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Objective The interpretation and clinical application of guidelines can be challenging and time-consuming, which may result in noncompliance to guidelines. The aim of this study was to convert the Dutch guideline for colorectal cancer (CRC) into decision trees and subsequently implement decision trees in an online decision support environment to facilitate guideline application. Methods The recommendations of the Dutch CRC guidelines (published in 2014) were translated into decision trees consisting of decision nodes, branches and leaves that represent data items, data item values and recommendations, respectively. Decision trees were discussed with experts in the field and published as interactive open access decision support software (available at www.oncoguide.nl). Decision tree validation and a concordance analysis were performed using consecutive reports (January 2016–January 2017) from CRC multidisciplinary tumour boards (MTBs) at Amsterdam University Medical Centers, location AMC. Results In total, we developed 34 decision trees driven by 101 decision nodes based on the guideline recommendations. Decision trees represented recommendations for diagnostics (n = 1), staging (n = 10), primary treatment (colon: n = 1, rectum: n = 5, colorectal: n = 9), pathology (n = 4) and follow-up (n = 3) and included one overview decision tree for optimal navigation. We identified several guideline information gaps and areas of inconclusive evidence. A total of 158 patients’ MTB reports were eligible for decision tree validation and resulted in treatment recommendations in 80% of cases. The concordance rate between decision tree treatment recommendations and MTB advices was 81%. Decision trees reported in 22 out of 24 non-concordant cases (92%) that no guideline recommendation was available. Conclusions We successfully converted the Dutch CRC guideline into decision trees and identified several information gaps and areas of inconclusive evidence, the latter being the main cause of the observed disagreement between decision tree recommendations and MTB advices. Decision trees may contribute to future strategies to optimize quality of care for CRC patients.

Introduction: Population-based data on the implementation of guidelines for cancer patients in daily practice are scarce, while practice variation may influence patient outcomes. Therefore, we evaluated treatment patterns and associated variables in the systemic treatment of metastatic colorectal cancer (mCRC) in the Netherlands. Material and methods: We selected a random sample of adult mCRC patients diagnosed from 2008 to 2015 from the National Cancer Registry in 20 (4 academic, 8 teaching and 8 regional) Dutch hospitals. We examined the influence of patient, demographic and tumour characteristics on the odds of being treated with systemic therapy according to the current guideline and assessed its association with survival. Results: Our study population consisted of 2222 mCRC patients of whom 1307 patients received systemic therapy for mCRC. Practice variation was most obvious in the use of bevacizumab and anti-EGFR therapy in patients with (K)RAS wild-type tumours. Administration rates did not differ between hospital types but fluctuated between individual hospitals for bevacizumab (8–92%; p

Background Clinical guidelines are generated to preserve high-quality evidence-based care. Data on the implementation of guidelines into clinical practice are scarce, despite that guideline adherence prevents over- and undertreatment and correlates with survival. Therefore, we investigated guideline adherence for the systemic treatment in high-risk stage II and stage III colon cancer and metastatic colorectal cancer. Patients and Methods In all Dutch hospitals (n = 88) 1 medical oncologist involved in colorectal cancer care was approached to participate. An online survey was conducted regarding the local standard of care for adjuvant chemotherapy in high-risk stage II and stage III colon cancer and first-line treatment regimens in metastatic colorectal cancer. Frequency tables were provided for categorical variables and compared for differences in guideline adherence according to hospital type (academic/teaching/regional). Results The overall response rate was 70% (62 of 88). Reported guideline adherence was at least 60% of all presented settings. For high-risk stage II and stage III colon cancer, treatment strategies agreed with national guidelines in 66% and 84% of hospitals, and overtreatment patterns were identified in 28% and 13%, respectively. Targeted therapy was not routinely administered as first-line treatment in metastatic colorectal cancer (range from 63% to 71% in different settings). No differences in guideline adherence were observed among different hospital types. Conclusion Guideline adherence as reported by medical oncologists in The Netherlands is suboptimal. Possible explanations include unawareness or disagreement with the guidelines, or local financial restrictions. Our results recommend additional support of guideline implementation and monitoring in clinical practice, and investigating underlying causes in case of nonadherence.

BACKGROUND/AIM: Adjuvant chemotherapy is recommended for a subgroup of colon cancer patients based on patient and tumour characteristics. Population-based data on the adoption of the prevailing guideline recommendations including the assessment of tumour mismatch repair (MMR) status are limited, while variations in treatment strategies may influence patient outcomes. Therefore, the aim of the study was to assess practice variation in adjuvant chemotherapy administration in colon cancer patients. PATIENTS AND METHODS: We examined the association between patient, demographic and tumour characteristics on the odds of being treated with adjuvant chemotherapy in a random sample of adult stage II-III colon cancer patients from the Dutch National Cancer Registry (2008-2015) and assessed its association with survival. RESULTS: The study population consisted of 2,044 patients of whom 18% (79 out of 450) were high-risk stage II and 65% (645 out of 997) were stage III colon cancer and received adjuvant chemotherapy. Chemotherapy administration differed between individual hospitals (high-risk stage II: 0-39%; p=0.01; stage III: 50-78%; p=0.06). Type of hospital (teaching versus academic) and the presence of a pT4 tumour were positively associated (high-risk stage II), and bowel perforation and examined regional lymph nodes (

Background and aim: Medical specialists aim to provide evidence-based care based on the most recent scientific insights, but with the ongoing expansion of medical literature it seems unfeasible to remain updated. "Black-box" decision support tools such as Watson for Oncology (Watson) are gaining attention as they offer a promising opportunity to conquer this challenging issue, but it is not known if the advice given is congruent with guidelines or clinically valid in other settings. We present a protocol for the content evaluation of black-box decision support tools and a feasibility study to test the content and usability of Watson using this protocol. Methods: The protocol consists of developing synthetic patient cases based on Dutch guidelines and expert opinion, entering the synthetic cases into Watson and Oncoguide, noting the response of each system and evaluating the result using a cross-tabulation scoring system resulting in a score range of —12 to +12. Treatment options that were not recommended according to the Dutch guideline were labeled with a "red flag" if Watson recommended it, and an "orange flag" if Watson suggested it for consideration. To test the feasibility of applying the protocol, we developed synthetic patient cases for the adjuvant treatment of stage I to stage III colon cancer based on relevant patient, clinical and tumor characteristics and followed our protocol. Additionally, for the feasibility study we also compared the recommendations from the NCCN guideline with Watson's advice, and evaluated usability by a cognitive walkthrough method. Results: In total, we developed 190 synthetic patient cases (stage I: n=8; stage II: n=110; and stage III: n=72). Overall concordance scores per case for Watson versus Oncoguide ranged from a minimum score of -4 (n=6) to a maximum score of+12 (n=17) and from —4 (n=9) to +12 (n=24) for Watson versus the NCCN guidelines). In total, 69 cases (36%) were labeled with red flags, 96 cases (51%) with orange flags and 25 cases (13%) without flags. For the comparison of Watson with the NCCN guidelines, no red or orange flags were identified. Conclusions: We developed a research protocol for the evaluation of a black-box decision support tool, which proved useful and usable in testing the content and usability of Watson. Overall concordance scores ranged considerably between synthetic cases for both comparisons between Watson versus Oncoguide and Watson versus NCCN. Non-concordance is partially attributable to guideline differences between the United States and The Netherlands. This implies that further adjustments and localization are required before implementation of Watson outside the United States. Relevance for patients: This study describes the first steps of content evaluation of a decision support tool before implementation in daily oncological patient care. The ultimate goal of the incorporation of decision support tools in daily practice is to improve personalized medicine and quality of care.

Background and aim Medical specialists aim to provide evidence-based care based on the most recent scientific insights, but with the ongoing expansion of medical literature it seems unfeasible to remain updated. "Black-box" decision support tools such as Watson for Oncology (Watson) are gaining attention as they offer a promising opportunity to conquer this challenging issue, but it is not known if the advice given is congruent with guidelines or clinically valid in other settings. We present a protocol for the content evaluation of black-box decision support tools and a feasibility study to test the content and usability of Watson using this protocol. Methods The protocol consists of developing synthetic patient cases based on Dutch guidelines and expert opinion, entering the synthetic cases into Watson and Oncoguide, noting the response of each system and evaluating the result using a cross-tabulation scoring system resulting in a score range of -12 to +12. Treatment options that were not recommended according to the Dutch guideline were labeled with a "red flag" if Watson recommended it, and an "orange flag" if Watson suggested it for consideration. To test the feasibility of applying the protocol, we developed synthetic patient cases for the adjuvant treatment of stage I to stage III colon cancer based on relevant patient, clinical and tumor characteristics and followed our protocol. Additionally, for the feasibility study we also compared the recommendations from the NCCN guideline with Watson's advice, and evaluated usability by a cognitive walkthrough method. Results In total, we developed 190 synthetic patient cases (stage I: n=8; stage II: n=110; and stage III: n=72). Overall concordance scores per case for Watson versus Oncoguide ranged from a minimum score of -4 (n=6) to a maximum score of+12 (n=17) and from -4 (n=9) to +12 (n=24) for Watson versus the NCCN guidelines). In total, 69 cases (36%) were labeled with red flags, 96 cases (51%) with orange flags and 25 cases (13%) without flags. For the comparison of Watson with the NCCN guidelines, no red or orange flags were identified. Conclusions We developed a research protocol for the evaluation of a black-box decision support tool, which proved useful and usable in testing the content and usability of Watson. Overall concordance scores ranged considerably between synthetic cases for both comparisons between Watson versus Oncoguide and Watson versus NCCN. Non-concordance is partially attributable to guideline differences between the United States and The Netherlands. This implies that further adjustments and localization are required before implementation of Watson outside the United States. Relevance for patients This study describes the first steps of content evaluation of a decision support tool before implementation in daily oncological patient care. The ultimate goal of the incorporation of decision support tools in daily practice is to improve personalized medicine and quality of care.