Factors That Influence Conversion to Resectability and Survival After Resection of Metastases in RAS WT Metastatic Colorectal Cancer (mCRC): Analysis of FIRE-3- AIOKRK0306

Abstract

Background: Tumor assessments after first-line therapy of RAS wild-type mCRC with cetuximab (cet) versus bevacizumab (bev) in combination with FOLFIRI were evaluated for factors influencing resectability, conversion to resectability, and survival after best response.

Methods: Conversion to resectability was defined as conversion of initially unresectable to resectable disease at best response as determined by retrospective assessment. Univariate and multivariate logistic models were fitted with resectability at best response as response variable. A Cox model comparing the survival from best response was used to measure the influence of treatment, resectability at best response, and resection. Interaction of resection and treatment arm on survival was tested by likelihood ratio test.

Results: Overall, 270 patients were evaluable (127 cet-arm, 143 bev-arm). Lung metastases (odds ratio [OR] 0.35, 95% confidence response [CI] 0.19-0.63), BRAF mutation (OR 0.33, 95% CI 0.12-0.82), and elevated alkaline phosphatase (OR 0.42, 95% CI 0.18-0.9) before randomization were associated with less chance of successful conversion and were integrated into a nomogram. Early tumor shrinkage (OR 1.86, 95% CI 1.06-3.3; p 0.034) and depth of response (OR 1.02, 95% CI 1.01-1.03; p < 0.001) were associated with successful conversion therapy. Resection of metastases improved post-best-response survival (hazard ratio 0.53, 95% CI 0.29-0.97; p = 0.039), predominantely in cet-treated patients (interaction test, p = 0.02).

Conclusions: Conversion to resectability is significantly associated with baseline characteristics that can be used in a nomogram to predict conversion. Moreover, early efficacy parameters (ETS and DpR) are associated with successful conversion therapy. In FIRE-3, resection of metastases was associated with improved post-best response survival, this effect originated predominantly from the cetuximab-based study arm.

Fig. 1

Study arms, resectability, and performed resections (RAS wild-type population). *One patient in the bevacizumab arm was resectable at baseline and became unresectable at best response (nadir) and was consecutively not resected

Fig. 2

Resectability review of the RAS wild-type subset. For baseline assessments, original scores were simplified to “yes” (=R0 resection with or without perioperative therapy only limited to the abdomen or not) and “no” (=conversion therapy or not resectable). For the best response assessment original scores were simplified to “yes” (=R0 resection with or without ablative modality limited to the abdomen or not) and “no” (=not resectable)

Fig. 2

Resectability review of the RAS wild-type subset. For baseline assessments, original scores were simplified to “yes” (=R0 resection with or without perioperative therapy only limited to the abdomen or not) and “no” (=conversion therapy or not resectable). For the best response assessment original scores were simplified to “yes” (=R0 resection with or without ablative modality limited to the abdomen or not) and “no” (=not resectable)

Fig. 3

Effect of potential predictors on the probability of becoming resectable at best response. Representation of unadjusted odds ratios (logistic univariate models), odds ratios adjusted for other predictors (logistic multivariate model) and odds ratios of the reduced model. Only patients whose tumor lesions were assessed as non-resectable at baseline were kept in the analyses. The response variable is binary and equals 1 if the patient status became resectable at best response and zero otherwise. Post-baseline variables (log time to no best response, ETS, Depth of response) were excluded from the multivariate analyses as well as some variables due to correlation/colinearity (prior adjuvant treatment was removed, because it is highly correlated with metastasis type, some variables in link with the presence of metastasis in an organ and the number of organs with metastasis, the dichotomous version of alkaline phosphatase as the log-transformed version was included in the analysis). LLD liver limited disease; LuLD lung limited disease; ETS early tumor shrinkage; AP alkaline phosphatase; WBC white blood cell count. In the multivariate analyses, LLD patients seem to have less chance to be resectable at best response than non-LDD patients. The reason for this is the presence of the variable “lung metastasis” and “Number of organs with metastasis” in the model. Once these two variables are removed from the analyses, LLD OR is greater than 1 (but p value is still > 0.05)

Fig. 4

Nomogram for the prediction of successful conversion therapy. To get a patient prediction of resectability at nadir: Step 1, compute the number of points corresponding to the patient by drawing vertical lines from patient lung metastasis status, BRAF status and log-transformed alkalic phosphatase value to the “Points” scale. A patient without any lung metastasis, a wild-type BRAF tumor and log transformed baseline alkalic phosphatase of 4 would get a total number of points of 44 + 52 + 86 = 182. Step 2, report this value on “Total Points” scale and draw a vertical line passing through the value 182. The intersection of this vertical line with “Probability of resectability at nadir” scale gives the patient probability of resectability at nadir

Fig. 5

a Kaplan–Meier plot representing post-best response survival for each treatment—resectability at best response—resected status group. b Fitted post best response survival based on Model with smallest AIC according to resectability at best response, resection, and first-line treatment