Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation

A dynamic nomogram for predicting pathologic complete response to neoadjuvant chemotherapy in locally advanced rectal cancer

AIM

To explore the clinical factors associated with pathologic complete response (pCR) for locally advanced rectal cancer (LARC) patients treated with neoadjuvant chemoradiotherapy (nCRT) and develop a web-based dynamic nomogram.

METHODS

Retrospective analysis of patients with examination confirmed LARC from 2011 to 2022. Patients from the Union Hospital of Fujian Medical University were included as the training cohort (n = 1579) and Zhangzhou Hospital of Fujian Medical University as the external validation cohort (n = 246).

RESULTS

In the training cohort, after nCRT, 350 (22.2%) patients achieved pCR. More stomas were avoided in pCR patients (73.9% vs. 69.7%, p = 0.043). After a median follow-up time of 47.7 months (IQR 2-145) shown OS (5-year: 93.7% vs. 81.0%, HR = 0.310, 95%CI: 0.189-0.510, p < 0.001) and DFS (5-year: 91.2% vs. 75.0%, HR = 0.204, 95%CI: 0.216-0.484, p < 0.001) were significantly better among patients with pCR than non-pCR. Multivariable Logistic analysis shown pCR was significantly associated with Pre-CRT CEA (HR = 0.944, 95%CI: 0.921-0.968; p < 0.001), histopathology (HR = 4.608, 95%CI: 2.625-8.089; p < 0.001), Pre-CRT T stage (HR = 0.793, 95%CI: 0.634-0.993; p = 0.043), Pre-CRT N stage (HR = 0.727, 95%CI: 0.606-0.873; p = 0.001), Pre-CRT MRI EMVI (HR = 0.352, 95%CI: 0.262-0.473; p < 0.001), total neoadjuvant therapy (HR = 2.264, 95%CI: 1.280-4.004; p = 0.005). Meanwhile, the online version of the nomogram established in this study was publicized on an open-access website (URL: https://pcrpredict.shinyapps.io/LARC2/). The model predicted accuracy with a C-index of 0.73 (95% CI: 0.70-0.75), with an average C-index of 0.73 for the internal cross validation and 0.78 (95% CI: 0.72-0.83) for the external validation cohort, showing excellent model accuracy. Delong test results showed the model has an important gain value for clinical characteristics to predict pCR in rectal cancer.

CONCLUSIONS

Patients with pCR had a better prognosis, including OS and DFS, and were independently associated with Pre-CRT CEA, histopathology, Pre-CRT T/N stage, Pre-CRT MRI EMVI, and TNT. A web-based dynamic nomogram was successfully established for clinical use at any time.

Radiomics Signature Based on Support Vector Machines for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

The objective of this study was to evaluate the discriminative capabilities of radiomics signatures derived from three distinct machine learning algorithms and to identify a robust radiomics signature capable of predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy in patients diagnosed with locally advanced rectal cancer (LARC). In a retrospective study, 211 LARC patients were consecutively enrolled and divided into a training cohort (n = 148) and a validation cohort (n = 63). From pretreatment contrast-enhanced planning CT images, a total of 851 radiomics features were extracted. Feature selection and radiomics score (Radscore) construction were performed using three different machine learning methods: least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine (SVM). The SVM-derived Radscore demonstrated a strong correlation with the pCR status, yielding area under the receiver operating characteristic curves (AUCs) of 0.880 and 0.830 in the training and validation cohorts, respectively, outperforming the RF and LASSO methods. Based on this, a nomogram was developed by combining the SVM-based Radscore with clinical indicators to predict pCR after neoadjuvant chemoradiotherapy. The nomogram exhibited superior predictive power, achieving AUCs of 0.910 and 0.866 in the training and validation cohorts, respectively. Calibration curves and decision curve analyses confirmed its appropriateness. The SVM-based Radscore demonstrated promising performance in predicting pCR for LARC patients. The machine learning-driven nomogram, which integrates the Radscore and clinical indicators, represents a valuable tool for predicting pCR in LARC patients.

Baseline and early digital [ 18 F]FDG PET/CT and multiparametric MRI contain promising features to predict response to neoadjuvant therapy in locally advanced rectal cancer patients: a pilot study

OBJECTIVE

In this pilot study, we investigated the feasibility of response prediction using digital [ 18 F]FDG PET/computed tomography (CT) and multiparametric MRI before, during, and after neoadjuvant chemoradiation therapy in locally advanced rectal cancer (LARC) patients and aimed to select the most promising imaging modalities and timepoints for further investigation in a larger trial.

METHODS

Rectal cancer patients scheduled to undergo neoadjuvant chemoradiation therapy were prospectively included in this trial, and underwent multiparametric MRI and [ 18 F]FDG PET/CT before, 2 weeks into, and 6-8 weeks after chemoradiation therapy. Two groups were created based on pathological tumor regression grade, that is, good responders (TRG1-2) and poor responders (TRG3-5). Using binary logistic regression analysis with a cutoff value of P  ≤ 0.2, promising predictive features for response were selected.

RESULTS

Nineteen patients were included. Of these, 5 were good responders, and 14 were poor responders. Patient characteristics of these groups were similar at baseline. Fifty-seven features were extracted, of which 13 were found to be promising predictors of response. Baseline [T2: volume, diffusion-weighted imaging (DWI): apparent diffusion coefficient (ADC) mean, DWI: difference entropy], early response (T2: volume change, DWI: ADC mean change) and end-of-treatment presurgical evaluation MRI (T2: gray level nonuniformity, DWI: inverse difference normalized, DWI: gray level nonuniformity normalized), as well as baseline (metabolic tumor volume, total lesion glycolysis) and early response PET/CT (Δ maximum standardized uptake value, Δ peak standardized uptake value corrected for lean body mass), were promising features.

CONCLUSION

Both multiparametric MRI and [ 18 F]FDG PET/CT contain promising imaging features to predict response to neoadjuvant chemoradiotherapy in LARC patients. A future larger trial should investigate baseline, early response, and end-of-treatment presurgical evaluation MRI and baseline and early response PET/CT.

Development and Validation of Nomograms to Predict Survival in Patients Undergoing Complete Cytoreduction and Hyperthermic Intraperitoneal Chemotherapy for Pseudomyxoma Peritonei of Appendiceal Origin

Importance

Pseudomyxoma peritoni, a rare condition characterized by mucinous ascites and peritoneal deposits, mainly originates from a ruptured mucinous appendix tumor and is considered an indolent disease but can progress and become fatal. Optimal treatment to improve cure and survival rates involves complete cytoreductive surgery (CCRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Accurate predictive models are useful in supporting and informing treatment strategies and stratifying patient follow-up.

Objective

To evaluate the prognostic significance of clinically important variables and generate validated nomograms to predict overall (OS) and disease-free survival (DFS) following CCRS and hyperthermic intraperitoneal HIPEC for pseudomyxoma peritonei (PMP) of appendiceal origin.

Design, Setting, and Participants

This retrospective study used prospectively collected data on patients who had cytoreductive surgery (CRS) and HIPEC in a single institution between 1994 and 2018. The cohort was randomly allocated into development (70%) and validation (30%) sets. Univariate and multivariate analyses were performed with Cox proportional hazards regression.

Main Outcomes and Measures

A prediction model was developed with significant prognostic factors identified by multivariate analysis. The model's prognostic performance was evaluated with the concordance index (C index). The nomogram was calibrated by comparing the predicted and observed probabilities.

Results

Of 2637 CRS and HIPEC operations, 1102 patients (female, 64.4%; median age [IQR], 57.0 [48.0-66.0] years) (41.8%) had CCRS for PMP of appendiceal origin. Elevated tumor markers, peritoneal carcinomatosis index, gastrectomy, and tumor grade were independent predictive factors for DFS. Gender, age, elevated tumor makers, peritoneal carcinomatosis index, and tumor grade influenced OS. The nomograms were generated with respective prognostic factors. The nomograms showed good performance in predicting survival. Median OS of the cohort was 16.5 years (95% CI, 13.7-19.2) with a 5-year probability of survival of 80.2%. The median DFS was 10.3 years (95% CI, 7.2- 13.3) and the 5-year probability of recurrence-free survival was 60.5%.

Conclusions and Relevance

Clinically important independent predictors for survival and recurrence were selected to develop the nomograms for OS and DFS. These 2 nomograms are user friendly and useful tools for patient management with clinical trial design applications.

International consensus recommendations on key outcome measures for organ preservation after (chemo)radiotherapy in patients with rectal cancer

Multimodal treatment strategies for patients with rectal cancer are increasingly including the possibility of organ preservation, through nonoperative management or local excision. Organ preservation strategies can enable patients with a complete response or near-complete clinical responses after radiotherapy with or without concomitant chemotherapy to safely avoid the morbidities associated with radical surgery, and thus to maintain anorectal function and quality of life. However, standardization of the key outcome measures of organ preservation strategies is currently lacking; this includes a lack of consensus of the optimal definitions and selection of primary end points according to the trial phase and design; the optimal time points for response assessment; response-based decision-making; follow-up schedules; use of specific anorectal function tests; and quality of life and patient-reported outcomes. Thus, a consensus statement on outcome measures is necessary to ensure consistency and facilitate more accurate comparisons of data from ongoing and future trials. Here, we have convened an international group of experts with extensive experience in the management of patients with rectal cancer, including organ preservation approaches, and used a Delphi process to establish the first international consensus recommendations for key outcome measures of organ preservation, in an attempt to standardize the reporting of data from both trials and routine practice in this emerging area.

Computed tomography-derived biomarker for predicting the treatment response to neoadjuvant chemoradiotherapy of rectal cancer

BACKGROUND

Malignant tumor essentially implies structural heterogeneity. Analysis of medical imaging can quantify this structural heterogeneity, which can be a new biomarker. This study aimed to evaluate the usefulness of texture analysis of computed tomography (CT) imaging as a biomarker for predicting the therapeutic response of neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer.

METHODS

We enrolled 76 patients with rectal cancer who underwent curative surgery after nCRT. Texture analyses (Fractal analysis and Histogram analysis) were applied to contrast-enhanced CT images, and fractal dimension (FD), skewness, and kurtosis of the tumor were calculated. These CT-derived parameters were compared with the therapeutic response and prognosis.

RESULTS

Forty-six of 76 patients were diagnosed as clinical responders after nCRT. Kurtosis was significantly higher in the responders group than in the non-responders group (4.17 ± 4.16 vs. 2.62 ± 3.19, p = 0.04). Nine of 76 patients were diagnosed with pathological complete response (pCR) after surgery. FD of the pCR group was significantly lower than that of the non-pCR group (0.90 ± 0.12 vs. 1.01 ± 0.12, p = 0.009). The area under the receiver-operating characteristics curve of tumor FD for predicting pCR was 0.77, and the optimal cut-off value was 0.84 (accuracy; 93.4%). Furthermore, patients with lower FD tumors tended to show better relapse-free survival and disease-specific survival than those with higher FD tumors (5-year, 80.8 vs. 66.6%, 94.4 vs. 80.2%, respectively), although it was not statistically significant (p = 0.14, 0.11).

CONCLUSIONS

CT-derived texture parameters could be potential biomarkers for predicting the therapeutic response of rectal cancer.

Watch-and-wait strategy in rectal cancer: Is there a tumour size limit? Results from two pooled prospective studies

BACKGROUND

Frequency and predictive factors for a clinical complete response (cCR) in unselected patients are unclear.

MATERIAL AND METHODS

Two prospective observational studies were designed and pooled to explore predictive factors for cCR. Both studies evaluated the watch-and-wait strategy in consecutive patients; the first single-institutional study in elderly with a small tumour, the second multi-institutional study in all the patients receiving standard of care preoperative radiotherapy.

RESULTS

Four hundred and ninety patients were analysed. Short-course radiotherapy alone, or with consolidation chemotherapy or chemoradiation was given to 40.6%, 40.2% and 19.2% of the patients, respectively. The median interval from the radiation start to the first tumour response assessment was 10.2 weeks for short-course radiation and 13.2 weeks for chemoradiation. Seventy-three patients had cCR and 71 underwent w&w with the median follow-up of 24 months. The regrowth rate was 26.8%. cCR rate was 39.0% for low-risk cancer (cT1-2N0), 16.8% for intermediate-risk (cT3 with unthreatened mesorectal fascia [MRF-] or cT2N+) and 5.4% for high-risk (cT4 or MRF+). In the multivariable analysis, tumour volume (or tumour length and circumferential extent) and cN status were significant predictors for cCR. In circular cancers or with a length ≥7 cm (n = 184), cCR rate was only 2.7%, sustained cCR 1.6% and the sensitivity of cCR diagnosis 23.1%. None of 27 patients with a tumour larger than 120 cm³ achieved cCR.

CONCLUSIONS

Considering watch-and-wait strategy is questionable in patients with circular tumours or with tumour length ≥7 cm.

Nomogram predicting cancer-specific mortality in early-onset rectal cancer: a competing risk analysis

BACKGROUND

The incidence of rectal cancer has meaningfully increased in young patients. However, quantitative evaluation for the competing data of early-onset rectal cancer is lacking. So, we performed a competing risk analysis to calculate the cumulative incidence of death for patients with early-onset rectal cancer and developed a nomogram to predict the probability of cancer-specific mortality for these patients.

METHODS

We abstracted data of patients with early-onset rectal cancer between 2004 and 2016 by using the Surveillance, Epidemiology, and End Results program database. The cumulative incidence function was used to calculate the crude cancer-specific mortality of early-onset rectal cancer. Fine and Gray's proportional sub-distribution hazard model was adopted to explore the risk factors of cancer-specific death. Then, we establish a nomogram to predict their 3-, 5-, and 10-year probabilities.

RESULTS

We identified 9917 patients with early-onset rectal cancer, and they were randomly divided into training (n = 6941) and validation (n = 2976) cohorts. In the training cohort, the 3-, 5-, and 10-year cumulative incidences of cancer-specific death after diagnosis for early-onset rectal cancer were 11.4%, 19.9%, and 28.8%, respectively. Fine and Gray's model showed that sex, race, marital status, histology, T stage, N stage, M stage, examined lymph nodes, and pretreatment carcinoembryonic antigen were independently associated with cancer-specific mortality. Such factors were selected to develop a prognostic nomogram.

CONCLUSION

The competing risk nomogram has an ideal performance for predictive cancer-specific mortality in early-onset rectal cancer.

Nomogram for prediction of pathologic complete remission using biomarker expression and endoscopic finding after preoperative chemoradiotherapy in rectal cancer

Objective

The aim of this study is to develop a nomogram for prediction of pathologic complete remission (pCR) after preoperative chemoradiotherapy (CRT) for rectal cancer.

Methods

mRNA expression levels of seven molecular markers [p53, p21, Ki-67, vascular endothelial growth factor (VEGF), CD133, CD24, CD44] were measured by reverse transcriptase polymerase chain reaction (RT-PCR) in 120 rectal cancers. Endoscopic findings of clinical complete remission (cCR) and biologic variables were used to construct nomogram in the training group (n=80), which was validated in the validation group (n=40).

Results

mRNA expression levels of four markers (p53, p21, Ki67, CD133) correlated with pCR (24/80, 30.0%) in the training group. Low expression of p53 and/or high expression of p21, Ki67 and CD133 showed greater pCR rate. pCR was shown in 18 (69.2%) of 26 cases showing endoscopic cCR in the training group. Higher pCR rate was demonstrated in lower tumor location than middle tumor (19/49, 38.8% vs. 5/31, 16.1%). A nomogram for prediction of pCR was developed from the multivariate prediction model using these six variables, which showed good discrimination ability in the training group [area under the curve (AUC)=0.945] and validation group (AUC=0.922). The calibration plot showed good agreement between actual and predicted pCR in both patient groups.

Conclusions

Nomogram for assessment of pCR can be useful for making treatment decisions after CRT according to predicted responses.

Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer

BACKGROUND

Total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT) is recommended in the latest treatment of locally advanced rectal cancer (LARC).

OBJECTIVE

To predict whether patients with LARC can achieve pathologic complete response (pCR), comparing MRI-based radiomics between before and after neoadjuvant radiotherapy (nRT) was performed.

METHODS

One hundred and sixty-five MRI-based radiomics features in axial T2-weighted images were obtained quantitatively from Imaging Biomarker Explorer Software. The specific features of conventional and developing radiomics were selected with the analysis of least absolute shrinkage and selection operator logistic regression, of which the predictive performance was analyzed with receiver operating curve and calibration curve, and applied to an independent cohort.

RESULTS

One hundred and thirty-one target patients were enrolled in the present study. A radiomics signature founded on seven radiomics features was generated in the primary cohort. A remarkable difference about Rad-score between pCR and non-pCR group occurred in both of primary (P < .001) or validation cohorts (P < .001). The value of area under the curves was 0.92 (95% CI, 0.86-0.99) and 0.87 (95% CI, 0.74-1.00) in the primary and validation cohorts, respectively. The Rad-score (OR = 23.581; P < .001) from multivariate logistic regression analysis was significant as an independent factor of pCR.

CONCLUSION

Our predictive model based on radiomics features was an independent predictor for pCR in LARC and could be a candidate in clinical practice.

Emerging trends in the treatment of rectal cancer

The conventional treatment for cT3-T4 or node-positive clinically resectable rectal cancer is long course preoperative chemoradiation followed by surgery and postoperative adjuvant chemotherapy. Disadvantages of this approach include possible overtreatment of patients, 6 weeks of daily radiation treatment, and undetected metastatic disease. There are a number of emerging trends which are changing this approach to treatment. Selected topics included in this manuscript include the selective use of pelvic radiation, the role of radiation for a positive radial margin, the interval between radiation and surgery, non-operative management, new chemoradiation regimens, short vs. long course radiation, and the role of postoperative adjuvant chemotherapy.

The 2017 Assisi Think Tank Meeting on rectal cancer: A positioning paper

BACKGROUND AND PURPOSES

To describe current practice in the management of rectal cancer, to identify uncertainties that usually arise in the multidisciplinary team (MDT)'s discussions ('grey zones') and propose next generation studies which may provide answers to them.

MATERIALS AND METHODS

A questionnaire on the areas of controversy in managing T2, T3 and T4 rectal cancer was drawn up and distributed to the Rectal-Assisi Think Tank Meeting (ATTM) Expert European Board. Less than 70% agreement on a treatment option was indicated as uncertainty and selected as a 'grey zone'. Topics with large disagreement were selected by the task force group for discussion at the Rectal-ATTM.

RESULTS

The controversial clinical issues that had been identified within cT2-cT3-cT4 needed further investigation. The discussions focused on the role of (1) neoadjuvant therapy and organ preservation on cT2-3a low-middle rectal cancer; (2) neoadjuvant therapy in cT3 low rectal cancer without high risk features; (3) total neoadjuvant therapy, radiotherapy boost and the best chemo-radiotherapy schedule in T4 tumors. A description of each area of investigation and trial proposals are reported.

CONCLUSION

The meeting successfully identified 'grey zones' and, in the light of new evidence, proposed clinical trials for treatment of early, intermediate and advanced stage rectal cancer.

Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing

Quantitative imaging features (radiomics) extracted from apparent diffusion coefficient (ADC) maps of rectal cancer patients can provide additional information to support treatment decision. Most available radiomic computational packages allow extraction of hundreds to thousands of features. However, two major factors can influence the reproducibility of radiomic features: interobserver variability, and imaging filtering applied prior to features extraction. In this exploratory study we seek to determine to what extent various commonly-used features are reproducible with regards to the mentioned factors using ADC maps from two different clinics (56 patients). Features derived from intensity distribution histograms are less sensitive to manual tumour delineation differences, noise in ADC images, pixel size resampling and intensity discretization. Shape features appear to be strongly affected by delineation quality. On the whole, textural features appear to be poorly or moderately reproducible with respect to the image pre-processing perturbations we reproduced.

Magnetic Resonance, Vendor-independent, Intensity Histogram Analysis Predicting Pathologic Complete Response After Radiochemotherapy of Rectal Cancer

PURPOSE

The objective of this study is finding an intensity based histogram (IBH) signature to predict pathologic complete response (pCR) probability using only pre-treatment magnetic resonance (MR) and validate it externally in order to create a workflow for the external validation of an MR IBH signature and to apply the model out of the environment where it has been tuned. The impact of pCR and the final predictors on the survival outcome were also evaluated.

METHODS AND MATERIALS

Three centers using different MR scanners were involved in this retrospective study. The first center recruited 162 patients for model training, and the second and third centers provided 34 plus 25 patients for external validation. Patients provided written consent. Accrual period was from May 2008 to December 2014. After surgery pathologic response was defined. T2-weighted MR scans acquired before chemoradiation therapy (CRT) were used for analysis addressed on primary lesions. Images were pre-processed using Laplacian of Gaussian (LoG) filter with multiple σ, and first order intensity histogram-based features (kurtosis, skewness, and entropy) were extracted. Features selection was performed using Mann-Whitney test. Tumor staging (cT, cN) was added to build a logistic regression model and predict pCR. Model performance was evaluated with internal and external validation using area under the curve (AUC) of the receiver operator characteristic (ROC) and calibration with Hosmer-Lemeshow test. The linear cross-correlation matrix (Pearson's coefficient) and the variance inflation factor (VIF) were used to check the correlation and the co-linearity among the final predictors. The amount of the information added through the radiomics features was estimated by using the DeLong's test, and the impact of pCR and the final predictors on survival outcomes were evaluated through the Kaplan-Meier curves by using the log-rank test and the multivariate Cox model.

RESULTS

Candidate-to-analysis features were skewness (σ = 0.485, P value = .01) and entropy (σ = 0.344, P value < .05). Logistic regression analysis showed as significant covariates cT (P value < .01), skewness-σ = 0.485 (P value = .01), and entropy-σ = 0.344 (P value < .05). Model AUCs were 0.73 (internal) and 0.75 (external).

CONCLUSIONS

This MR-based, vendor-independent model can be helpful for predicting pCR probability in locally advanced rectal cancer (LARC) patients only using pre-treatment imaging.

A nomogram for predicting survival of patients with locally advanced pancreatic cancer treated with chemoradiotherapy

BACKGROUND

We developed a nomogram for predicting survival of patients with locally advanced pancreatic cancer (LAPC) after concurrent chemoradiotherapy (CRT) using ¹⁸F-flurodeoxyglucose-positron emission tomography (FDG-PET) parameters and CA 19-9 levels.

METHODS

Based on 426 patients with LAPC who received concurrent CRT between 2004 and 2015, we investigated significant prognostic factors for survival to build a nomogram, including the maximum standardized uptake value (SUV_max) and CA 19-9 levels. Predictive accuracy and discriminative ability were then measured.

RESULTS

Median progression-free survival and overall survival (OS) were 9.4 and 15.4 months, respectively, at a median 15-month follow-up. High-dose radiation (EQD2, ≥61 Gy), initial SUV_max <3.5 and CA 19-9 ≤400 U/mL, and surgical resection after CRT were significantly related to prolonged OS by multivariate analysis (p < 0.05). A nomogram model for OS was established and showed good calibration and acceptable discrimination (c-index 0.656). Using the nomogram, 3 different prognosis groups could be identified with a median OS of 25, 15, and 11 months (p < 0.001).

CONCLUSION

A nomogram was developed with high-dose radiation (EQD2, ≥61 Gy), initial SUV_max <3.5, CA 19-9 ≤400 U/mL, and surgical resection after CRT for patients with LAPC. This will help in clinical decision-making and in selecting patients for CRT.

Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

OBJECTIVES

To develop and validate a radiomics predictive model based on pre-treatment multiparameter magnetic resonance imaging (MRI) features and clinical features to predict a pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC) after receiving neoadjuvant chemoradiotherapy (CRT).

METHODS

One hundred and eighty-six consecutive patients with LARC (training dataset, n = 131; validation dataset, n = 55) were enrolled in our retrospective study. A total of 1,188 imaging features were extracted from pre-CRT T2-weighted (T2-w), contrast-enhanced T1-weighted (cT1-w) and ADC images for each patient. Three steps including least absolute shrinkage and selection operator (LASSO) regression were performed to select key features and build a radiomics signature. Combining clinical risk factors, a radiomics nomogram was constructed. The predictive performance was evaluated by receiver operator characteristic (ROC) curve analysis, and then assessed with respect to its calibration, discrimination and clinical usefulness.

RESULTS

Thirty-one of 186 patients (16.7%) achieved pCR. The radiomics signature derived from joint T2-w, ADC, and cT1-w images, comprising 12 selected features, was significantly associated with pCR status and showed better predictive performance than signatures derived from either of them alone in both datasets. The radiomics nomogram, incorporating the radiomics signature and MR-reported T-stages, also showed good discrimination, with areas under the ROC curves (AUCs) of 0.948 (95% CI, 0.907-0.989) and 0.966 (95% CI, 0.924-1.000), as well as good calibration in both datasets. Decision curve analysis confirmed its clinical usefulness.

CONCLUSIONS

This study demonstrated that the pre-treatment radiomics nomogram can predict pCR in patients with LARC and potentially guide treatments to select patients for a "wait-and-see" policy.

KEY POINTS

• Radiomics analysis of pre-CRT multiparameter MR images could predict pCR in patients with LARC. • Proposed radiomics signature from joint T2-w, ADC and cT1-w images showed better predictive performance than individual signatures. • Most of the clinical characteristics were unable to predict pCR.

Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer

The aim of this study was to propose a methodology to investigate the tumour heterogeneity and evaluate its ability to predict pathologically complete response (pCR) after chemo-radiotherapy (CRT) in locally advanced rectal cancer (LARC). This approach consisted in normalising the pixel intensities of the tumour and identifying the different sub-regions using an intensity-based thresholding. The spatial organisation of these subpopulations was quantified using the fractal dimension (FD). This approach was implemented in a radiomic workflow and applied to 198 T2-weighted pre-treatment magnetic resonance (MR) images of LARC patients. Three types of features were extracted from the gross tumour volume (GTV): morphological, statistical and fractal features. Feature selection was performed using the Wilcoxon test and a logistic regression model was calculated to predict the pCR probability after CRT. The model was elaborated considering the patients treated in two institutions: Fondazione Policlinico Universitario "Agostino Gemelli" of Rome (173 cases, training set) and University Medical Centre of Maastricht (25 cases, validation set). The results obtained showed that the fractal parameters of the subpopulations have the highest performance in predicting pCR. The predictive model elaborated had an area under the curve (AUC) equal to 0.77 ± 0.07. The model reliability was confirmed by the validation set (AUC = 0.79 ± 0.09). This study suggests that the fractal analysis can play an important role in radiomics, providing valuable information not only about the GTV structure, but also about its inner subpopulations.

Model predicting the ypN0 status after good response to chemoradiotherapy in rectal cancer

BACKGROUND

The purpose of this study was to identify the predictive factors for ypN0 status in tumors with good pathologic response to chemoradiotherapy (CRT).

METHODS

A retrospective chart review was conducted on patients at two tertiary cancer center who underwent rectal resection after good response to CRT between 2000 and 2013.

RESULTS

No preoperative treatment (oxaliplatin use, radiotherapy boost of 5,4 Gy, delay CRT-surgery) impacted on the ypN status. In the multivariate analysis, only a ypT<3 (HR 7.5 [2,9-19.5]) was significant and no lymphovascular invasion (HR 8,9 [1.6-49.8]) was limited to significance.The best model predicting the ypN0 status used only the ypT status<3. The major part (92.2%) of patients with ypT0-2 tumors had no LN invasion.

CONCLUSION

The risk of lymph node involvement metastases was only 7.8% for the patients with an ypT0-2 status. A fullthickness transanal resection coud be the futur treatment of these patients.

Molecular Imaging Using PET/CT for Radiation Therapy Planning for Adult Cancers: Current Status and Expanding Applications

Accurate tumor delineation is a priority in radiation therapy (RT). Metabolic imaging has a key and evolving role in target volume selection and delineation. This is especially so for non-small cell lung cancer, squamous cell cancer of the head and neck, and lymphoma, for which positron emission tomography/computed tomography (PET/CT) is complimentary to structural imaging modalities, not only in delineating primary tumors, but also often in revealing previously undiagnosed regional nodal disease. At some sites, PET/CT has been confirmed to enable target size reduction compared with structural imaging alone, with enhanced normal tissue sparing and potentially allowing for dose escalation. These contributions often dramatically affect RT strategies. However, some limitations exist to the use of fluorodeoxyglucose-PET in RT planning, including its relatively poor spatial resolution and partial voluming effects for small tumors. A role is developing for contributions from metabolic imaging to RT planning at other tumor sites and exciting new applications for the use of non-fluorodeoxyglucose metabolic markers for RT planning.

Complete response after chemoradiotherapy for rectal cancer: what is the reasonable approach?

With the increasing use of preoperative treatment rather than upfront surgery, it has become evident that the response of rectal carcinoma to standard chemoradiotherapy (CRT) shows a great variety that includes histopathologiocally confirmed complete tumor regression in 10–30% of cases. Adaptive strategies to avoid radical surgery, either by local excision or non-operative management, have been proposed in these highly responsive tumors. A growing number of prospective clinical trials and experiences from large databases, such as the European Registration of Cancer Care (EURECCA) watch-and-wait database, or the recent Oncological Outcome after Clinical Complete Response in Patients with Rectal Cancer (OnCoRe) project, will provide more information on its safety and efficacy, and help to select appropriate patients. Future studies will have to establish appropriate inclusion criteria and optimize CRT regimens in order to maximize the number of patients achieving complete response. Standardized re-staging procedures have to be investigated to improve the prediction of a sustained complete response, and long-term close follow-up with thorough documentation of failure patterns and salvage therapies will have to prove the oncological safety of this approach.

FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

PURPOSE

The aim of this study was to investigate the prognostic value of baseline ¹⁸F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC).

METHODS

Eighty-six patients with LARC underwent ¹⁸F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT).

RESULTS

The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrast_NGTDM) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4).

CONCLUSION

Textural analysis of baseline ¹⁸F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume-based parameters. The utility of such features, especially coarseness, should be confirmed by larger clinical studies before considering their potential integration into decisional algorithms aimed at personalized medicine.

Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer

BACKGROUND AND PURPOSE

To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.

MATERIAL AND METHODS

Eighty-five rectal cancer patients underwent preoperative CRT. ¹⁸F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate models were built combining the obtained parameters. Final models were calculated on the data combination with the highest AUC.

RESULTS

Twenty-two patients (26%) achieved ypT0-1N0 response. ¹⁸F-FDG PET/CT had worse predictive performance than DWI and T2-volumetry (AUC 0.61±0.04, 0.72±0.03, and 0.72±0.02, respectively). Combining all imaging parameters increased the AUC to 0.81±0.03. Adding cytokines or gene expression did not improve the AUC (AUC of 0.72±0.06 and 0.79±0.04 respectively). Final models combining ¹⁸F-FDG PET/CT, DWI, and T2-weighted volumetry at all TPs and using only TP1 and TP3, allowed ypT0-1N0 prediction with a 75% sensitivity, 94% specificity and PPV of 80%.

CONCLUSIONS

Combining ¹⁸F-FDG PET/CT, DWI, and T2-weighted MRI volumetry obtained before CRT and prior to surgery may help physicians in selecting rectal cancer patients for organ-preservation.

Organ preservation in rectal cancer - Challenges and future strategies

Neoadjuvant radiochemotherapy with subsequent total mesorectal excision is the standard of care for locally advanced rectal cancer. While this multimodal strategy has decreased local recurrences rates below 5%, long-term morbidities are considerable in terms of urinary, sexual or bowel functioning. At the same time approximately 10–20% of patients have no evidence of residual tumour in their surgical specimen. Pioneering studies from Brazil have suggested that surgery can safely be omitted in carefully selected patients with a clinical complete response after radiochemotherapy. Although confirmatory studies showed similar results, challenges in terms of optimizing radiochemotherapy for organ-preservation, appropriate selection of patients for non-operative management and the safety of this approach remain. The present review will summarize the current data on organ-preservation in rectal cancer and discuss the challenges that need to be addressed in future trials.

Clinical utility of pretreatment prediction of chemoradiotherapy response in rectal cancer: a review

Approximately 20% of all patients with locally advanced rectal cancer experience pathologically complete responses following neoadjuvant chemoradiotherapy (CRT) and standard surgery. The utility of radical surgery for patients exhibiting good CRT responses has been challenged. Organ-sparing strategies for selected patients exhibiting complete clinical responses include local excision or no immediate surgery. The subjects of this tailored management are patients whose presenting disease corresponds to current indications of neoadjuvant CRT, and their post-CRT tumor response is assessed by clinical and radiological examinations. However, a model predictive of the CRT response, applied before any treatment commenced, would be valuable to facilitate such a personalized approach. This would increase organ preservation, particularly in patients for whom upfront CRT is not generally prescribed. Molecular biomarkers hold the greatest promise for development of a pretreatment predictive model of CRT response. A combination of clinicopathological, radiological, and molecular markers will be necessary to render the model robust. Molecular research will also contribute to the development of drugs that can overcome the radioresistance of rectal tumors. Current treatments for rectal cancer are based on the expected prognosis given the presenting disease extent. In the future, treatment schemes may be modified by including the predicted CRT response evaluated at presentation.

Use of sequential endorectal US to predict the tumor response of preoperative chemoradiotherapy in rectal cancer

BACKGROUND AND AIMS

Accurate prediction of the response to preoperative chemoradiotherapy (CRT) potentially assists in the individualized selection of treatment. Endorectal US (ERUS) is widely used for the pretreatment staging of rectal cancer, but its use for preoperatively predicting the effects of CRT is not well evaluated because of the inflammation, necrosis, and fibrosis induced by CRT. This study assessed the value of sequential ERUS in predicting the efficacy of preoperative CRT for locally advanced rectal cancer.

METHODS

Forty-one patients with clinical stage II/III rectal adenocarcinoma were enrolled prospectively. Radiotherapy was delivered to the pelvis with concurrent chemotherapy of capecitabine and oxaliplatin. Total mesorectal excision was performed 6 to 8 weeks later. EUS measurements of primary tumor maximum diameter were performed before (ERUS1), during (ERUS2), and 6 to 8 weeks after (ERUS3) CRT, and the ratios of these were calculated. Correlations between ERUS values, tumor regression grade (TRG), T down-staging rate, and pathologic complete response (pCR) rate were assessed, and survival was analyzed.

RESULTS

There was no significant correlation between ERUS2/ERUS1 and TRG. The value of ERUS3/ERUS1 correlated with pCR rate and TRG but not T down-staging rate. An ERUS3 value of 6.3 mm and ERUS3/ERUS1 of 52% were used as the cut-off for predicting pCR, and patients were divided into good and poor prognosis groups. Although not statistically significant, 3-year recurrence and survival rates of the good prognosis group were better than those of the poor prognosis group.

CONCLUSIONS

Sequential ERUS may predict therapeutic efficacy of preoperative CRT for locally advanced rectal cancer. (Clinical trial registration number: NCT01582750.).

Tumor compactness improves the preoperative volumetry-based prediction of the pathological complete response of rectal cancer after preoperative concurrent chemoradiotherapy

In addition to clinical factors (tumor and node stage) and treatment factors (equivalent radiotherapy dose and chemotherapy regimen), we assessed whether different performances of various tumor volume measurements help predict the pathological complete response (pCR) of locally advanced rectal cancer (LARC) after preoperative concurrent chemoradiotherapy (CCRT). A total of 122 patients with LARC treated with a long course of CCRT, between December 2009 and March 2015, were enrolled in this bi-institutional study. Tumor delineation was based on standard T2-weighted magnetic resonance imaging or contrast-enhanced computed tomography before CCRT. Tumor compactness was defined as the ratio of the volume and the surface area. The tumor compactness-corrected TV (TCTV) was defined as the ratio of the real TV (RTV) and tumor compactness. Twenty-three (18.9%) patients had a pCR. Areas under the curve of the receiver operating characteristic for pCR prediction calculated using the RTV, cylindrical approximated TV (CATV), and TCTV were 0.724, 0.747, and 0.780, respectively. The prediction performance of TCTV was significantly more efficient than that of both RTV (P = 0.0057) and CATV (P = 0.0329). Multivariate logistic regression analysis revealed tumor compactness (P = 0.001), RTV (P = 0.042), and preoperative clinical nodal status (P = 0.044) as significant predictors of a pCR. In addition, poor tumor compactness was closely associated with lymphovascular space invasion (P = 0.008) and pathological nodal status (P = 0.003). For patients with LARC receiving preoperative CCRT, tumor compactness is a useful radiomic parameter for improving the volumetric based prediction model.

Nomogram basing pre-treatment parameters predicting early response for locally advanced rectal cancer with neoadjuvant chemotherapy alone: a subgroup efficacy analysis of FOWARC study

Objective

To develop an accurate model with pre-treatment parameters to predict tumor regression and down-staging in locally advanced rectal cancer patients, basing the cohort of preoperative chemotherapy alone in FOWARC study.

Patients and Methods

From Jan 2011 to Feb 2015, complete data was available for 137 out of 165 patients who received preoperative chemotherapy alone. All pre-treatment clinical parameters were collected. Tumor regression grade (TRG) 0-1 was defined as good regression, and pathological TNM stage (ypTNM) 0-I after neoadjuvant treatment was defined as good down-staging. Nomogram was established to predict tumor regression and down-staging. The predictive performance of the model was assessed with concordance index and calibration plots.

Results

Of the 137 patients, 10 had TRG 0 (complete regression); 32 patients, TRG 1; and 95 patients, TRG 2 and 3 (poor regression); 56 (40.9%) patients were classified as good down-staging with ypTNM stage 0-I. The predictive nomograms were developed to predict the probability of TRG 0-1 and good down-staging with a C-index of 0.72 (95% CI: 0.604-0.797) and 0.76 (95% CI: 0.681-0.844). Calibration plots showed good statistical performance on internal validation. Predictive factors in the models included tumor length, tumor circumferential extent, age, and ApoA1.

Conclusions

The model based on available clinical parameters could accurately predict early efficacy with neoadjuvant mFOLFOX6 chemotherapy alone, which might help in patient selection for optimized treatment.

Standardized data collection to build prediction models in oncology: a prototype for rectal cancer

The advances in diagnostic and treatment technology are responsible for a remarkable transformation in the internal medicine concept with the establishment of a new idea of personalized medicine. Inter- and intra-patient tumor heterogeneity and the clinical outcome and/or treatment's toxicity's complexity, justify the effort to develop predictive models from decision support systems. However, the number of evaluated variables coming from multiple disciplines: oncology, computer science, bioinformatics, statistics, genomics, imaging, among others could be very large thus making traditional statistical analysis difficult to exploit. Automated data-mining processes and machine learning approaches can be a solution to organize the massive amount of data, trying to unravel important interaction. The purpose of this paper is to describe the strategy to collect and analyze data properly for decision support and introduce the concept of an 'umbrella protocol' within the framework of 'rapid learning healthcare'.

Nomograms for colorectal cancer: A systematic review

AIM

To assist in the selection of suitable nomograms for obtaining desired predictions in daily clinical practice.

METHODS

We conducted electronic searches for journal articles on colorectal cancer (CRC)-associated nomograms using the search terms colon/rectal/colorectal/nomogram. Of 174 articles initially found, we retrieved 28 studies in which a nomogram for CRC was developed.

RESULTS

We discuss the currently available CRC-associated nomograms, including those that predict the oncological prognosis, the short-term outcome of treatments, such as surgery or neoadjuvant chemoradiotherapy, and the future development of CRC. Developing nomograms always presents a dilemma. On the one hand, the desire to cover as wide a patient range as possible tends to produce nomograms that are too complex and yet have C-indexes that are not sufficiently high. Conversely, confining the target patients might impair the clinical applicability of constructed nomograms.

CONCLUSION

The information provided in this review should be of use in selecting a nomogram suitable for obtaining desired predictions in daily clinical practice.

New Perspectives on Predictive Biomarkers of Tumor Response and Their Clinical Application in Preoperative Chemoradiation Therapy for Rectal Cancer

Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10-30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment.

[(18)F]FPRGD2 PET/CT imaging of integrin αvβ3 levels in patients with locally advanced rectal carcinoma

PURPOSE

Our primary objective was to determine if [(18)F]FPRGD2 PET/CT performed at baseline and/or after chemoradiotherapy (CRT) could predict tumour regression grade (TRG) in locally advanced rectal cancer (LARC). Secondary objectives were to compare baseline [(18)F]FPRGD2 and [(18)F]FDG uptake, to evaluate the correlation between posttreatment [(18)F]FPRGD2 uptake and tumour microvessel density (MVD) and to determine if [(18)F]FPRGD2 and FDG PET/CT could predict disease-free survival.

METHODS

Baseline [(18)F]FPRGD2 and FDG PET/CT were performed in 32 consecutive patients (23 men, 9 women; mean age 63 ± 8 years) with LARC before starting any therapy. A posttreatment [(18)F]FPRGD2 PET/CT scan was performed in 24 patients after the end of CRT (median interval 7 weeks, range 3 - 15 weeks) and before surgery (median interval 4 days, range 1 - 15 days).

RESULTS

All LARC showed uptake of both [(18)F]FPRGD2 (SUVmax 5.4 ± 1.5, range 2.7 - 9) and FDG (SUVmax 16.5 ± 8, range 7.1 - 36.5). There was a moderate positive correlation between [(18)F]FPRGD2 and FDG SUVmax (Pearson's r = 0.49, p = 0.0026). There was a moderate negative correlation between baseline [(18)F]FPRGD2 SUVmax and the TRG (Spearman's r = -0.37, p = 0.037), and a [(18)F]FPRGD2 SUVmax of >5.6 identified all patients with a complete response (TRG 0; AUC 0.84, 95 % CI 0.68 - 1, p = 0.029). In the 24 patients who underwent a posttreatment [(18)F]FPRGD2 PET/CT scan the response index, calculated as [(SUVmax1 - SUVmax2)/SUVmax1] × 100 %, was not associated with TRG. Post-treatment [(18)F]FPRGD2 uptake was not correlated with tumour MVD. Neither [(18)F]FPRGD2 nor FDG uptake predicted disease-free survival.

CONCLUSION

Baseline [(18)F]FPRGD2 uptake was correlated with the pathological response in patients with LARC treated with CRT. However, the specificity was too low to consider its clinical routine use.

Prospective, Multicenter Validation Study of Magnetic Resonance Volumetry for Response Assessment After Preoperative Chemoradiation in Rectal Cancer: Can the Results in the Literature be Reproduced?

PURPOSE

To review the available literature on tumor size/volume measurements on magnetic resonance imaging for response assessment after chemoradiotherapy, and validate these cut-offs in an independent multicenter patient cohort.

METHODS AND MATERIALS

The study included 2 parts. (1) Review of the literature: articles were included that assessed the accuracy of tumor size/volume measurements on magnetic resonance imaging for tumor response assessment. Size/volume cut-offs were extracted; (2) Multicenter validation: extracted cut-offs from the literature were tested in a multicenter cohort (n=146). Accuracies were calculated and compared with reported results from the literature.

RESULTS

The review included 14 articles, in which 3 different measurement methods were assessed: (1) tumor length; (2) 3-dimensonial tumor size; and (3) whole volume. Study outcomes consisted of (1) complete response (ypT0) versus residual tumor; (2) tumor regression grade 1 to 2 versus 3 to 5; and (3) T-downstaging (ypT<cT). In the multicenter cohort, best results were obtained for the validation of the whole-volume measurements, in particular for the outcome ypT0 (accuracy 44%-80%), with the optimal cut-offs being 1.6 cm(3) (after chemoradiation therapy) and a volume reduction of Δ80% to 86.6%. Accuracies for whole-volume measurements to assess tumor regression grade 1 to 2 were 52% to 61%, and for T-downstaging 51% to 57%. Overall accuracies for tumor length ranged between 48% and 53% and for 3D size measurement between 52% and 56%.

CONCLUSIONS

Magnetic resonance volumetry using whole-tumor volume measurements can be helpful in rectal cancer response assessment with selected cut-off values. Measurements of tumor length or 3-dimensional tumor size are not helpful. Magnetic resonance volumetry is mainly accurate to assess a complete tumor response (ypT0) after chemoradiation therapy (accuracies up to 80%).

Carcinoembryonic antigen has prognostic value for tumor downstaging and recurrence in rectal cancer after preoperative chemoradiotherapy and curative surgery: A multi-institutional and case-matched control study of KROG 14-12

BACKGROUND AND PURPOSE

The Korean Radiation Oncology Group evaluated the significance of carcinoembryonic antigen (CEA) levels both as a predictor of tumor response after CRT and as a prognosticator for recurrence-free survival.

METHODS AND MATERIALS

1804 rectal cancer patients, staged cT3-4N0-2M0, participated in a multicenter study. The patients were administered preoperative radiation of 50.4 Gy in 28 fractions with 5-FU or capecitabine, followed by total mesorectal excision. Patients with elevated CEA levels (>5 ng/mL) were matched at a 1 (n=595):1 (n=595) ratio with patients with normal CEA (⩽5 ng/mL). The tumor response after CRT and the recurrence-free survival (RFS) rates were evaluated and compared between two arms.

RESULTS

An elevated CEA level (p<0.001) was determined to be a significant negative predictor of downstaging after CRT. The downstaging rate was 42.9% for normal CEA and 23.4% for elevated CEA. A multivariate analysis also revealed that cT (p=0.021) and cN classification (p=0.001), tumor size (p=0.002), and tumor location from the anal verge (p=0.006) were significant predictors for tumor downstaging. The 5-year RFS rates were significantly higher for the normal CEA arm than for the elevated CEA arm (74.2 vs. 63.5%, p<0.001).

CONCLUSIONS

Elevated CEA (>5 ng/mL) is a negative predictor of tumor downstaging after CRT and also has a negative impact on RFS in rectal cancer.

Personalized radiotherapy: concepts, biomarkers and trial design

In the past decade, and pointing onwards to the immediate future, clinical radiotherapy has undergone considerable developments, essentially including technological advances to sculpt radiation delivery, the demonstration of the benefit of adding concomitant cytotoxic agents to radiotherapy for a range of tumour types and, intriguingly, the increasing integration of targeted therapeutics for biological optimization of radiation effects. Recent molecular and imaging insights into radiobiology will provide a unique opportunity for rational patient treatment, enabling the parallel design of next-generation trials that formally examine the therapeutic outcome of adding targeted drugs to radiation, together with the critically important assessment of radiation volume and dose-limiting treatment toxicities. In considering the use of systemic agents with presumed radiosensitizing activity, this may also include the identification of molecular, metabolic and imaging markers of treatment response and tolerability, and will need particular attention on patient eligibility. In addition to providing an overview of clinical biomarker studies relevant for personalized radiotherapy, this communication will highlight principles in addressing clinical evaluation of combined-modality-targeted therapeutics and radiation. The increasing number of translational studies that bridge large-scale omics sciences with quality-assured phenomics end points-given the imperative development of open-source data repositories to allow investigators the access to the complex data sets-will enable radiation oncology to continue to position itself with the highest level of evidence within existing clinical practice.