Comparison of prognostic prediction models for rectal gastrointestinal stromal tumor

Introduction

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract and represent approximately 1~3% of all primary gastrointestinal malignancies [1, 2]. Their clinical and pathological features differ significantly in terms of sites (stomach, small intestine, colon and rectum) [3, 4]. Rectal GISTs (RGISTs) account for less than 5% of all GIST cases and are associated with a poor survival prognosis [5–6].

Most GISTs contain a mutation in the KIT proto-oncogene, or less frequently in the PDGFRA gene, and are usually responsive to the tyrosine kinase inhibitor imatinib mesylate (IM) (Gleevec, Novartis Pharmaceuticals Corporation, Basel, Switzerland) [7, 8]. With the advent of molecular-targeted therapy, the treatment of metastatic or unresectable GISTs has generated excellent results. Perioperative IM therapy may be particularly beneficial for RGISTs, and some have reported that neoadjuvant chemotherapy can reduce tumor volume, thereby facilitating surgical resection or increasing the likelihood of organ retention and further improving patient prognosis [9–11]. Based on these data and the presence of KIT exon 11 mutations in most RGISTs (KIT exon 11 is more sensitive to IM than other mutations, such as KIT exon 9 or PDGFRA), preoperative IM therapy is recommended for RGISTs in the majority of advanced cases. The surgical approach for RGIST removal has also changed significantly from radical excision to local resection or low anterior resection [12–15].

When screening patients who may benefit from IM-assisted therapy, the most important factor is estimation of the risk of recurrence after primary GIST resection. Risk stratification of GISTs is mainly based on tumor size, mitotic activity and location, the most well-recognized indicators of recurrent or metastatic risk [16]. The American College of Surgeons Oncology Group (ACOSOG) Z9001 trial also confirmed these three prognostic indicators [17]. However, due to a paucity of research and insufficient studies, no individual or optimal staging system exists for RGISTs. Two commonly used staging systems for prognosis are the modified National Institutes of Health consensus criteria (NIH criteria of 2008) and the WHO Classification of Tumors of the Digestive System consensus criteria (WHO criteria of 2013) (Table 1) [18, 19]. Neither of these classifications provides a quantifiable risk of recurrence for individual patients, which limits the ability of stratifying the risk ratio of RGISTs compared to other GISTs. A nomogram developed at Memorial Sloan-Kettering Cancer Center (MSKCC) has been employed to predict the risk of tumor recurrence after gross surgical resection of GIST [20]. A moderate risk of RGISTs was revealed for the stomach and small intestine, yet only 14 colonic or rectal GISTs were included in the nomogram, potentially reducing the productive and predictive value for RGISTs. Therefore, it is necessary to develop a specific stratification system for RGIST recurrence to identify patients with a high risk of recurrence who can receive individualized treatment according to their specific circumstances.

In this study, we developed a new, effective statistical model for individual RGIST patients based on a moderately large cohort. Our aim was to predict the risk of tumor recurrence after gross surgical resection of localized primary RGISTs combined with or without postoperative chemotherapy. Furthermore, we compared this model with the NIH, WHO and FD-Hou (a staging system developed at Fudan University by Hou Yingyong based on 12 clinicopathological parameters, Table 1) staging systems [21, 22], and we confirmed the role of IM in the management of RGISTs.

Results

Discussion

In the past twenty years, GISTs have been the most successfully treated type of solid tumor by molecular-targeted therapy. Molecular targeting of the KIT gene and the PDGFRA gene can effectively control recurrent and metastatic high-risk GIST and has become a model for molecular-targeted therapy of solid tumors. The response of GISTs to IM significantly depends on the mutation sites in KIT and PDGFRA. KIT exon 11 mutations may be markedly responsive to IM, whereas KIT exon 9 mutations may require a higher dose of IM. Additionally, wildtype tumors and PDGFRA-mutated tumors show ineffective responses to IM [23, 24]. Therefore, GISTs have become a model for individualized treatment of tumors. Neoadjuvant therapy and adjuvant therapy might benefit to RGIST patients and extend their RFS and OS [9, 11, 25]. As the incidence of RGIST is exceedingly low, very scant information is available on RGISTs. Due to the use of IM and the specificity of rectal anatomy (locally progressive RGISTs may be bulky due to the pelvic space and often adhere to the pelvic floor), the majority of patients currently choose to undergo molecular-targeted therapy instead of direct surgery after diagnosis of an RGIST. Unless the tumor is small, surgery is expected to preserve the sphincter. Therefore, the natural history of RGISTs has been less extensively investigated. This study has an apparent strength due to the relatively large number of primary specimens.

The aforementioned studies have confirmed the role of IM in RGISTs. In our study, the Kaplan-Meier curve for RFS indicated no significance between the IM and no-IM groups. Of note, we found a statistically significant difference in OS based on IM; none of the patients in the IM group incurred an incident event as of the last follow-up. The survival curve of RFS indicated that taking IM may be better than not taking IM.

Our department of pathology has accumulated numerous GIST samples because of our long-term attention to the clinical treatment of GISTs [21, 22, 26]. Based on the collected samples, our study used newer statistical tools to focus on the treatment and prognosis of RGISTs. Previous reports have indicated the specific biological and prognostic features of RGISTs compared to GISTs at other locations, as well as their high local recurrence rate [5, 6]. Moreover, in two commonly used staging systems (NIH and WHO), an appropriate grading system for RGISTs was not developed, but rather RGISTs were incorporated into the system used for small intestinal GISTs. Our research led to the development of a nomogram model to predict the individual prognosis of RGIST patients. Tumor size was consistent with that in previous reports and was easy to interpret, and the mitotic rate was assessed once again by two experienced pathologists. The concordance probability of the nomogram showed better performance than that of the NIH, WHO and FD-Hou systems. The cut-off value of 65 points was selected to stratify risk into low and high. An obvious stratification in the four staging systems was observed by Kaplan-Meier curves, but we did not find a significant difference among the groups with relatively lower risk RGISTs using the WHO or NIH systems. Because of the low incidence of RGISTs, the use of multi-grade stratification systems, and the low number of cases within each grade, individual grades may not have included any cases; this may be especially true for the WHO system, which has 8 grades of GIST. Moreover, classification of the malignant group in the WHO system (3b, 5, 6a, 6b) was not superior to that of the nomogram, which alerted us to the necessity of concise estimation of RGIST classification. Our study also suggested that it is unnecessary to focus on subset stratification for relatively lower-risk RGIST cases and that mainly high-risk patients should be screened. The FD-Hou staging system uses a variety of morphological indicators and thus requires a GIST pathologist with specific training. High-risk malignances in the four stratifications can all benefit from treatment with the tyrosine kinase inhibitor IM. The prognostic nomogram provides a better predictive performance for individual patients than the prediction resulting from dividing patients into large groups. Nomograms in other studies quantified the risk of tumor recurrence after complete resection as a continuous variable, and we used a cut-off value as a threshold for tumor recurrence to help select patients for IM treatment [20, 27, 28].

No difference in RFS was observed for high-risk patients, regardless of whether they received IM treatment after the first surgery. In the analysis of OS, high-risk patients who received IM after the first surgery showed a better prognosis, though statistical significance was not reached. This result may be due to the low number of patients with IM therapy after the first resection in the cases we included because our samples were from both the IM era and the pre-IM era, in which IM was unavailable. Ultimately, after applying the nomogram, the survival curve of the IM subgroup in the malignant group exhibited a possible trend for improved prognosis. Therefore, we recommend that the malignant group (>65 points) should actively receive IM therapy and that the nonmalignant group (≤65 points) may require long-term follow-up.

As our staging system is based on two indicators of tumor size and mitotic rate, it is only suitable for patients who have not received any treatment before surgery. If the patient has been treated before surgery, the tumor size and the mitotic count of postoperative pathological specimens may be affected. Hence, this model can be used to predict the patient's recurrence risk after surgery in GIST cases originating in the rectum and without any treatment before surgery, as long as the clinician records the tumor size of the patient during surgery and the mitotic count (50 HPFs) of the postoperative pathological specimen.

There are several limitations in this study. First, the validation cohort C-indices were only 0.557 (RFS) and 0.600 (OS), which may be attributed to the small sample size (n=26). Second, the two factors used to develop the nomogram might not have been measured uniformly across institutions. Tumor size may be affected by fixation or imaging differences, and the mitotic rate can be largely affected by subjective factors; therefore, experienced pathologists are still needed to assess the validity of this novel nomogram. Third, our study only recruited patients in China, and the results may not be applicable to other countries, especially Western countries. Finally, with a retrospective study, unknown or unobserved sources may result in information bias.

Conclusion

Our study pioneers the development of a concise two-tier grading system (FD-ZS system) for prognostic prediction of RGISTs based on tumor size, mitotic rate and a cut-off value to help RGIST patients determine whether to undergo adjuvant IM treatment. The predictive ability of the system is simpler to that of current international systems, including the NIH system (2008), the WHO system (2013), and the FD-Hou clinicopathological parameters staging system. The FD-ZS staging system may help to more concisely guide the combined use of surgery and molecular-targeted therapy in RGIST and improve the prognosis of RGIST patients. In addition, we found that IM affected the OS of RGIST patients and may result in longer survival.

Materials and Methods

Supplementary Materials

Supplementary Figures

Supplementary Table 1

Supplementary Table 2

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Supplementary Table 5