External validation of a lung cancer-based prediction model for two-year mortality in esophageal cancer patient cohorts

PURPOSE/OBJECTIVE

Chemo-radiotherapy can improve the oncological outcome of esophageal cancer (EC) patients, but may cause long term radiation-induced toxicity, including an increased risk of non-cancer related death. For lung cancer patients, a model to predict 2-year total mortality using mean heart dose (MHD) and gross tumor volume (GTV) has previously been developed and validated. This project aimed to externally validate this model in EC patients.

METHODS

Five EC patient cohorts from 3 different Dutch centres were used for model validation. External validity of the model was assessed separately in definitive (n = 170) and neo-adjuvant (n = 568) chemoradiotherapy (dCRT and nCRT) patients. External validity was assessed in terms of calibration by calibration plots, calibration-in-the-large (CITL) and calibration slope (CS), and discrimination by assessment of the c-statistic. If suboptimal model performance was observed, the model was further updated accordingly.

RESULTS

For the dCRT patients, good calibration was found after adjustment of the intercept (CITL 0.00; CS 1.08). The c-statistic of the adjusted model was 0.67 (95%CI: 0.58 to 0.75). For nCRT patients the model needed adjustment of both the slope and the intercept because of initial miscalibration in the validation population (CITL 0.00; CS 1.72). After recalibration, the model showed perfect calibration (i.e., CITL 0, CS 1), as is common after recalibration. The c-statistic of the recalibrated model equaled 0.62 (95%CI: 0.57 to 0.67).

CONCLUSION

The existing model for 2-year mortality prediction in lung cancer patients, based on the predictive factors MHD and GTV, showed good performance in EC patients after updating the intercept and/or slope of the original model.

Severity of oEsophageal Anastomotic Leak in patients after oesophagectomy: the SEAL score

Background

Anastomotic leak (AL) is a common but severe complication after oesophagectomy. It is unknown how to determine the severity of AL objectively at diagnosis. Determining leak severity may guide treatment decisions and improve future research. This study aimed to identify leak-related prognostic factors for mortality, and to develop a Severity of oEsophageal Anastomotic Leak (SEAL) score.

Methods

This international, retrospective cohort study in 71 centres worldwide included patients with AL after oesophagectomy between 2011 and 2019. The primary endpoint was 90-day mortality. Leak-related prognostic factors were identified after adjusting for confounders and were included in multivariable logistic regression to develop the SEAL score. Four classes of leak severity (mild, moderate, severe, and critical) were defined based on the risk of 90-day mortality, and the score was validated internally.

Results

Some 1509 patients with AL were included and the 90-day mortality rate was 11.7 per cent. Twelve leak-related prognostic factors were included in the SEAL score. The score showed good calibration and discrimination (c-index 0.77, 95 per cent c.i. 0.73 to 0.81). Higher classes of leak severity graded by the SEAL score were associated with a significant increase in duration of ICU stay, healing time, Comprehensive Complication Index score, and Esophagectomy Complications Consensus Group classification.

Conclusion

The SEAL score grades leak severity into four classes by combining 12 leak-related predictors and can be used to the assess severity of AL after oesophagectomy.

Locally advanced rectal cancer: is diffusion weighted MRI helpful for the identification of complete responders (ypT0N0) after neoadjuvant chemoradiation therapy?

OBJECTIVES

To determine retrospectively the additional value of DWI-MRI toT2-MRI for predicting complete response (ypT0N0 = CR) after chemoradiation-therapy (CRT) in locally advanced rectal cancer.

METHODS

Seventy locally advanced rectal cancer patients underwent CRT followed by restaging MRI and resection. Two readers with different experience levels independently scored T2 images for CR and, in a second reading, combined T2 and DWI. A 5-point confidence-level score was used to generate ROC curves. Areas under the ROC curves (AUC) and interobserver agreement were compared for both readings. Histology served as reference standard.

RESULTS

The interobserver agreement increased after addition of DWI from 0.35 to 0.58 but the AUC improved only for the experienced reader (0.77 to 0.89, p = 0.005 vs. 0.74 to 0.70, p > 0.05). Sensitivity and NPV improved from 20-30 % to 40-70 %, respectively 88 % to 91-95 %. Specificity and PPV improved only for the experienced reader (87 to 93 % respectively 27 to 63 %).

CONCLUSION

Adding DWI to T2-MRI improves consistency between readers and has potential to improve readers' accuracy dependent on his/her experience. DWI could be of additional value, particularly in ruling out CR (high NPV), but considering the sub-optimal PPV one should be cautious about relying solely on MRI for the clinical decision to offer a wait-and-see strategy.