Predictive Factors for Pathologic Complete Response Following Neoadjuvant Chemoradiotherapy for Rectal Cancer

Can Pretreatment MRI and Planning CT Radiomics Improve Prediction of Complete Pathological Response in Locally Advanced Rectal Cancer Following Neoadjuvant Treatment?

OBJECTIVE(S)

The treatment response to neoadjuvant chemoradiation (nCRT) differs largely in individuals treated for rectal cancer. In this study, we investigated the role of radiomics to predict the pathological response in locally advanced rectal cancers at different treatment time points: (1) before the start of any treatment using baseline T2-weighted MRI (T2W-MR) and (2) at the start of radiation treatment using planning CT.

METHODS

Patients on nCRT followed by surgery between June 2017 to December 2019 were included in the study. Histopathological tumour response grading (TRG) was used for classification, and gross tumour volume was defined by the radiation oncologists. Following resampling, 100 and 103 pyradiomic features were extracted from T2W-MR and planning CT images, respectively. Synthetic minority oversampling technique (SMOTE) was used to address class imbalance. Four machine learning classifiers built clinical, radiomic, and merged models. Model performances were evaluated on a held-out test dataset following 3-fold cross-validation using area under the receiver operator characteristic curves (AUC) with bootstrap 95% confidence intervals.

RESULTS

One hundred and fifty patients were included; 58/150 with TRG 1 were classified as complete responders, and rest were incomplete responders (IR). Clinical models performed better (AUC = 0.68) compared to radiomics models (AUC = 0.62). Overall, the clinical + T2W-MR model showed best performance (AUC = 0.72) in predicting the pathological response prior to therapy. Clinical + Planning CT-merged models could only achieve the highest AUC of 0.66.

CONCLUSION

Merging clinical and baseline T2W-MR radiomics enhances predicting pathological response in rectal cancer. Validation in larger cohorts is warranted, especially for watch and wait strategies.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer

BACKGROUND

Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide. Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer (LARC). Except for pathological examination after resection, it is not known exactly whether LARC patients have achieved pathological complete response (pCR) before surgery. To date, there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes.

AIM

To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC.

METHODS

Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed. Patients were categorized into pCR and non-pCR groups. Univariate analysis (using the χ² test or Fisher’s exact test) and logistic multivariate regression analysis were used to study clinical predictors affecting pCR. The 5-year disease-free survival (DFS) and overall survival (OS) rates were calculated using Kaplan-Meier analysis, and differences in survival curves were assessed with the log-rank test.

RESULTS

Univariate analysis showed that pretreatment carcinoembryonic antigen (CEA) level, lymphocyte-monocyte ratio (LMR), time interval between neoadjuvant therapy completion and total mesorectal excision, and tumor size were correlated with pCR. Multivariate results showed that CEA ≤ 5 ng/mL (P = 0.039), LMR > 2.73 (P = 0.023), and time interval > 10 wk (P = 0.039) were independent predictors for pCR. Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates (94.7% vs 59.7%, P = 0.002) and 5-year OS rates (95.8% vs 80.1%, P = 0.019) compared to the non-pCR group. Tumor deposits (TDs) were significantly correlated with shorter DFS (P = 0.002) and OS (P < 0.001).

CONCLUSION

Pretreatment CEA, LMR, and time interval contribute to predicting nCRT efficacy in LARC patients. Achieving pCR demonstrates longer DFS and OS. TDs correlate with poor prognosis.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer

BACKGROUND

Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide. Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer (LARC). Except for pathological examination after resection, it is not known exactly whether LARC patients have achieved pathological complete response (pCR) before surgery. To date, there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes.

AIM

To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC.

METHODS

Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed. Patients were categorized into pCR and non-pCR groups. Univariate analysis (using the χ 2 test or Fisher's exact test) and logistic multivariate regression analysis were used to study clinical predictors affecting pCR. The 5-year disease-free survival (DFS) and overall survival (OS) rates were calculated using Kaplan-Meier analysis, and differences in survival curves were assessed with the log-rank test.

RESULTS

Univariate analysis showed that pretreatment carcinoembryonic antigen (CEA) level, lymphocyte-monocyte ratio (LMR), time interval between neoadjuvant therapy completion and total mesorectal excision, and tumor size were correlated with pCR. Multivariate results showed that CEA ≤ 5 ng/mL (P = 0.039), LMR > 2.73 (P = 0.023), and time interval > 10 wk (P = 0.039) were independent predictors for pCR. Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates (94.7% vs 59.7%, P = 0.002) and 5-year OS rates (95.8% vs 80.1%, P = 0.019) compared to the non-pCR group. Tumor deposits (TDs) were significantly correlated with shorter DFS (P = 0.002) and OS (P < 0.001).

CONCLUSION

Pretreatment CEA, LMR, and time interval contribute to predicting nCRT efficacy in LARC patients. Achieving pCR demonstrates longer DFS and OS. TDs correlate with poor prognosis.

Characteristics of pathologic complete response for locally advanced rectal cancer

BACKGROUND

Neoadjuvant chemoradiation (NACRT) is the standard of care for locally advanced rectal cancers. The purpose of this study was to determine patient and tumor factors associated with a pathologic complete response (pCR).

METHODS

The National Surgical Quality Improvement Program proctectomy-targeted database was utilized to identify all patients from 2016 to 2020 who underwent NACRT followed by proctectomy with curative intent for T3-4N0-2 rectal cancers.

RESULTS

A total of 1891 patients were included, of which 253 (13.4%) demonstrated a pCR. Pretreatment N0 staging was associated with a higher rate of pCR (18.9%) when compared to N1 (6.7%) and N2 (6.7%) (p < 0.0001). Patients clinically staged at T3N0 had the highest rate of pCR (19.5%). Gender, age, race, weight, smoking status, and tumor height were not associated with pCR.

CONCLUSIONS

Patients with cN0 disease were more likely to experience a pCR compared to cN1-2 patients. Tumor height relative to anal verge or patient demographics were not associated with pCR.

Construction and Evaluation of Nomogram for Hematological Indicators to Predict Pathological Response after Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

OBJECTIVE

A retrospective study was conducted by developing prediction models to evaluate the association between hematological indexes, their changes during neoadjuvant chemoradiotherapy (NCRT), and tumor pathological response in patients with locally advanced rectal cancer.

METHODS

The clinical data of 202 patients who received NCRT and radical surgery in Sichuan Cancer Hospital were retrospectively analyzed. Univariate and logistic multivariate regression analyses were used to identify hematological indexes with predictive significance. The independent risk factors were imported into the R software, and a nomogram prediction model was developed. The bootstrap method and ROC curve were used to evaluate the discriminative degree of the model.

RESULTS

Univariate analysis demonstrated age, tumor diameter, preoperative T, distance from tumor to the anal verge, CEA before NCRT, preoperative CEA, lymphocyte changes, platelet changes, and pathology of rectal cancer after NCRT were associated. Multivariate analysis demonstrated that age, tumor distance from the anus, preoperative CEA, lymphocyte changes, and platelet changes were independent risk factors. The independent risk factors were imported into the R software to construct a nomogram model. The area under the ROC was 0.76, and the slope of the calibration curve of the nomogram was close to 1.

CONCLUSION

A low preoperative CEA level, a young age, a high tumor from the anal verge, the maintenance of circulating lymphocyte level, and a decreased platelet level after NCRT are important factors for favorable outcomes after NCRT. Developing a nomogram prediction model with good discrimination and consistency can provide some guidance for predicting pathological responses after NCRT.

Promises and Challenges of Predictive Blood Biomarkers for Locally Advanced Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy

The treatment of locally advanced rectal cancer (LARC) requires a multimodal approach combining neoadjuvant radiotherapy or chemoradiotherapy (CRT) and surgery. Predicting tumor response to CRT can guide clinical decision making and improve patient care while avoiding unnecessary toxicity and morbidity. Circulating biomarkers offer both the advantage to be easily accessed and followed over time. In recent years, biomarkers such as proteins, blood cells, or nucleic acids have been investigated for their predictive value in oncology. We conducted a comprehensive literature review with the aim to summarize the status of circulating biomarkers predicting response to CRT in LARC. Forty-nine publications, of which forty-seven full-text articles, one review and one systematic review, were retrieved. These studies evaluated circulating markers (CEA and CA 19-9), inflammatory biomarkers (CRP, albumin, and lymphocytes), hematologic markers (hemoglobin and thrombocytes), lipids and circulating nucleic acids (cell-free DNA [cfDNA], circulating tumor DNA [ctDNA], and microRNA [miRNA]). Post-CRT CEA levels had the most consistent association with tumor response, while cfDNA integrity index, MGMT promoter methylation, ERCC-1, miRNAs, and miRNA-related SNPs were identified as potential predictive markers. Although circulating biomarkers hold great promise, inconsistent results, low statistical power, and low specificity and sensibility prevent them from reliably predicting tumor response following CRT. Validation and standardization of methods and technologies are further required to confirm results.

[Complete response after neoadjuvant therapy : How certain is the pathology?]

Histopathologic evaluation of tumors after neoadjuvant therapy is performed by tumor regression grading (TRG) systems, which reflect the proportion of vital residual primary tumor in relation to the previous total tumor. The World Health Organization (WHO) tumor grading is replaced by TRG in tumor classification. The histopathological work-up of a tumor is based on the criteria of the TNM classification even after neoadjuvant therapy. A uniform TRG does not exist. For various tumors TRGs based on the tumor entity have been established, consisting of a 3-stage or 5‑stage grading system. Complete histopathological tumor regression is only present if no vital tumor cells are detectable in the histopathological examination of the primary surgical specimens (primary tumor and accompanying locoregional lymph nodes) and there are no distant metastases.

Can histologic features predict neoadjuvant therapy response in rectal adenocarcinoma?

Current standard therapy for locally advanced rectal cancer (LARC) is neoadjuvant therapy followed by surgical resection; however, treatment response is variable among patients. This study aimed to identify histologic features that predict tumor response. This retrospective study included 105 patients with LARC, all of whom underwent biopsy followed by neoadjuvant therapy and subsequent surgical resection. Each patient's initial biopsy was evaluated for tumor grade, tumor budding, intraepithelial lymphocytes, intraepithelial neutrophils, desmoplasia, apoptosis, adjacent stromal lymphocytes, signet ring cells, mucinous features, tumoral Paneth cells, dirty necrosis, microscopic ulceration, and prominent lymphoid aggregates. These histologic features, along with patient age at diagnosis and tumor microsatellite status, were compared to tumor regression grades from the respective resection specimens. No histologic factors in tumor biopsies predictive of treatment response in post-therapy resection specimens were identified. Histologic features in pre-therapy biopsy samples of LARC do not predict subsequent response to neoadjuvant therapy. Effective and reliable methods to predict response to neoadjuvant therapy in rectal cancer remain elusive.