Barriers and Facilitators to the Choice of Active Surveillance for Low-Risk Papillary Thyroid Cancer in China: A Qualitative Study Examining Patient Perspectives

Zhu, Pingting; Zhang, Qianqian; Wu, Qiwei; Shi, Guanghui; Wang, Wen; Xu, Huiwen; Zhang, Li; Qian, Meiyan; Hegarty, Josephine

doi:10.1089/thy.2022.0347

Cited by 13 publications

(1 citation statement)

References 33 publications

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“…Therefore, accurately predicting lymph node metastasis in PTMC patients can signi cantly assist clinicians in making informed decisions. It is also well-known that selecting a treatment plan for PTMC patients is a complex process that also needs to consider patient preferences and the psychological anxiety of living with cancer [20,21], especially for patients with lymph node metastasis. These clinical issues highlight the importance of accurately predicting lymph node metastasis through imaging and clinical features and underscore the broad clinical application prospects of developing a practical prediction model for lymph node metastasis in patients with PTMC.…”

Section: Introductionmentioning

confidence: 99%

Predictive model and clinical application for lymph node metastasis in papillary thyroid microcarcinoma

Su,

Sun,

et al. 2024

Preprint

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Purpose Papillary thyroid microcarcinomas (PTMC), small tumors under 10 mm, represent a major part of the increase in papillary thyroid cancer cases. The treatment plans for PTMC patients with lymph node metastasi should be different from those without lymph node metastasis. Therefore, accurately identifying patients with cervical lymph node metastasis is of great clinical significance. Methods We analyzed data from 256 patients diagnosed with PTMC, using age, gender, tumor size, lesion count, and ACR score as predictors. Outcomes were based on cervical lymph node pathology. Four machine learning models—Random Forest, Multivariate Logistic Regression, Support Vector Machine, and Xgboost—were tested for their predictive accuracy and clinical utility. We then created an online website for direct prediction and designed online platforms that allow other researchers to upload their data for model building and prediction. The website and platform design is based on "shiny" package. Results The Random Forest model proved optimal, achieving an AUC of 0.92. It showed high sensitivity (0.83) and specificity (0.90) at the best threshold of 0.46. The link to the website we built based on this model is as follows: http://yucemoxing.online:8082. Additionally, the link to the online platforms that allows userss to upload their own data for model building and prediction is as follows: http://yucemoxing.online:8081,http://yucemoxing.site:8089,http://yucemoxing.online:8084,http://yucemoxing.online:8085,http://yucemoxing.online:8083,http://yucemoxing.online:8088, http://yucemoxing.online:8087, http://yucemoxing.online:8086 Conclusions Machine learning tools can reliably predict cervical lymph node metastasis in PTMC patients. The developed websites offer valuable tools for clinical application, enhancing decision-making in treatment strategies.

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Section: Introductionmentioning

confidence: 99%

Predictive model and clinical application for lymph node metastasis in papillary thyroid microcarcinoma

Su,

Sun,

et al. 2024

Preprint

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Thermal Ablation for Papillary Thyroid Carcinoma

Yan,

Li,

et al. 2024

JAMA Otolaryngol Head Neck Surg

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ImportanceImage-guided thermal ablation has been administered for patients with T1N0M0 papillary thyroid carcinoma (PTC) who elect to not undergo surgery or receive active surveillance. Considering the indolent nature of PTC, long-term outcomes of ablation are needed.ObjectiveTo investigate l0-year outcomes of thermal ablation in treating T1N0M0 PTC.Design, Setting, and ParticipantsThis multicenter study was conducted at 4 university-affiliated hospitals in China and included 179 consecutive patients with T1N0M0 PTC (median [IQR] volume, 88.0 [163.2] mm3) who underwent thermal ablation between June 2010 and March 2014. Patients who were ineligible to undergo surgery or elected not to were included, and patients had PTC tumors that were smaller than 20 mm as confirmed by biopsy; no clinical or imaging evidence of extrathyroidal extension, lymph node metastasis (LNM), or distant metastasis; and no history of neck irradiation.Main Outcomes and MeasuresThe primary outcomes were disease progression (LNM, newly developed tumors, persistent tumors, and distant metastasis) and disease-free survival (DFS). Secondary outcomes were technical success, volume reduction rate, tumor disappearance, complications, and delayed surgery. DFS was calculated using a Kaplan-Meier analysis.ResultsAmong the 179 patients, the mean (SD) age was 45.8 (12.7) years, and 118 (65.9%) were female. During a mean (SD) follow-up period of 120.8 (10.8) months, disease progression was found in 11 of 179 patients (6.1%), including LNM in 4 patients (2.2%), newly developed tumors in 6 patients (3.3%), and persistent tumor in 1 patient (0.6%). The 10-year DFS was 93.9%. The technical success, median volume reduction rate, and tumor disappearance rate was 100%, 100%, and 97.2%, respectively. The magnitude of the disease progression (6.1% vs 7.1%; difference, 1.0%; 95% CI, −6.5% to 25.6%) and DFS (93.9% vs 92.9%; difference, 1.0%, 95% CI, −6.5% to 25.6%) between patients with T1a and T1b tumors was small. The difference in the rate of tumor disappearance between T1a and T1b tumors was large (99.4% vs 71.4%; difference, 28.0%; 95% CI, 10.9%-54.0%). One patient experienced transient voice hoarseness (0.6%). Because of anxiety, 1 patient underwent delayed surgery (0.6%).Conclusions and RelevanceThe results of this 10-year multicenter cohort study suggest that thermal ablation is an effective and safe alternative for patients with T1N0M0 PTC who do not undergo surgery or receive active surveillance. For safe and effective treatment, accurate radiologic evaluation, an understanding of ablation techniques, and experienced physicians are recommended.

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Long‐term outcomes of active surveillance for low‐risk papillary thyroid carcinoma: Progression patterns and tumor calcification

Sugitani,

Nagaoka,

Saitou

et al. 2024

World j. surg.

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IntroductionActive surveillance (AS) for low‐risk papillary thyroid carcinoma (PTC) is acknowledged as a valid management strategy. While older age is identified as a favorable factor for progression, long‐term evidence is scarce and lifelong monitoring has been deemed essential. This study investigated progression patterns and tumor calcification under long‐term AS and explored the possibility of ending follow‐up.Materials and MethodsA total of 650 patients with low‐risk PTC who chose AS were enrolled. Progression was defined as either tumor enlargement (≥3 mm from initiation) or development of clinically apparent lymph node metastasis.ResultsThe median observation period was 8 years; 45.2% were under surveillance for ≥10 years. Overall, 80 patients (12.3%) exhibited progression. Median age and observation period at the time of progression were 55 and 4 years, respectively. Only 2 patients showed progression after 15 years of follow‐up and 5 patients showed progression after reaching 80 years old. Among 71 patients experiencing tumor enlargement, surgery was performed immediately in 32 patients. The remaining 39 patients continued surveillance, but only 5 demonstrated ongoing enlargement thereafter. Of 40 surgeries due to progression, 36 were conducted within the first 10 years. The degree of calcification correlated with age and observation periods. No progression occurred after the development of rim calcification.ConclusionsProgression during AS was extremely rare in older patients with long‐term surveillance and in tumors with rim calcification. It may be feasible to consider ending scheduled surveillance visits for these patients. Instances of progression halting after enlargement are not uncommon.

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Barriers and Facilitators to the Choice of Active Surveillance for Low-Risk Papillary Thyroid Cancer in China: A Qualitative Study Examining Patient Perspectives

Cited by 13 publications

References 33 publications

Predictive model and clinical application for lymph node metastasis in papillary thyroid microcarcinoma

Predictive model and clinical application for lymph node metastasis in papillary thyroid microcarcinoma

Thermal Ablation for Papillary Thyroid Carcinoma

Long‐term outcomes of active surveillance for low‐risk papillary thyroid carcinoma: Progression patterns and tumor calcification

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