Prognostic Factors Improving ATA Risk System and Dynamic Risk Stratification in Low- and Intermediate-Risk DTC Patients.

CONTEXT: American Thyroid Association (ATA) guidelines do not consider age at diagnosis as a prognostic factor on the estimation of the risk of persistent/recurrent disease in differentiated thyroid carcinoma (DTC) patients. While age at diagnosis has already been assessed in high-risk patients, it remains to be established in low- and intermediate-risk patients. OBJECTIVE: The aim of our study was to investigate the role of age as a prognostic factor in the short- and long-term outcome of DTC patients classified at low and intermediate risk according to the ATA stratification risk system. METHODS: We retrospectively evaluated 863 DTC patients (mean follow-up: 10 ± 6.2 years) 52% classified as low (449/863) and 48% as intermediate risk (414/863). For each ATA-risk class patients were divided into subgroups based on age at diagnosis (<55 or ≥55 years). RESULTS: In the intermediate-risk group, patients aged 55 years or older had a higher rate of structural disease (11.6% vs 8.9%), recurrent disease (4.1% vs 0.7%), and death (4.1% vs 1%) when compared with younger patients (<55 years) (P = .007). Multivariate analysis confirmed that older age at diagnosis (odds ratio [OR] = 3.9; 95% CI, 1.9-8.6; P < .001) was an independent risk factor for worse long-term outcome together with response to initial therapy (OR = 13.0; 95% CI, 6.3-27.9; P < .001), and T (OR = 32; 95% CI, 1.4-7.1; P = .005) and N category (OR = 2.3; 95% CI, 1.1-5.0; P = .03). Nevertheless, a negative effect of older age was documented only in the subgroup of intermediate DTC patients with persistent structural disease after initial therapy. Indeed, the rate of worse long-term outcome rose from 13.3% in the whole population of intermediate DTC patients to 47.8% in patients with persistent structural disease after initial therapy (P < .001) and to 80% in patients older than 55 years and persistent structural disease after initial therapy (P = .02). CONCLUSION: Our results suggest that age at diagnosis further predict individual outcomes in Intermediate-Risk DTC allowing ongoing management to be tailored accordingly.

Dynamic Risk Stratification Integrated with ATA Risk System for Predicting Long-Term Outcome in Papillary Thyroid Cancer.

BACKGROUND: In recent years, there has been a renewed interest in thyroid cancer management paradigms that use individualized risk assessments as the basis for treatment and follow-up recommendations. In this study, we assumed that the long-term follow-up of differentiated thyroid cancer patients might be better tailored by integrating the response to initial therapy with the America Thyroid Association (ATA) risk classes. METHODS: This retrospective study included low- and intermediate-risk papillary thyroid cancer (PTC) patients followed up for a median time of 8 years and classified according to the response to initial therapy assessed 6-12 months after initial treatment. RESULTS: After a median follow-up of 8 years, in the initial excellent response subgroup of PTC patients (n = 522), the rate of recurrent disease was significantly higher in intermediate-risk patients than in low-risk PTC patients (6.9% versus 1.2%, p = 0.0005). Similarly, in the initial biochemical incomplete response subgroup (n = 82), the rate of excellent response was significantly higher in low-risk PTC patients (58.0%) than in intermediate-risk PTC patients (33.3%) (p = 0.007). Finally, in the initial structural incomplete response subgroup (n = 66), the rate of excellent response was higher in low-risk patients (80.0%) than in intermediate-risk patients (46.4%) (p = 0.08). Moreover, all patients with initial indeterminate response had an excellent response at the last follow-up visit. ATA risk classes were independently associated with long-term outcome in each subgroup of patients classified dynamically after initial therapy and the overall prognostic performance, defined via ROC curve analysis, of response to initial therapy integrated with the ATA risk system (AUC: 0.89; 95% CI: 0.86-0.92) was significantly higher compared to the ATA risk stratification (AUC 0.69; 95% CI: 0.65-0.74, p < 0.001) or the dynamic risk stratification (DRS) systems alone (AUC: 0.86 95% CI: 0.82-0.90, p = 0.007). CONCLUSIONS: This study of a large cohort of PTC patients showed that the initial ATA risk criteria may be useful for improving the risk-adapted management of PTC patients based on the response to initial therapy.

Pilot Study on the Impact of Polymorphisms Linked to Multi-Kinase Inhibitor Metabolism on Lenvatinib Side Effects in Patients with Advanced Thyroid Cancer.

Multi-kinase inhibitors (MKIs) represent the best therapeutic option in advanced thyroid cancer patients. The therapeutic efficacy and toxicity of MKIs are very heterogeneous and are difficult to predict before starting treatment. Moreover, due to the development of severe adverse events, it is necessary to interrupt the therapy some patients. Using a pharmacogenetic approach, we evaluated polymorphisms in genes coding for proteins involved with the absorption and elimination of the drug in 18 advanced thyroid cancer patients treated with lenvatinib, and correlated the genetic background with (1) diarrhea, nausea, vomiting and epigastric pain; (2) oral mucositis and xerostomia; (3) hypertension and proteinuria; (4) asthenia; (5) anorexia and weight loss; (6) hand foot syndrome. Analyzed variants belong to cytochrome P450 (CYP3A4 rs2242480 and rs2687116 and CYP3A5 rs776746) genes and to ATP-binding cassette transporters (ABCB1 rs1045642, rs2032582 and rs2235048 and ABCG2 rs2231142). Our results suggest that the GG genotype for rs2242480 in CYP3A4 and CC genotype in rs776746 for CYP3A5 were both associated with the presence of hypertension. Being heterozygous for SNPs in the ABCB1 gene (rs1045642 and 2235048) implicated a higher grade of weight loss. The ABCG2 rs2231142 statistically correlated with a higher extent of mucositis and xerostomia (CC genotype). Heterozygous and rare homozygous genotypes for rs2242480 in CYP3A4 and for rs776746 for CYP3A5 were found to be statistically linked to a worse outcome. Evaluating the genetic profile before starting lenvatinib treatment may help to predict the occurrence and grade of some side effects, and may contribute to improving patient management.