Modeling of Xerostomia After Radiotherapy for Head and Neck Cancer: A Registry Study

A real-life experience of long-term use of pilocarpine in irradiated head and neck cancer patients

AIMS

To assess long-term efficacy and side effects of pilocarpine on irradiated head and neck cancer (HNC) patients in both for prevention and treatment of radiation-induced xerostomia (RIX).

METHODS

Retrospective observational study was conducted. Eligibility criteria included irradiated HNC patients who received pilocarpine at least 12 weeks either for prevention (group A) or for treatment (group B) of RIX. We collected the documented Late Effect Normal Tissue Task Force-Subjective, Objective, Management, Analytics subjective/objective grades of RIX before (only group B) and the latest visit for pilocarpine prescription, dosage, side effects, duration of treatment, and the cause of discontinuation.

RESULTS

Between December 2007 and June 2022, 182 patients were enrolled including 95 patients (52%) in group A and 87 patients (48%) in group B. Group A patients reported grades 1, 2, 3, and 4 objective RIX in 0%, 7%, 93%, and 0%. Grade 1, 2, and 3 subjective RIX were 57%, 28%, and 15%. All patients in group B had grade 3 both objective/subjective RIX. The overall improvement of objective/subjective RIX was found in 40%/83%. Discontinuation was found in 51% of patients due to tolerable symptoms or deterioration of the patient's status.

CONCLUSIONS

Based on this retrospective analysis, long-term use of pilocarpine in irradiated HNC appears feasible for both prevention and treatment of RIX.

Radiomics and dosiomics-based prediction of radiotherapy-induced xerostomia in head and neck cancer patients

BACKGROUND AND AIM

Dose-response modeling for radiotherapy-induced xerostomia in head and neck cancer (HN) patients is a promising frontier for personalized therapy. Feature extraction from diagnostic and therapeutic images (radiomics and dosiomics features) can be used for data-driven response modeling. The aim of this study is to develop xerostomia predictive models based on radiomics-dosiomics features.

METHODS

Data from the cancer imaging archive (TCIA) for 31 HN cancer patients were employed. For all patients, parotid CT radiomics features were extracted, utilizing Lasso regression for feature selection and multivariate modeling. The models were developed by selected features from pretreatment (CT1), mid-treatment (CT2), post-treatment (CT3), and delta features (ΔCT2-1, ΔCT3-1, ΔCT3-2). We also considered dosiomics features extracted from the parotid dose distribution images (Dose model). Thus, combination models of radio-dosiomics (CT + dose & ΔCT + dose) were developed. Moreover, clinical, and dose-volume histogram (DVH) models were built. Nested 10-fold cross-validation was used to assess the predictive classification of patients into those with and without xerostomia, and the area under the receiver operative characteristic curve (AUC) was used to compare the predictive power of the models. The sensitivity and accuracy of models also were obtained.

RESULTS

In total, 59 parotids were assessed, and 13 models were developed. Our results showed three models with AUC of 0.89 as most predictive, namely ΔCT2-1 + Dose (Sensitivity 0.99, Accuracy 0.94 & Specificity 0.86), CT3 model (Sensitivity 0.96, Accuracy 0.94 & Specificity 0.86) and DVH (Sensitivity 0.93, Accuracy 0.89 & Specificity 0.84). These models were followed by Clinical (AUC 0.89, Sensitivity 0.81, Accuracy 0.97 & Specificity 0.89) and CT2 & Dose (AUC 0.86, Sensitivity 0.97, Accuracy 0.87 & Specificity 0.82). The Dose model (developed by dosiomics features only) had AUC, Sensitivity, Specificity, and Accuracy of 0.72, 0.98, 0.33, and 0.79 respectively.

CONCLUSION

Quantitative features extracted from diagnostic imaging during and after radiotherapy alone or in combination with dosiomics markers obtained from dose distribution images can be used for radiotherapy response modeling, opening up prospects for personalization of therapies toward improved therapeutic outcomes.

World Workshop on Oral Medicine VIII: Development of a Core Outcome Set for Dry Mouth: A Systematic Review of Outcome Domains for Xerostomia

OBJECTIVE

The purpose of this study was to identify all outcome domains used in clinical studies of xerostomia, that is, subjective sensation of dry mouth. This study is part of the extended project "World Workshop on Oral Medicine Outcomes Initiative for the Direction of Research" to develop a core outcome set for dry mouth.

STUDY DESIGN

A systematic review was performed on MEDLINE, EMBASE, CINAHL, and Cochrane Central Register of Controlled Trials databases. All clinical and observational studies that assessed xerostomia in human participants from 2001 to 2021 were included. Information on outcome domains was extracted and mapped to the Core Outcome Measures in Effectiveness Trials taxonomy. Corresponding outcome measures were summarized.

RESULTS

From a total of 34,922 records retrieved, 688 articles involving 122,151 persons with xerostomia were included. There were 16 unique outcome domains and 166 outcome measures extracted. None of these domains or measures were consistently used across all the studies. The severity of xerostomia and physical functioning were the 2 most frequently assessed domains.

CONCLUSION

There is considerable heterogeneity in outcome domains and measures reported in clinical studies of xerostomia. This highlights the need for harmonization of dry mouth assessment to enhance comparability across studies and facilitate the synthesis of robust evidence for managing patients with xerostomia.

The Role of Patient- and Treatment-Related Factors and Early Functional Imaging in Late Radiation-Induced Xerostomia in Oropharyngeal Cancer Patients

Simple Summary

In the present prospective study, we assessed the role of various Magnetic Resonance Imaging biomarkers combined with self-assessed xerostomia questionnaires and patient- and treatment-related factors, in predicting xerostomia at 12 months after chemoradiotherapy for oropharyngeal squamous cell carcinoma. We hypothesized that the integration of pre-treatment imaging biomarkers, which addresses the tissue heterogeneity and individual variations among patients, could improve the accuracy of conventional prediction models that are based only on dose information, ultimately providing a better understanding of the pathophysiological mechanisms underlying radiation induced salivary dysfunction. The implementation of multifactorial models, driven by machine learning algorithms, may improve prediction accuracy of radiation-induced toxicity and tailor individual treatment options for patients.

Abstract

The advent of quantitative imaging in personalized radiotherapy (RT) has offered the opportunity for a better understanding of individual variations in intrinsic radiosensitivity. We aimed to assess the role of magnetic resonance imaging (MRI) biomarkers, patient-related factors, and treatment-related factors in predicting xerostomia 12 months after RT (XER₁₂) in patients affected by oropharyngeal squamous cell carcinoma (OSCC). Patients with locally advanced OSCC underwent diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI at baseline; DWI was repeated at the 10th fraction of RT. The Radiation Therapy Oncology Group (RTOG) toxicity scale was used to evaluate salivary gland toxicity. Xerostomia-related questionnaires (XQs) were administered weekly during and after RT. RTOG toxicity ≥ grade 2 at XER₁₂ was considered as endpoint to build prediction models. A Decision Tree classification learner was applied to build the prediction models following a five-fold cross-validation. Of the 89 patients enrolled, 63 were eligible for analysis. Thirty-six (57.1%) and 21 (33.3%) patients developed grade 1 and grade 2 XER₁₂, respectively. Including only baseline variables, the model based on DCE-MRI and V65 (%) (volume of both glands receiving doses ≥ 65 Gy) had a fair accuracy (77%, 95% CI: 66.5–85.4%). The model based on V65 (%) and XQ-Int_mid (integral of acute XQ scores from the start to the middle of RT) reached the best accuracy (81%, 95% CI: 71–88.7%). In conclusion, non-invasive biomarkers from DCE-MRI, in combination with dosimetric variables and self-assessed acute XQ scores during treatment may help predict grade 2 XER₁₂ with a fair to good accuracy.

Modified Gap Arthroplasty for Temporomandibular Joint Ankylosis Following Radiotherapy for Rhabdomyosarcoma: Report of an Unusual Case and Brief Literature Review

Radiotherapy at the temporomandibular joint (TMJ) area often results in trismus, however, post radiation ankylosis is extremely rare and has not been previously reported in literature. Radiation is known to impact the vasculature of bony structures leading to bone necrosis with certain risk factors including surgical intervention, even teeth extraction, that could lead to osteoradionecrosis. Accordingly, gap arthroplasty for such case seemed rather challenging. In this report, we introduce for the first time, a rare case of temporomandibular joint ankylosis post radiotherapy for management of rhabdomyosarcoma in a 12 years-old boy. A modified gap arthroplasty technique combined simultaneously with pterygo-masseteric muscle flap was applied to lower the risk of osteoradionecrosis due surgical trauma at irradiated area. Computed tomographic scan on the head indicated that the TMJ architecture was completely replaced by bone, with fusion of the condyle, sigmoid notch, and coronoid process to the zygomatic arch and glenoid fossa. The patient’s problem was totally solved with no osteoradionecrosis or relapse of ankylosis observed at follow up visits. Herein, the modified gap arthroplasty combined with pterygo-masseteric muscle flap could be recommended to be applied on other cases of ankylosis especially after receiving radiotherapy.

Modelling Radiation-Induced Salivary Dysfunction during IMRT and Chemotherapy for Nasopharyngeal Cancer Patients

BACKGROUND

Radiation-induced xerostomia is one of the most prevalent adverse effects of head and neck cancer treatment, and it could seriously affect patients' qualities of life. It results primarily from damage to the salivary glands, but its onset and severity may also be influenced by other patient-, tumour-, and treatment-related factors. We aimed to build and validate a predictive model for acute salivary dysfunction (aSD) for locally advanced nasopharyngeal carcinoma (NPC) patients by combining clinical and dosimetric factors.

METHODS

A cohort of consecutive NPC patients treated curatively with IMRT and chemotherapy at 70 Gy (2-2.12 Gy/fraction) were utilised. Parotid glands (cPG, considered as a single organ) and the oral cavity (OC) were selected as organs-at-risk. The aSD was assessed at baseline and weekly during RT, grade ≥ 2 aSD chosen as the endpoint. Dose-volume histograms were reduced to the Equivalent Uniform Dose (EUD). Dosimetric and clinical/treatment features selected via LASSO were inserted into a multivariable logistic model. Model validation was performed on two cohorts of patients with prospective aSD, and scored using the same schedule/scale: a cohort (NPC_V) of NPC patients (as in model training), and a cohort of mixed non-NPC head and neck cancer patients (HNC_V).

RESULTS

The model training cohort included 132 patients. Grade ≥ 2 aSD was reported in 90 patients (68.2%). Analyses resulted in a 4-variables model, including doses of up to 98% of cPG (cPG_D98%, OR = 1.04), EUD to OC with n = 0.05 (OR = 1.11), age (OR = 1.08, 5-year interval) and smoking history (OR = 1.37, yes vs. no). Calibration was good. The NPC_V cohort included 38 patients, with aSD scored in 34 patients (89.5%); the HNC_V cohort included 93 patients, 77 with aSD (92.8%). As a general observation, the incidence of aSD was significantly different in the training and validation populations (p = 0.01), thus impairing calibration-in-the-large. At the same time, the effect size for the two dosimetric factors was confirmed. Discrimination was also satisfactory in both cohorts: AUC was 0.73, and 0.68 in NPC_V and HNC_V cohorts, respectively.

CONCLUSION

cPG D98% and the high doses received by small OC volumes were found to have the most impact on grade ≥ 2 acute xerostomia, with age and smoking history acting as a dose-modifying factor. Findings on the development population were confirmed in two prospectively collected validation populations.

Lubricating properties of chewing stimulated whole saliva from patients suffering from xerostomia

OBJECTIVES

The study aimed to quantify the lubricating properties of chewing stimulated whole saliva from healthy controls (n = 22), from patients suffering from primary Sjögren's syndrome (n = 37) and from patients undergoing head-and-neck radiotherapy (n = 34).

MATERIALS AND METHODS

All participants had to complete the Xerostomia Inventory questionnaire to score dry mouth sensation. Lubrication was measured using an ex vivo tongue-enamel friction system in terms of Relief and Relief period. MUC5b and total protein concentrations of the saliva samples were measured by an enzyme-linked immunosorbent assay and a bicinchoninic acid assay, respectively.

RESULTS

Relief of Sjögren's patients' saliva and post-irradiation patients' saliva was similar compared with healthy controls, but saliva from post-irradiation patients lubricated significantly better than saliva from Sjögren's patients. The Relief period was similar between the three groups. The Relief and Relief period were higher for saliva samples post-irradiation compared to pre-irradiation. MUC5b and total protein concentrations were comparable in all groups. MUC5b and total protein output were significantly lower in patients subjected to radiotherapy compared to saliva from healthy controls and pre-irradiation patients. MUC5b concentrations positively correlated with lubricating properties of post-irradiation patient saliva.

CONCLUSIONS

The lubricating properties of patient saliva were not any worse than healthy controls. Lower flow rate leads to lower availability of saliva in the oral cavity and decreases the overall output of protein and MUC5b, which might result in an insufficient replenishing of the mucosal salivary film.

CLINICAL RELEVANCE

An insufficient replenishing might underlie the sensation of a dry mouth and loss of oral function.

A Risk Prediction Model by LASSO for Radiation-Induced Xerostomia in Patients With Nasopharyngeal Carcinoma Treated With Comprehensive Salivary Gland-Sparing Helical Tomotherapy Technique

Objective

This study aimed to develop a least absolute shrinkage and selection operator (LASSO)-based multivariable normal tissue complication probability (NTCP) model to predict radiation-induced xerostomia in patients with nasopharyngeal carcinoma (NPC) treated with comprehensive salivary gland–sparing helical tomotherapy technique.

Methods and Materials

LASSO with the extended bootstrapping technique was used to build multivariable NTCP models to predict factors of patient-reported xerostomia relieved by 50% and 80% compared with the level at the end of radiation therapy within 1 year and 2 years, R50-1year and R80-2years, in 203 patients with NPC. The model assessment was based on 10-fold cross-validation and the area under the receiver operating characteristic curve (AUC).

Results

The prediction model by LASSO with 10-fold cross-validation showed that radiation-induced xerostomia recovery could be predicted by prognostic factors of R50-1year (age, gender, T stage, UICC/AJCC stage, parotid Dmean, oral cavity Dmean, and treatment options) and R80-2years (age, gender, T stage, UICC/AJCC stage, oral cavity Dmean, N stage, and treatment options). These prediction models also demonstrated a good performance by the AUC.

Conclusion

The prediction models of R50-1year and R80-2years by LASSO with 10-fold cross-validation were recommended to validate the NTCP model before comprehensive salivary gland–sparing radiation therapy in patients with NPC.