Letter to the editor: Incidence rate of occult lymph node metastasis in clinical T1 − 2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study

Recently, we had the honor of reading the article titled " Incidence rate of occult lymph node metastasis in clinical T1 − 2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study “ [1]. This study retrospectively included 242 eligible patients from 4 centers to determine the incidence of OLM in cT1 − 2N0M0 SCLC patients. For each lesion, two ROIs were defined using total tumor volume ( GTV ) and peritumoral 15 mm volume ( PTV ). Five models were constructed by extracting 1595 radiologic features based on enhanced ct from GTV and PTV, and the performance of the models was evaluated using indicators such as area under the curve ( AUC ), accuracy, sensitivity, specificity, calibration curve and decision curve analysis ( DCA ). At the same time, clinical parameters and rad _ score ( GTV and PTV ) were included to construct nomogram. The combined model combines three radiological features of GTV and PTV, as well as two clinical parameters ( smoking status and body size ), showing strong predictive power. In the external validation cohort, the peak AUC value of the model is 0.772, which is better than the alternative model. The nomogram can significantly improve the diagnostic accuracy of radiologists and add substantial value to the clinical decision-making process of patients with cT1 − 2N0M0 SCLC.

We sincerely appreciate the contributions made by the authors. However, there are issues in this study that require further exploration.The clinical factors included in this study lacked laboratory indicators such as CEA, CA153, CA199, and CA125. CEA can be used as a predictive marker for the risk of recurrence and death measured over time. There is a certain correlation between the degree of CEA elevation and lung cancer, and with the increase of TNM stage, the serum level is also increased [2]. CA153, CA199 and CA125 are related to the diagnosis, identification and prognosis of lung cancer [3, 4]. These indicators can reflect the degree of differentiation and malignancy of lung cancer to a certain extent. And these indicators have a certain correlation with tumor metastasis. At the same time, these laboratory indicators are often checked when the patient is admitted to the hospital, and the acquisition is relatively simple. If these laboratory indicators are included in the nomogram through statistical tests, it is expected to further improve the model performance.

Finally, we express our gratitude once again for the authors’ contributions to this study. We hope our insights prove valuable for their further research, and we look forward to hearing their opinions.