A novel nomogram for identifying high-risk patients among active surveillance candidates with papillary thyroid microcarcinoma

Development and validation of a nomogram for failure to collect oocytes in POSEIDON Groups 3 and 4 undergoing IVF/ICSI treatment

This study aimed to develop and validate a predictive model for failure to collect oocytes in the Patient-Oriented Strategies Encompassing Individualized Oocyte Number (POSEIDON) Groups 3 and 4 during their first in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycle. A retrospective analysis was conducted on patients in POSEIDON Groups 3 and 4 who underwent their first IVF/ICSI cycle at our center from January 2016 to December 2023. A total of 2,373 patients were randomly assigned to the training or validation cohort at a ratio of 6:4. Univariate analysis, the least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis were used to identify the risk factors. It revealed that the anti-Müllerian hormone (AMH) concentration, controlled ovarian stimulation (COS) protocols, the number of follicles ≥ 14 mm on the day of trigger, and the change in estradiol level between the day before trigger and the trigger day (ΔE2) were the independent predictors. A nomogram was constructed accordingly. The areas under the receiver operating characteristic curves (ROC) of the training and the validation cohorts were 0.868 (95% CI: 0.835-0.902) and 0.860 (95% CI: 0.823-0.897), respectively. The calibration curve showed that the predicted risk of the model was in good agreement with the actual results. Decision curve analysis (DCA) demonstrated the clinical value of this nomogram. Our nomogram provides a practical and user-friendly tool for clinical decision-making.

Predicting disease-specific survival in patients undergoing active surveillance for papillary thyroid carcinoma

BACKGROUND

American Thyroid Association guidelines support active surveillance (AS) for low-risk papillary thyroid cancer (PTC). We developed a calculator to aid patient selection.

METHODS

From 2004 to 2020, 148,904 PTC patients were selected from the surveillance, epidemiology, and end results (SEER) database. Univariable and multivariable analysis evaluated patient and treatment characteristics. Patients were randomly allocated into training (80%) or validation sets (20%). Coefficients generated a mathematical model to predict 5- and 10-year disease-specific survival (DSS).

RESULTS

The mean DSS was 15.5 years with a 5- and 10-year DSS of 99.3% and 98.6%, respectively. Age, sex, race, median household income (MHI), tumor size, and nodal status were significant on multivariable analysis (p ≤ 0.05) and included variables in our calculator. 2404 patients underwent non-operative management (NOM) and were more likely older, male, higher MHI, larger tumor size, and less nodal positivity. Area under the curve (AUC) for 5- and 10-year DSS were 0.83 and 0.81, respectively, for the training set and 0.81 and 0.79, respectively, for the validation set.

EXAMPLE

65-year-old White female with a 0.8 cm PTC, cN0 with a MHI ≥ $75,000, had a 10-year predicted DSS was 95.6% with NOM and 99.3% with surgery. Alternatively, changing the patient's race to Hispanic, the 10-year predicted DSS was 94.1% with NOM and 99.0% with surgery.

CONCLUSIONS

As awareness of AS for PTC expands, it is important to consider objective data to guide informed decision making. This validated calculator is a useful tool to predict DSS for patients considering AS for PTC.

Ultrasound-guided fine needle aspiration thyroglobulin in the diagnosis of lymph node metastasis of differentiated papillary thyroid carcinoma and its influencing factors

Background

Ultrasound-guided fine needle aspiration thyroglobulin (FNA-Tg) is recommended for the diagnosis of lymph node metastasis (LNM) in differentiated thyroid cancer (DTC), but its optimal cutoff value remains controversial, and the effect of potential influencing factors on FNA-Tg levels is unclear.

Method

In this study, a retrospective analysis was conducted on 281 patients diagnosed with DTC, encompassing 333 lymph nodes. We analyze the optimal cutoff value and diagnostic efficacy of FNA-Tg, while also evaluating the potential influence of various factors on FNA-Tg.

Results

For FNA-Tg, the optimal cutoff value was 16.1 ng/mL (area under the curve (AUC)= 0.942). The optimal cutoff value for FNA-Tg/sTg was 1.42 (AUC = 0.933). The AUC for FNA combined with FNA-Tg yielded the highest value compared to other combined diagnostic methods (AUC = 0.955). It has been found that serum thyroglobulin (sTg) is positively correlated with FNA-Tg (Rs = 0.318), while serum thyroglobulin antibodies (sTgAb) is negatively correlated with FNA-Tg (Rs = -0.147). In cases where the TNM stage indicated N1b, the presence of large or high volume lymph node metastasis(HVLNM), lymph node lateralization/suspicion (L/S) ratio ≤ 2, ultrasound findings indicating lymph node liquefaction, calcification, and increased blood flow, patients with coexisting Hashimoto's thyroiditis (HT), a tumor size ≥10 mm, and postoperative pathology confirming invasion of the thyroid capsule, higher levels of FNA-Tg were observed. However, the subgroup classification of DTC and the presence or absence of thyroid tissue did not demonstrate any significant impact on the levels of FNA-Tg.

Conclusion

The findings of this study indicate that the utilization of FNA in conjunction with FNA-Tg is a crucial approach for detecting LNM in DTC. TNM stage indicated N1b, the presence of HVLNM, the presence of HT, lymph node L/S ratio, liquefaction, calcification, tumor diameter, sTg and sTgAb are factors that can impact FNA-Tg levels.In the context of clinical application, it is imperative to individualize the use of FNA-Tg.