) in the head and neck region commonly develop trismus during and after treatment, leading to a significant decrease in masticatory efficacy and quality of life. Evidence has suggested that Photobiomodulation (PBMT) with low-level laser (LLLT) may act in the prevention of RT-induced trismus. The aim of the study is to evaluate the role of RT associated or not with CT in the prevalence of trismus in patients with head and neck cancer (HNC), through a systematic review, and to conduct a clinical trial to verify the efficacy of PBMT in the prevention of trismus in these patients. First, a systematic review of the literature guided by PRISMA and registered in PROSPERO (CRD42021255377) was carried out with the following starting question: (P) in patients with head and neck cancer (E) treated with chemoradiotherapy (C) compared to patients treated only with radiotherapy (O) is there a higher prevalence of trismus or chewing difficulty? For this, 963 articles were screened in the PubMed, Lilacs, Livivo, Scopus, Embase, Web of Science, EBSCO and gray literature databases (Open Grey, Google Scholar and ProQuest). Eight articles were included for qualitative and quantitative synthesis of prevalence by inverse variance method and random effects, heterogeneity analysis [I2 and Tau2], one-of-out analysis and Eggs and Begg tests, risk of bias analysis (Newcastle Ottawa Scale) and quality of evidence (GRADE). The eight selected articles included 2332 patients and presented low risk of bias. Radiochemotherapy significantly increased (p=0.0003) the prevalence of trismus by 2.55 (95% CI = 1.53-4.23) times compared to RT, with significant heterogeneity (I2 = 59%, p=0.010), but low (Tau2=0.29). Trismus was directly related to worse quality of life, the one-of-out analysis showed no significant difference between the studies and GRADE demonstrated an important level of evidence. The second phase of the study: a phase II clinical trial, randomized, triple-blind, placebo-controlled, guided by the CONSORT (Consolidated Standards of Reporting Trials) guidelines and registered in REBEC (Brazilian Registry of Clinical Trials). Forty-six patients undergoing RT for HNC were included. Patients were equally and randomly allocated into PBMT and PBMT placebo groups and evaluated daily by measuring mouth opening, pain on mouth opening and pain on palpation of the masticatory muscles using the Visual Analogue Scale (VAS). An extraoral infrared laser (~808nm) with a power of 0.1W, energy of 3J, 30s (107J/cm2) per point was used, applied extraorally to the anterior temporal (MT), masseter (MM) and temporomandibular joints (TMJ) muscles and intraorally to the medial pterygoid (MP) muscle. The food quality inventory (ASGP) and quality of life (QoL) analysis (OHIP-14) were applied. Student's t-test, Mann-Whitney test and linear regression models were used (p<0.05). Patients in the PBMT group presented a smaller reduction in mouth opening (-0.15±4.51 mm vs -3.75±3.69 mm, p=0.005), as well as less pain on palpation of the masticatory muscles throughout radiotherapy (right MM: 9.5% (p=0.584) vs 46.2% (p=0.005); left MM: -13.5% (p=0.439) vs 49.3% (p=0.003); right T: -48.1% (p=0.003) vs 18.9% (p=0.274); left T: -15.7% (p=0.365) vs 52.1% (p=0.001); right MP: -62.5% (p<0.001) vs -14.6% (p=0.402); left MP: 18.6% (p=0.282) vs 51.3% (p=0.002); right TMJ: - 9.4% (p=0.589) vs 76.6% (p<0.001); left TMJ: 9.8% (p=0.574) vs 19.2% (p=0.267)), in addition to a lower prevalence of trismus (grade 1, p=0.002) compared to the placebo group. The DMFT, OHIP-14 and ASGP scores did not differ between groups (p>0.05). No difference was observed in mouth opening (M1-M6) after treatment. PBMT was effective in preventing trismus and pain in the masticatory muscles during radiotherapy treatment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,027 |
| Bibliométrie | 0,008 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».