Nowadays, increasing evidence strongly suggest clinicians to explore valuable prognostic factors and further construct risk stratification model to evaluate prognosis and guide treatment decisions for CC patients 15–19. However, the role of histology subtype is always overlooked, especially in MAC. Meanwhile, accurate prediction of the survival for C-MAC patients is crucial for subsequent treatment decisions and long-term follow-up 20, 21, 16. The prediction is extraordinarily valuable in stage II C-MAC, which is a very heterogeneous sub-population of CC 6, 22. To solve this problem, we successfully constructed and validated a specific nomogram integrating multiple clinicopathological factors, which could evaluate the survival probability for individual stage II C-MAC patients who underwent surgical treatment. To our knowledge, the present study was the first nomogram to estimate the individual prognosis of stage II C-MAC patients and also provided risk stratification for patients who needed chemotherapy.
The clinicopathological variables used for this nomogram are routinely collected from the SEER database. This study found that diagnosis age, pT stage, serum CEA level, tumor number and PNI status were the prognostic factors for survival of stage II C-MAC patients after surgical treatment. All of these risk factors have been separately validated by previous studies. For example, some studies found patients with C-MAC tumors generally had a higher pT stage and a higher ratio of PNI, which might cause a higher incidence of the local spreading and lead to lower resection rates 23, 9, 24. There were also studies revealed that preoperative elevated serum CEA level was a risk factor for worse survival 8, 25. Meanwhile, the present study found the prognosis was strongly associated with age, which was confirmed by other studies in patients with C-MAC who underwent surgical treatment 7, 26, 5, 27. The potential explanation was that elderly patients were often accompanied by dysfunction, malnutrition, and comorbidity, which limited them to receive aggressive treatment. Multiple tumor number was also considered as a risk factor for prognosis compared with the solitary tumor in C-MAC by some studies6, 8, 28. Based on these above predictors, we constructed a novel nomogram model in the present study, which avoided the limitation of a single predictor and achieved individual and high predictive accuracy. Besides, this nomogram was extensively validated by discrimination and calibration in a separate internal validation cohort, as well as checked the potential clinical utility by DCA curves. After these validations, the nomogram model had good predictive accuracy for OS and was valuable for clinical decision-making in stage II C-MAC patients. What’s more, these risk factors constructed the nomogram which could be conveniently obtained by any medical center, thus greatly expanding the clinical application value.
In addition, another interesting finding was that the risk score stratification based on the nomogram had good potency to determine postoperative chemotherapy for stage II C-MAC patients. An unsolved dilemma for oncologists is whether to perform postoperative chemotherapy in stage II C-MAC patients 8, 6, 9, 7, 17. Postoperative chemotherapy represented a double-edged sword in stage II C-MAC. Considering the toxicity and resistance of chemotherapeutic agents, recent studies proposed that stage II CC patients should carefully consider postoperative chemotherapy 29, 1, 30. In this study, chemotherapy was beneficial in the high-risk subgroup of stage II C-MAC patients, but it would not improve survival for low- and middle-risk patients. These findings could help oncologists to identify a subset of stage II C-MAC patients who should perform postoperative chemotherapy, which could guide subsequent treatment choice and follow-up.
Given the above, this study confirmed the simple nomogram was valuable for patients with stage II C-MAC, which offered the following primary strengths. First, this nomogram was a good tool to provide accurate and individual prognosis prediction for an individual stage II C-MAC patient. Secondly, as a simple and intuitive graphic calculator, this nomogram was based on readily available data of stage II C-MAC patients, which was easily obtained and convenient for clinical translational application in the clinic 31, 18, 32. Thus, oncologists could rapidly evaluate prognosis and conveniently interpret it to patients, then work together to make subsequent treatment decisions and follow-up. Thirdly, this nomogram came from the largest publicly available database and accepted a systematic assessment, making it more robust and reliable in the clinic 33, 34. In addition, patients stratified by the prognostic scores provided better performance in the individual survival prediction and chemotherapy management for stage II C-MAC patients.
However, there were still several limitations in this study, which were primarily originated from the inherent weaknesses of the retrospective database with inevitable bias and missing data. In addition, some specific information of C-MAC patients was lacking in the SEER database, such as MSI status, KRAS and BRAF mutations. In addition, although the nomogram was well validated by the internal validation cohort, further prospective multi-center validation was still needed.