In our study, several factors were not uniformly distributed between the para-aortic lymph node metastasis and non-metastasis groups. With regard to sex, the proportion of male participants with metastasis was higher. In terms of middle and upper abdominal tumors and cumulative tumors in the entire stomach, the proportion of patients with metastasis significantly increased. In patients with T4 stage or Borrmann type IV (i.e., invasion of the serosa), the proportion of patients with metastasis increased. The appearance of metastases also indicated a higher N stage, larger surgery area, lower degree of radical treatment, and higher proportion of organ metastasis.
In the multivariate regression analysis, factors such as male sex, Borrmann types III and IV, T4 stage, and pancreatic or splenic metastases can be the factors associated with pre- and intraoperative treatment decisions, which can be used for the independent prediction of para-aortic lymph node metastases.
Experience as a result of caseload, surgical skill, and case selection are extremely important. Physicians from different hospitals may have individual surgical habits and judgments about disease conditions. By contrast, physicians from the same department usually have similar treatment ideas due to long-term preoperative discussion, perioperative ward round, and interactions between the mentor and student. A retrospective study conducted at a single center can prevent subjective differences between different hospitals as much as possible. Even so, the selection bias in retrospective analysis cannot be prevented. The patient’s condition, as determined using preoperative and intraoperative findings, and even financial status are the factors affecting intraoperative treatment decisions.
In future studies, two perspectives should be used in prospective clinical studies: the clinicopathological factors associated with para-aortic lymph node metastasis must be determined and the associated specific lymph node sites should be identified. In addition, a study about whether the metastasis status of specific lymph node sites should be included and whether there are sentinel lymph nodes for para-aortic lymph nodes must be conducted. A previous article has shown that station No.7 was the only significant indicator of PAN metastasis after adjusting for other variables. The diagnostic sensitivity and specificity of station No.7 for PAN metastasis were high, which is clinically useful, and this may be a convenient diagnostic indicator of PAN metastasis.
We focused on the principles of the surgeons and did not include N stage as a variable because it is challenging to accurately determine N stage before and during surgery. We introduced the variable peritoneal metastasis status and found that the accuracy significantly improved compared with before. Improvements in accuracy are dependent on the operability of continuous variables, such as tumor size and age, and do not require manual grouping such as that in the past. The predictors extracted from the two software were different. However, the accuracy of the modeler was higher, and the operations were simpler. The accuracy can still be improved. In the future, more data analysis methods could be introduced, which include decision trees, C5.0, and other methods that are preliminarily used in medical data analysis to better determine the optimal analytical method for different data types. In addition, clinical experience must also be introduced to more effectively optimize the accuracy of model prediction and generate more data for validation.
In conclusion, sex, Borrmann type, T stage, and combined organ metastasis were associated with PAN metastasis. Neural networks can be a good predictive model.