Tumor stage in patients operated for rectal cancer: a comparison of the pre-operative MR and the resection specimen, with specific attention to the effect of neo-adjuvant radiotherapy

Eeghen, Elmer E. van; Bakker, Sandra D.; Fransen, Gerwin; Flens, Marcel J.; Loffeld, R. J. L. F.

doi:10.21037/jgo.2017.04.05

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…Our results were consistent with previous studies regarding esophageal cancer in which radiotherapy/chemoradiotherapy would cause a decrease in LN number [22][23][24]. These results might be related to tumor and nodal down-staging, which also has been proved in other cancers, including rectal and nonsmall cell lung cancer [25,26]. However, the impact of neoadjuvant chemotherapy alone on the number of dissected LNs in EGC or esophageal cancer has not been reported.…”

Section: Discussionsupporting

confidence: 92%

Impacts of neoadjuvant therapy on the number of dissected lymph nodes in esophagogastric junction cancer patients

Wang

et al. 2023

BMC Gastroenterol

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Background Neoadjuvant therapy favors the prognosis of various cancers, including esophagogastric junction cancer (EGC). However, the impacts of neoadjuvant therapy on the number of dissected lymph nodes (LNs) have not yet been evaluated in EGC. Methods We selected EGC patients from the Surveillance, Epidemiology, and End Results (SEER) database (2006–2017). The optimal number of resected LNs was determined using X-tile software. Overall survival (OS) curves were plotted with the Kaplan–Meier method. Prognostic factors were evaluated using univariate and multivariate COX regression analyses. Results Neoadjuvant radiotherapy significantly decreased the mean number of LN examination compared to the mean number of patients without neoadjuvant therapy (12.2 vs. 17.5, P = 0.003). The mean LN number of patients with neoadjuvant chemoradiotherapy was 16.3, which was also statistically lower than 17.5 (P = 0.001). In contrast, neoadjuvant chemotherapy caused a significant increase in the number of dissected LNs (21.0, P < 0.001). For patients with neoadjuvant chemotherapy, the optimal cutoff value was 19. Patients with > 19 LNs had a better prognosis than those with 1–19 LNs (P < 0.05). For patients with neoadjuvant chemoradiotherapy, the optimal cutoff value was 9. Patients with > 9 LNs had a better prognosis than those with 1–9 LNs (P < 0.05). Conclusions Neoadjuvant radiotherapy and chemoradiotherapy decreased the number of dissected LNs, while neoadjuvant chemotherapy increased it in EGC patients. Hence, at least 10 LNs should be dissected for neoadjuvant chemoradiotherapy and 20 for neoadjuvant chemotherapy, which could be applied in clinical practice.

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Section: Discussionsupporting

confidence: 92%

Impacts of neoadjuvant therapy on the number of dissected lymph nodes in esophagogastric junction cancer patients

Wang

et al. 2023

BMC Gastroenterol

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“…Although nCRT plays an important role in improving the prognosis for LARC, the patient responses to nCRT vary from a complete lack of response to pathologic complete response (pCR) [ 6 , 7 ]. Accurate identification of the tumor response to nCRT is therefore of great value for patients with LARC, allowing ineffective treatment to be avoided.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients

et al. 2022

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Background The purpose of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). Methods Patients with LARC who underwent nCRT were included in this retrospective study (207 patients). After preprocessing of multiparametric MRI, radiomics features were extracted and four feature selection methods were used to select robust features. The selected features were used to build five machine learning classifiers, and 20 (four feature selection methods × five machine learning classifiers) predictive models for the screening of poor responders were constructed. The predictive models were evaluated according to the area under the curve (AUC), F1 score, accuracy, sensitivity, and specificity. Results Eighty percent of all predictive models constructed achieved an AUC of more than 0.70. A predictive model using a support vector machine classifier with the minimum redundancy maximum relevance (mRMR) selection method followed by the least absolute shrinkage and selection operator (LASSO) selection method showed superior prediction performance, with an AUC of 0.923, an F1 score of 88.14%, and accuracy of 91.03%. The predictive performance of the constructed models was not improved by ComBat compensation. Conclusions In rectal cancer patients who underwent neoadjuvant chemoradiotherapy, machine learning classifiers with radiomics features extracted from multiparametric MRI were able to accurately discriminate poor responders from good responders. The techniques should provide additional information to guide patient-tailored treatment.

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“…While overtreatment may represent a considerable risk, undertreatment caused by inaccurately described nodal negativity might be even worse. Several analyses have shown rates of pathologically confirmed positive nodes in 20–30% of patients initially staged as cT3cN0 on EUS and MRI with or without neoadjuvant treatment [ 47 , 48 , 49 ]. In patients treated by surgery alone, understaging seemed more frequent than overstaging [ 47 ], thus making undertreatment more likely than overtreatment.…”

Section: Treatment Algorithmmentioning

confidence: 99%

“…Several analyses have shown rates of pathologically confirmed positive nodes in 20–30% of patients initially staged as cT3cN0 on EUS and MRI with or without neoadjuvant treatment [ 47 , 48 , 49 ]. In patients treated by surgery alone, understaging seemed more frequent than overstaging [ 47 ], thus making undertreatment more likely than overtreatment. While there is some evidence that MRI nodal staging accuracy can be improved by using more sophisticated MRI criteria [ 22 ], it remains an issue of treatment philosophy if a possibility of under- or overtreatment seems more harmful to the patient, which needs to be individually discussed.…”

Section: Treatment Algorithmmentioning

confidence: 99%

How We Treat Localized Rectal Cancer—An Institutional Paradigm for Total Neoadjuvant Therapy

Roeder

Gerum

Hecht

et al. 2022

Cancers

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Total neoadjuvant therapy (TNT)—the neoadjuvant employment of radiotherapy (RT) or chemoradiation (CRT) as well as chemotherapy (CHT) before surgery—may lead to increased pathological complete response (pCR) rates as well as a reduction in the risk of distant metastases in locally advanced rectal cancer. Furthermore, increased response rates may allow organ-sparing strategies in a growing number of patients with low rectal cancer and upfront immunotherapy has shown very promising early results in patients with microsatellite instability (MSI)-high/mismatch-repair-deficient (dMMR) tumors. Despite the lack of a generally accepted treatment standard, we strongly believe that existing data is sufficient to adopt the concept of TNT and immunotherapy in clinical practice. The treatment algorithm presented in the following is based on our interpretation of the current data and should serve as a practical guide for treating physicians—without any claim to general validity.

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Tumor stage in patients operated for rectal cancer: a comparison of the pre-operative MR and the resection specimen, with specific attention to the effect of neo-adjuvant radiotherapy

Cited by 4 publications

References 21 publications

Impacts of neoadjuvant therapy on the number of dissected lymph nodes in esophagogastric junction cancer patients

Impacts of neoadjuvant therapy on the number of dissected lymph nodes in esophagogastric junction cancer patients

Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients

How We Treat Localized Rectal Cancer—An Institutional Paradigm for Total Neoadjuvant Therapy

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