NTCP modeling and dose–volume correlations for acute xerostomia and dry eye after whole brain radiation

Abstract

Background Whole brain radiation (WBRT) may lead to acute xerostomia and dry eye from incidental parotid and lacrimal exposure, respectively. We performed a prospective observational study to assess the incidence/severity of this toxicity. We herein perform a secondary analysis relating parotid and lacrimal dosimetric parameters to normal tissue complication probability (NTCP) rates and associated models. Methods Patients received WBRT to 25–40 Gy in 10–20 fractions using 3D-conformal radiation therapy without prospective delineation of the parotids or lacrimals. Patients completed questionnaires at baseline and 1 month post-WBRT. Xerostomia was assessed using the University of Michigan xerostomia score (scored 0–100, toxicity defined as ≥ 20 pt increase) and xerostomia bother score (scored from 0 to 3, toxicity defined as ≥ 2 pt increase). Dry eye was assessed using the Subjective Evaluation of Symptom of Dryness (SESoD, scored from 0 to 4, toxicity defined as ≥ 2 pt increase). The clinical data were fitted by the Lyman–Kutcher–Burman (LKB) and Relative Seriality (RS) NTCP models. Results Of 55 evaluable patients, 19 (35%) had ≥ 20 point increase in xerostomia score, 11 (20%) had ≥ 2 point increase in xerostomia bother score, and 13 (24%) had ≥ 2 point increase in SESoD score. For xerostomia, parotid V10Gy–V20Gy correlated best with toxicity, with AUC 0.68 for xerostomia score and 0.69–0.71 for bother score. The values for the D50, m and n parameters of the LKB model were 22.3 Gy, 0.84 and 1.0 for xerostomia score and 28.4 Gy, 0.55 and 1.0 for bother score, respectively. The corresponding values for the D50, γ and s parameters of the RS model were 23.5 Gy, 0.28 and 0.0001 for xerostomia score and 32.0 Gy, 0.45 and 0.0001 for bother score, respectively. For dry eye, lacrimal V10Gy–V15Gy were found to correlate best with toxicity, with AUC values from 0.67 to 0.68. The parameter values of the LKB model were 53.5 Gy, 0.74 and 1.0, whereas of the RS model were 54.0 Gy, 0.37 and 0.0001, respectively. Conclusions Xerostomia was most associated with parotid V10Gy–V20Gy, and dry eye with lacrimal V10Gy–V15Gy. NTCP models were successfully created for both toxicities and may help clinicians refine dosimetric goals and assess levels of risk in patients receiving palliative WBRT.

Estimating the Dose-Response Relationship for Ocular Pain after Radiotherapy of Head and Neck Cancers and Skull Base Tumors based on the LKB Radiobiological Model

“…The TD 50 of ocular pain was also equal to 27.54 Gy, which is less than the TD 50 reported for complications, such as dry eyes and optic neuropathy (28.4 Gy and 70.12 Gy, respectively) [ 30 , 31 ], showing greater radiation sensitivity of the eye in case of pain.…”

NTCP Modeling and Dose-Volume Correlations of Significant Hematocrit Drop 3 Months After Prostate Radiation Therapy

“…The values of the parameters of the relative seriality model and their 95% CIs were determined using the maximum likelihood method. 14 , 15 , 16 The CIs of the model parameters were determined using the profile likelihood method. The ability of the normal tissue complication probability (NTCP) models to distinguish patients with and without the examined symptoms was evaluated using the area under the curve (AUC) measure, which is used as a summary of the receiver operating characteristic curve.…”

“…The ability of the normal tissue complication probability (NTCP) models to distinguish patients with and without the examined symptoms was evaluated using the area under the curve (AUC) measure, which is used as a summary of the receiver operating characteristic curve. 16 , 17 Additionally, the odds ratio (OR) method was applied to identify NTCP thresholds beyond which the risk of toxicity increases significantly. 15 , 16 Those thresholds were identified in 3 steps.…”

“… 16 , 17 Additionally, the odds ratio (OR) method was applied to identify NTCP thresholds beyond which the risk of toxicity increases significantly. 15 , 16 Those thresholds were identified in 3 steps. First, we identified the thresholds for which the OR values were larger than 1 and sorted them by OR value (largest to smallest); second, we identified the thresholds for which the low limit of the 95% CI was larger than 1; and third, we identified the threshold with the smallest 95% CI.…”