Short-Term Clinical and Oncological Outcome of Prolonging Operation Interval After Neoadjuvant Chemoradiotherapy for Locally Advanced Middle and Low Rectal Cancer

Magnetic resonance imaging radiomics-based prediction of severe inflammatory response in locally advanced rectal cancer patients after neoadjuvant radiochemotherapy

PURPOSE

To predict severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced rectal cancer (RC) patients using magnetic resonance imaging (MRI) radiomics models.

METHODS

This retrospective study included patients who underwent radical surgery for RC cancer after neoadjuvant radiochemotherapy between July 2017 and December 2019 at XXX Hospital. MRI radiomics features were extracted from T2WI images before (pre-nRCT-RF) and after (post-nRCT-RF) neoadjuvant radiochemotherapy, and the variation of radiomics features before and after neoadjuvant radiochemotherapy (delta-RF) were calculated. Eight, eight, and five most relevant features were identified for pre-nRCT-RF, post-nRCT-RF, and delta-RF, respectively.

RESULTS

Eighty-six patients were included and randomized 3:1 to the training and test set (n = 65 and n = 21, respectively). The prediction model based on delta-RF had areas under the curve (AUCs) of 0.80 and 0.85 in the training and test set, respectively. A higher rate of difficult operations was observed in patients with severe inflammation (65.5% vs. 42.9%, P = 0.045).

CONCLUSION

The prediction model based on MRI delta-RF may be a useful tool for predicting severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced RC patients.

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

A New Nomogram for Predicting the Postoperative Overall Survival in Patients with Middle-Aged and Elderly Rectal Cancer: A Single Center Retrospective Study in Chinese Population

Purpose

Patients with middle-aged and elderly rectal cancer (MERC) usually have poor prognosis after surgery. This study aimed to develop a nomogram to achieve individualized prediction of overall survival (OS) in patients with MERC and to guide follow-up and subsequent diagnosis and treatment plans.

Patients and Methods

A total of 349 patients were randomly assigned to the training and validation cohorts in a 7:3 ratio. Multivariate Cox regression analysis was performed using the results of univariate Cox regression analysis to confirm independent prognostic factors of OS. Thereafter, the nomogram was built using the “rms” package. Subsequently, discriminative ability and calibration of the nomogram were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Integrated discrimination improvement (IDI), net reclassification improvement (NRI), and the area under the ROC curves (AUC) were compared between the nomogram and the tumor-node-metastasis (TNM) staging system (8th edition). Finally, we established a predictive model to assess the survival benefit of patients with MERC by calculating nomogram scores for each patient.

Results

Six variables were identified as independent prognostic factors and included in the nomogram: smoking history, family history, hematochezia, tumor size, N stage, and M stage. Based on these factors, we successfully constructed a nomogram and evaluated its discriminative and predictive abilities using ROC curves, calibration curves, and DCA. ROC curves, IDI, and NRI showed that the nomogram had outstanding clinical utility compared with the TNM staging system (8th edition) for OS prediction. The predictive model successfully distinguished between high-, medium-, and low-risk MERC patients.

Conclusion

Our nomogram provided a more satisfactory survival prediction ability than the TNM staging system (8th edition) for MERC patients. In addition, the nomogram was able to accurately categorize patients into different risk groups after surgery.

Timing to achieve the best recurrence-free survival after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: experience in a large-volume center in China

AIM

To identify the optimal interval from the end of neoadjuvant chemoradiotherapy to surgery (CRT-surgery interval) based on long-term oncological outcome of locally advanced rectal cancer (LARC).

METHODS

Retrospective data analysis is reported from patients diagnosed with cT3 or T4 or TxN+ rectal cancer who underwent neoadjuvant treatment and curative-intent surgery between January 2010 and December 2018. With a priority focus on the effect of interval on oncological prognosis, we used recurrence-free survival (RFS) as the primary endpoint to determine the best cutoff point of time intervals. Then, the short-term and long-term outcomes of patients from longer and shorter interval groups were compared.

RESULTS

Data from 910 patients were analyzed, with 185 patients who achieved pCR (20.3%). The trend for increased rates of pCR for groups with a prolonged time interval was not observed (P = 0.808). X-tile determined a cutoff value of 10.5 weeks, and the population was divided into longer (> 10 weeks) and shorter (≤ 10 weeks) interval groups. The shorter interval was associated with a higher wound infection rate (4.7% vs. 1.1%, P = 0.031), but other postoperative complications did not differ between the groups. The 5-year RFS rate was significantly higher in patients in a longer group than those in the shorter weeks group (86.8% vs. 77.8%, P = 0.016). The 5-year OS rates between groups were similar (84.1% vs. 82.5%, P = 0.257). Local recurrence and lung metastases rates were higher in shorter interval group than those of longer group (local recurrence rate: 1.7% vs. 5.1%, P = 0.049; lung metastases rate: 5.7% vs. 10.7%, P = 0.047). Cox multivariate regression analysis confirmed the CRT-surgery interval (HR = 0.599, P = 0.045) to be an independent prognostic factor of RFS.

CONCLUSION

This study is the first, to the best of our knowledge, to define the optimal CRT-surgery interval based on RFS as the primary endpoint. Prolonging the waiting period to 10 weeks after the completion of CRT with additional chemotherapy cycles during the interval period might be a promising option to improve oncological survival in LARC patients treated with CRT and TME without compromising the surgical safety. Further randomized controlled trials investigating this are warranted to prove a clearly causality.

Prediction of cancer-specific survival and overall survival in middle-aged and older patients with rectal adenocarcinoma using a nomogram model

•

Summarise the established knowledge on this subject.1

Middle-aged and older patients are at high risk of rectal adenocarcinoma; however, studies comprehensively analysing its predictors and the construction of visual nomogram models are limited.

2

Most studies that reported on the prediction of colorectal cancer-related survival models had limited samples and included data from a single centre. The included predictors were limited, or the evaluation indicators were not easy to obtain, greatly limiting clinical application.

3

With the advancement of medical care, the clinical outcomes of patients with rectal adenocarcinoma have changed. Therefore, new, more comprehensive, and practical indicators are required for constructing clinical prediction models to effectively determine the prognosis of patients.

•

What are the significant and/or new findings of this study?1

We included demographic and clinicopathological data from thousands of middle-aged and elderly patients with rectal adenocarcinoma to find relevant prognostic factors. New cut-offs were developed and used for the construction of nomograms.

2

The nomogram constructed this time has excellent predictive ability and clinical decision-making ability, and has good clinical practicability.

3

The nomogram survival prediction model constructed this time can effectively help evaluate the prognosis of middle-aged and elderly patients with rectal adenocarcinoma and guide the selection of clinical treatment measures.

Objective

To develop a new nomogram tool for predicting survival in middle-aged and elderly patients with rectal adenocarcinoma.

Methods

A total of 6,116 patients were randomly assigned in a 7:3 ratio to training and validation cohorts. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS) in the training set, and two nomogram prognostic models were constructed. The validity, accuracy, discrimination, predictive ability, and clinical utility of the models were assessed based on the concordance index (C-index), area under the receiver operating characteristics (ROC) curve, time-dependent area under the ROC curve (AUC), Kaplan-Meier survival curve, and decision curve analyses.

Results

Predictors of OS and CSS were identified, and nomograms were successfully constructed. The calibration discrimination for both the OS and CSS nomogram prediction models was good (C-index: 0.763 and 0.787, respectively). The AUC showed excellent predictive performance, and the calibration curve exhibited significant predictive power for both nomograms. The time-dependent AUC showed that the predictive ability of the predictor-based nomogram was better than that of the TNM stage. The nomograms successfully discriminated high-, medium-, and low-risk patients for all-cause and cancer-specific mortality. The decision curve demonstrated that the nomograms are useful with respect to good decision power.

Conclusion

Our nomogram survival prediction models may aid in evaluating the prognosis of middle-aged and older patients with rectal adenocarcinoma and guiding the selection of the clinical treatment measures.