Many previous studies have tried to predict pathologic response to chemotherapy. However, a comprehensive model for predicting pathologic response[10–13] is still lacking. This study established a prognostic model to predict pathologic response after chemotherapy based on several clinical factors that are obtainable in a non-invasive fashion. The weight and correlation of each factor influencing pathologic response was fully considered. The validation results suggest that the model could predict pathologic response with precision, as well as good sensitivity and specificity.
The RECIST criteria are currently widely used to evaluate chemotherapy response based on radiographic tumor change. As systematic treatment protocols and targeted drugs are refined, tumor response would also present as internal composition changes. Tumor tissue was replaced by necrosis and inflammatory cells in pathologic examination, causing tumor size to remain stable or even increase. Previous studies shown that although some patients were evaluated as unresponsive by RECIST criteria, major response could still be found by pathological examinations[14]. Consistently, in this study, major pathologic response was also observed in 39 (45.3%) patients of those with tumor increase after preoperative chemotherapy. This finding indicates that tumor radiographic changes after chemotherapy are not completely in consistent with the pathological response. Hence, the model for predicting pathological response in this study could be considered as a supplement to evaluate chemotherapy response and helps to make treatment strategies more comprehensively. For patients who were predicted to show major pathologic response despite stable tumor size, hepatectomy could be performed if the liver metastasis was resectable. If the metastases were still unresectable, our nomogram could allow for continuing with chemotherapy in pursuit of maximum pathologic response, and even complete pathologic response[15, 16]. In addition, patients with major pathologic response would show clearer tumor-normal liver interface (TNI) [17, 18], allowing for narrower or even R1 margins to be acceptable during surgery[19]. However, if patients were predicted to have minor pathologic response and still stable or progressing in size, it would be more reasonable to select a second-line chemotherapy regimen with higher efficiency to control tumor growth instead of pursuing sugery[4, 20].
In this study, we found several clinical factors that predicted the pathologic response of patients with CRLM to preoperative chemotherapy. Patients with RAS wild-type were more likely to experience a major response after preoperative chemotherapy. RAS status has long been known to be associated with long-term survival and the sensitivity to chemotherapy[21, 22]. Previous studies also found similar results showing that major responses were more common in patients with RAS wild-type compared with those with RAS mutant [10, 13]. Tumor size and tumor number has also been proven to correlate with degree of pathologic response. Zimmitti et al. and Georgios et al. showed that CRLM size > 3 cm was an independent predictor of poor response to chemotherapy[10, 13]. Patients with larger tumors and higher tumor number reflected a heavier tumor burden, which is already known to be a negative factor for survival[23]. DFI < 12 months is another factor shown to be in association with major pathological response. It might be explained by the following reason. Patients with metachronous liver metastases (DFI ≥ 12months) might have received adjuvant chemotherapy after resection of primary tumors. Therefore, it is often needed to change to 2nd-line chemotherapy when liver metastases occur. Previous literature shown that the efficiency of second-line chemotherapy was only about 20%[24], so it might be difficult for these patients to develop major pathologic response. However, patients with simultaneous liver metastases usually don’t receive any treatment previously, so their pathologic response after preoperative chemotherapy would be relatively higher.
It was interesting that some other factors, such as primary tumor site and the use of bevacizumab[11, 25], which were previously shown to be related to chemotherapy response, were found not to be independent factors influencing pathologic response in our study. Georgios et al. also found that adding bevacizumab was not associated with pathologic response in multivariate analysis (P = 0.3)[10]. Primary tumor location was also an important factor for chemotherapy response. Wang et al. and Serayssol et al. found that it was associated with poor pathologic response[11, 12]. However, other studies did not find similar results. In order to avoid bias arising from to patient selection and operating within a single-center sample, we choose three important factors - primary tumor site, RAS mutational status, and the use of bevacizumab and performed a subgroup analysis to assess the predictive power of this model in different subgroups. The results showed that the nomogram performed well in predicting major pathologic response to preoperative chemotherapy in patients with different characteristics.
There are several limitations in this study. The main disadvantage of this study is that it uses data collected retrospectively with a limited sample size, which makes selection bias unavoidable. A certain degree of heterogeneity in terms of diagnosis and treatment might influence the results of the study. In addition, metastatic liver tumors are highly heterogeneous suggesting that there may be differences in pathologic response rates between different tumors. Thus, we chose the average pathologic response rate according to the method of Blazer et al. Finally, in this study we only performed internal validation since there was no external validation cohort. Because of this, the reliability of the model was suboptimal.