Dataset Information

Treatment-related adverse effects with TKIs in patients with advanced or radioiodine refractory differentiated thyroid carcinoma: a systematic review and meta-analysis.

ABSTRACT:

Background

Tyrosine kinase inhibitors (TKIs) have been administered to advanced or radio-iodine refractory differentiated thyroid carcinoma (RR-DTC) patients for years. We performed a pooled analysis to explore the frequency of severe adverse effects in advanced or RR-DTC patients treated with sorafenib and lenvatinib.

Methods

We performed a comprehensive search of computerized databases, including PubMed, Web of Science, Ovid, EMASE, and the Cochrane Library, from the drugs' inception to July 2018 to identify clinical trials. All grade and severe adverse events (AEs; grade ≥3) were analyzed. This meta-analysis was conducted in accordance with PRISMA guidelines.

Results

In total, seve studies published from 2012-2018 with 657 patients were eligible for this study. We included two studies (238 patients) that received 200 mg sorafenib twice and five studies (419 patients) that received 24 mg lenvatinib daily. The frequency of AEs was different among the two drugs. Patients in the sorafenib group had a significantly higher frequency of all grade hand-foot syndrome, hypocalcemia, rash, elevated alanine aminotransferase (ALT), and elevated aspartate aminotransferase (AST). Conversely, the lenvatinib group experienced more frequent all grade voice change, hypertension, nausea, and vomiting compared with those with sorafenib. For grade ≥3 adverse effects, hand-foot syndrome, hypocalcemia, and elevated ALT were more frequent in sorafenib-treated patients. Moreover, lenvatinib-treated patients had a significantly higher incidence of severe weight loss, hypertension, and nausea.

Conclusion

Significant differences in common adverse effects, such as all-grade and severe AEs, were detected between sorafenib and lenvatinib in the current study. Early intervention and management of treatment-related AEs (TRAEs) can minimize the impact on patients' quality-of-life, and avoid unnecessary dose reductions and treatment-related discontinuations.

SUBMITTER: Yu ST

PROVIDER: S-EPMC6388981 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe diagnosis of radioiodine refractory differentiated thyroid cancer (RAIR-DTC) is primarily based on clinical evolution and iodine uptake over the lesions, which is still time-consuming, thus urging a predictive model for timely RAIR-DTC informing. The aim of this study was to develop a nomogram model for RAIR prediction among DTC patients with distant metastases (DM).MethodsData were extracted from the treatment and follow-up databases of Peking Union Medical College Hospital between 2010 and 2021. A total of 124 patients were included and divided into RAIR (n=71) and non-RAIR (n=53) according to 2015 ATA guidelines. All patients underwent total thyroidectomy followed by at least two courses of RAI treatment. Serological markers and various clinical, pathological, genetic status, and imaging factors were integrated into this study. The pre-treatment stimulated Tg and pre- and post-treatment suppressed Tg at the first and second course RAI treatment were defined as s-Tg1, s-Tg2, sup-Tg1, and sup-Tg2, respectively. Δs-Tg denoted s-Tg1/s-Tg2, and Δs-TSH denoted s-TSH1/s-TSH2. Multivariate logistic regression and correlation analysis were utilized to determine the independent predictors of RAIR. The performance of the nomogram was assessed by internal validation and receiver operating characteristic (ROC) curve, and benefit in clinical decision-making was assessed using decision curve.ResultsIn univariate logistic regression, nine possible risk factors were related to RAIR. Correlation analysis showed four of the above factors associated with RAIR. Through multivariate logistic regression, Δs-Tg/Δs-TSH<1.50 and age upon diagnosis were obtained to develop a convenient nomogram model for predicting RAIR. The model was internally validated and had good predictive efficacy with an AUC of 0.830, specificity of 0.830, and sensitivity of 0.755. The decision curve also showed that if the model is used for clinical decision-making when the probability threshold is between 0.23 and 0.97, the net benefit of patients is markedly higher than that of the TreatAll and TreatNone control groups.By using 1.50 as a cut-off ofΔs-Tg/Δs-TSH, differing biochemical progression among the generally so-called RAIR can be further stratified as meaningfully rapidly or slowly progressive patients (P=0.012).ConclusionsA convenient user-friendly nomogram model was developed with good predictive efficacy for RAIR. The progression of RAIR can be further stratified as rapidly or slowly progressive by using 1.50 as a cut-off value of Δs-Tg/Δs-TSH.

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