SOURCE: Prediction Models for Overall Survival in Patients With Metastatic and Potentially Curable Esophageal and Gastric Cancer

External validation of a nomogram predicting conditional survival after tri-modality treatment of esophageal cancer

BACKGROUND

A conditional survival nomogram was developed at a single high-volume center to predict 5-year overall survival for esophageal cancer patients after neoadjuvant chemoradiation and esophagectomy. The aim of this study was to externally validate the nomogram in a cohort of patients with esophageal adeno- or squamous cell carcinoma from another high-volume center.

METHODS

Consecutive patients with an esophageal adeno- or squamous cell carcinoma who had undergone esophagectomy after being treated with preoperative chemoradiation between 2004 and 2016 were selected from a prospectively maintained institutional database. The level of discrimination for prediction of 5-year overall survival was quantified by Harrell's C statistic. Calibration of the conditional survival nomogram was visualized by plotting predicted 5-year survival and observed 5-year survival for comparison.

RESULTS

Of the 296 patients examined, the probability of 5-year overall survival directly after surgery was 45% and increased to 51%, 68%, 78%, and 89% for each additional year survived. The predicted 5-year overall survival differed from the observed survival, with a calibration slope of 0.54, 0.55, 0.59, 0.73, and 1.09 directly after surgery and 1, 2, 3, and 4 years of survival after surgery, respectively. The nomogram's discrimination level for 5-year survival was moderate, with a C statistic of 0.65 compared to the 0.70 reported in the original study.

CONCLUSION

The nomogram model has moderate predictive discrimination and accuracy, supporting its applicability to external cohorts to predict conditional survival. Further validation studies should empirically assess the model for predictive performance.

Effect of a prediction tool and communication skills training on communication of treatment outcomes: a multicenter stepped wedge clinical trial (the SOURCE trial)

Background

For cancer patients to effectively engage in decision making, they require comprehensive and understandable information regarding treatment options and their associated outcomes. We developed an online prediction tool and supporting communication skills training to assist healthcare providers (HCPs) in this complex task. This study aims to assess the impact of this combined intervention (prediction tool and training) on the communication practices of HCPs when discussing treatment options.

Methods

We conducted a multicenter intervention trial using a pragmatic stepped wedge design (NCT04232735). Standardized Patient Assessments (simulated consultations) using cases of esophageal and gastric cancer patients, were performed before and after the combined intervention (March 2020 to July 2022). Audio recordings were analyzed using an observational coding scale, rating all utterances of treatment outcome information on the primary outcome-precision of provided outcome information-and on secondary outcomes-such as: personalization, tailoring and use of visualizations. Pre vs. post measurements were compared in order to assess the effect of the intervention.

Findings

31 HCPs of 11 different centers in the Netherlands participated. The tool and training significantly affected the precision of the overall communicated treatment outcome information (p = 0.001, median difference 6.93, IQR (-0.32 to 12.44)). In the curative setting, survival information was significantly more precise after the intervention (p = 0.029). In the palliative setting, information about side effects was more precise (p < 0.001).

Interpretation

A prediction tool and communication skills training for HCPs improves the precision of treatment information on outcomes in simulated consultations. The next step is to examine the effect of such interventions on communication in clinical practice and on patient-reported outcomes.

Funding

Financial support for this study was provided entirely by a grant from the Dutch Cancer Society (UVA 2014-7000).

Late Toxicity and Health-Related Quality of Life Following Definitive Chemoradiotherapy for Esophageal Cancer: A Systematic Review and Meta-analysis

PURPOSE

Definitive chemoradiotherapy (dCRT) is a treatment option with curative intent for patients with esophageal cancer that could result in late toxicities and affect health-related quality of life (HRQoL). This study aimed to review the literature and perform a meta-analysis to investigate the effect of dCRT on late toxicities and HRQoL in esophageal cancer.

METHODS AND MATERIALS

A systematic search was performed in MEDLINE, EMBASE, and PsychINFO. Prospective phase II and III clinical trials, population-based studies, and retrospective chart reviews investigating late toxicity or HRQoL after dCRT (≥50 Gy) were included. The HRQoL outcomes were analyzed using linear mixed-effect models with restricted cubic spline transformation. Any HRQoL changes of ≥10 points were considered clinically relevant. The risk of toxicities was calculated using the number of events and the total study population.

RESULTS

Among 41 included studies, 10 assessed HRQoL and 31 late toxicity. Global health status remained stable over time and improved after 36 months compared with baseline (mean change, +11). Several tumor-specific symptoms, including dysphagia, eating restrictions, and pain, improved after 6 months compared with baseline. Compared with baseline, dyspnea worsened after 6 months (mean change, +16 points). The risk of any late toxicity was 48% (95% CI, 33%-64%). Late toxicity risk of any grade for the esophagus was 17% (95% CI, 12%-21%), pulmonary 21% (95% CI, 11%-31%), cardiac 12% (95% CI, 6%-17%), and any other organ 24% (95% CI, 2%-45%).

CONCLUSIONS

Global health status remained stable over time, and tumor-specific symptoms improved within 6 months after dCRT compared with baseline, with the exception of dyspnea. In addition, substantial risks of late toxicity were observed.

SOURCE beyond first-line: A survival prediction model for patients with metastatic esophagogastric adenocarcinoma after failure of first-line palliative systemic therapy

Prior models have been developed to predict survival for patients with esophagogastric cancer undergoing curative treatment or first-line chemotherapy (SOURCE models). Comprehensive clinical prediction models for patients with esophagogastric cancer who will receive second-line chemotherapy or best supportive care are currently lacking. The aim of our study was to develop and internally validate a new clinical prediction model, called SOURCE beyond first-line, for survival of patients with metastatic esophagogastric adenocarcinoma after failure of first-line palliative systemic therapy. Patients with unresectable or metastatic esophageal or gastric adenocarcinoma (2015-2017) who received first-line systemic therapy (N = 1067) were selected from the Netherlands Cancer Registry. Patient, tumor and treatment characteristics at primary diagnosis and at progression of disease were used to develop the model. A Cox proportional hazards regression model was developed through forward and backward selection using Akaike's Information Criterion. The model was internally validated through 10-fold cross-validations to assess performance. Model discrimination (C-index) and calibration (slope and intercept) were used to evaluate performance of the complete and cross-validated models. The final model consisted of 11 patient tumor and treatment characteristics. The C-index was 0.75 (0.73-0.78), calibration slope 1.01 (1.00-1.01) and calibration intercept 0.01 (0.01-0.02). Internal cross-validation of the model showed that the model performed adequately on unseen data: C-index was 0.79 (0.77-0.82), calibration slope 0.93 (0.85-1.01) and calibration intercept 0.02 (-0.01 to 0.06). The SOURCE beyond first-line model predicted survival with fair discriminatory ability and good calibration.

Improving survival prediction of oesophageal cancer patients treated with external beam radiotherapy for dysphagia

INTRODUCTION

The recent POLDER trial investigated the effects of external beam radiotherapy (EBRT) on dysphagia caused by incurable oesophageal cancer. An estimated life expectancy of minimally three months was required for inclusion. However, nearly one-third of the included patients died within three months. The aim of this study was to investigate if the use of prediction models could have improved the physician's estimation of the patient's survival.

METHODS

Data from the POLDER trial (N = 110) were linked to the Netherlands Cancer Registry to retrieve patient, tumour, and treatment characteristics. Two published prediction models (the SOURCE model and Steyerberg model) were used to predict three-month survival for all patients included in the POLDER trial. Predicted survival probabilities were dichotomised and the accuracy, sensitivity, specificity, and the area under the curve (AUC) were used to evaluate the predictive performance.

RESULTS

The SOURCE and Steyerberg model had an accuracy of 79% and 64%, and an AUC of 0.76 and 0.60 (p = .017), respectively. The SOURCE model had higher specificity across survival cut-off probabilities, the Steyerberg model had a higher sensitivity beyond the survival probability cut-off of 0.7. Using optimal cut-off probabilities, SOURCE would have wrongfully included 16/110 patients into the POLDER and Steyerberg 34/110.

CONCLUSION

The SOURCE model was found to be a more useful decision aid than the Steyerberg model. Results showed that the SOURCE model could be used for three-month survival predictions for patients that are considered for palliative treatment of dysphagia caused by oesophageal cancer in addition to clinicians' judgement.

Informing Patients With Esophagogastric Cancer About Treatment Outcomes by Using a Web-Based Tool and Training: Development and Evaluation Study

Background

Due to the increasing use of shared decision-making, patients with esophagogastric cancer play an increasingly important role in the decision-making process. To be able to make well-informed decisions, patients need to be adequately informed about treatment options and their outcomes, namely survival, side effects or complications, and health-related quality of life. Web-based tools and training programs can aid physicians in this complex task. However, to date, none of these instruments are available for use in informing patients with esophagogastric cancer about treatment outcomes.

Objective

This study aims to develop and evaluate the feasibility of using a web-based prediction tool and supporting communication skills training to improve how physicians inform patients with esophagogastric cancer about treatment outcomes. By improving the provision of treatment outcome information, we aim to stimulate the use of information that is evidence-based, precise, and personalized to patient and tumor characteristics and is communicated in a way that is tailored to individual information needs.

Methods

We designed a web-based, physician-assisted prediction tool—Source—to be used during consultations by using an iterative, user-centered approach. The accompanying communication skills training was developed based on specific learning objectives, literature, and expert opinions. The Source tool was tested in several rounds—a face-to-face focus group with 6 patients and survivors, semistructured interviews with 5 patients, think-aloud sessions with 3 medical oncologists, and interviews with 6 field experts. In a final pilot study, the Source tool and training were tested as a combined intervention by 5 medical oncology fellows and 3 esophagogastric outpatients.

Results

The Source tool contains personalized prediction models and data from meta-analyses regarding survival, treatment side effects and complications, and health-related quality of life. The treatment outcomes were visualized in a patient-friendly manner by using pictographs and bar and line graphs. The communication skills training consisted of blended learning for clinicians comprising e-learning and 2 face-to-face sessions. Adjustments to improve both training and the Source tool were made according to feedback from all testing rounds.

Conclusions

The Source tool and training could play an important role in informing patients with esophagogastric cancer about treatment outcomes in an evidence-based, precise, personalized, and tailored manner. The preliminary evaluation results are promising and provide valuable input for the further development and testing of both elements. However, the remaining uncertainty about treatment outcomes in patients and established habits in doctors, in addition to the varying trust in the prediction models, might influence the effectiveness of the tool and training in daily practice. We are currently conducting a multicenter clinical trial to investigate the impact that the combined tool and training have on the provision of information in the context of treatment decision-making.