Clinical trial NCT04675138: Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care
Official title: Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Gastric Cancer
Esophageal Cancer
Esophagogastric Junction Cancer
Keywords: Gastric Cancer
Esophageal Cancer
Artificial Intelligence
Multidisciplinary Tumor Board
Clinical Decision Support System
Concordance
Lead sponsor: National University Hospital, Singapore
Sponsor class: OTHER
First posted: 2020-12-19
Enrollment: 1000
Sex: ALL
Minimum age (years): 21
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The population will be selected from hospitals that conduct tumor board for these cancers

Brief summary: Clinical Decision Support Systems (CDSSs) to augment clinical care and decision making. These are platforms which aim to improve healthcare delivery by enhancing medical decisions with targeted clinical knowledge, patient information, and other health information.

In view of the benefit of developing a CDSS, we sought to develop an alternative CDSS for oncologic therapy selection through a partnership with Ping An Technology (Shenzhen, China), beginning with gastric and oesophagal cancer. This would be done in a piecemeal fashion, with the prototype platform utilizing only international guidelines and high-quality published evidence from journals to arrive at case-specific treatment recommendations. This platform would then be evaluated by comparing its recommendations with that from the multidisciplinary tumour boards of several tertiary care institutions to determine the concordance rate.

Detailed description: Management of cancer is a complex process which involves numerous stakeholders. In view of this, institutions worldwide have adopted the use of Multidisciplinary Tumor Boards (MTBs) for delivery of cancer care. By tapping on the collective specialized knowledge and experience of various specialties, MTBs have been shown in some studies to result in more appropriate recommendations and improved patient outcomes. At our institution, cancer cases are similarly discussed at regular MTBs which comprises surgeons, oncologists, pathologists and radiologists who review and recommend treatments.

However, in smaller centres or centres with limited resources and minimal multi-disciplinary expertise, delivery of timely and appropriate cancer care could be a challenge. Additionally, clinicians, with their busy schedule, may not be able to keep abreast of new developments in cancer research. With rapid advances in scientific research, this pool of knowledge is expected to continue to burgeon, making keeping up-to-date increasingly onerous.

To address this need, clinicians have adopted the use of Clinical Decision Support Systems (CDSSs) to augment clinical care and decision-making. These are platforms which aim to improve healthcare delivery by enhancing medical decisions with targeted clinical knowledge, patient information, and other health information. Various studies have shown CDSSs to be beneficial in selected settings such as patient safety and diagnosis \[4\], and to even increase adherence to clinical guidelines. In recent years, advancements in artificial intelligence have also seen its use expand to include oncologic therapy selection, with IBM's Watson for Oncology (WFO) being the most prominent and only platform in use to-date. In a 2018 study, WFO's ability to provide treatment advice for breast cancer was compared against recommendations from a multidisciplinary board, where it showed a high degree of concordance. Since then, several other studies have sought to examine WFO's ability to provide treatment recommendations for cancer such as ovarian, gastric, lung, cervical and colorectal cancers, with mixed results. In particular, both studies which examined the recommendations for gastric cancers showed a much lower concordance rate compared to other cancers.

In view of the above, we sought to develop an alternative CDSS for oncologic therapy selection through partnership with Ping An Technology (Shenzhen, China), beginning with gastric and esophageal cancer. This would be done in a piecemeal fashion, with the prototype platform utilizing only international guidelines and high-quality published evidence from journals to arrive at case-specific treatment recommendations. This platform would then be evaluated retrospectively and prospectively by comparing its recommendations with that from the multidisciplinary tumor boards of several tertiary care institutions to determine the concordance rate.

Eligibility criteria: A. In discovery and internal retrospective validation part:

1. Patients with primary gastric adenocarcinoma including preinvasive carcinoma or
2. Patients with gastroesophageal junction cancers or
3. Patients with oesophageal cancer including adenocarcinoma, squamous cell carcinoma and preinvasive carcinoma subtypes.

B. In prospective validation part:

1. Patients with primary gastric adenocarcinoma including preinvasive carcinoma or
2. Patients with esophageal or gastroesophageal junction adenocarcinoma

Exclusion Criteria:

A. In discovery and internal retrospective validation part:

1. Patients with other primary cancers involving the stomach or oesophagus
2. Patients with other cancer subtypes
3. Patients with concomitant cancers of other organs

B. In prospective validation part:

1. Patients with esophageal squamous cell carcinoma
2. Patients who participate in clinical trials where the treatment modality is not standard of care

Primary outcomes:
measure: Concordance Rate
timeFrame: 1 to 2 years
Secondary outcomes:
measure: Reason for Discordance
timeFrame: 1 to 2 years
Other outcomes:
Locations:
city: Leipzig
country: Germany
facility: University Hospital Leipzig
city: Kashiwa
country: Japan
facility: National Cancer Centre Hospital East
city: Seoul
country: Korea, Republic of
facility: Seoul National University Hospital
city: Singapore
country: Singapore
facility: National University Hospital
city: Singapore
country: Singapore
facility: National Cancer Centre Singapore
city: Singapore
country: Singapore
facility: Ng Teng Feng General Hospital
city: Singapore
country: Singapore
facility: Tan Tock Seng Hospital
city: Stockholm
country: Sweden
facility: Karolinska Institute Hospital
city: Edinburgh
country: United Kingdom
facility: The University of Edinburgh
Study officials:
References:
citation: Somashekhar SP, Sepulveda MJ, Puglielli S, Norden AD, Shortliffe EH, Rohit Kumar C, Rauthan A, Arun Kumar N, Patil P, Rhee K, Ramya Y. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board. Ann Oncol. 2018 Feb 1;29(2):418-423. doi: 10.1093/annonc/mdx781.