Characterizing the patient experience during neoadjuvant therapy for pancreatic ductal adenocarcinoma: A qualitative study.

BACKGROUND: Neoadjuvant therapy (NT) has increasingly been utilized for patients with localized pancreatic ductal adenocarcinoma (PDAC). It is the recommended approach for borderline resectable (BR) and locally advanced (LA) cancers and an increasingly utilized option for potentially resectable (PR) disease. Despite its increased use, little research has focused on patient-centered metrics among patients undergoing NT, including patient experiences, preferences, and recommendations. A better understanding of all aspects of the patient experience during NT may identify opportunities to design interventions aimed at improving quality of life; it may also facilitate the completion of NT and receipt of surgery, ultimately optimizing long-term outcomes. AIM: To understand the experience of patients initiating and receiving NT to identify opportunities to improve neoadjuvant cancer care delivery. METHODS: Semi-structured interviews of patients with localized PDAC during NT were conducted to explore their experience initiating and receiving NT. Interviews took place between August 2020 and October 2021. Due to the descriptive nature of the research, questions were open ended. Interviews were conducted over the phone, audio recorded and then transcribed. All interviews were coded by two independent researchers using NVivo 12, iteratively identifying themes until thematic saturation was achieved. An integrative approach to qualitative analysis was used, utilizing both inductive and deductive methods. RESULTS: A total of 12 patients with localized PDAC were interviewed. Patients with BR (n = 7), PR (n = 2), and LA (n = 3) cancers participated in the study. All patients indicated that choosing NT was the doctor's recommendation, while most reported not being familiar with the concept of NT (n = 11) and that NT was presented as the only option (n = 8). Five themes describing the patient experience emerged: physical symptoms, emotional symptoms, coping mechanisms, access to care, and life factors. The most commonly cited recommendation for improving the experience of NT was improved education before and during NT (n = 7). Patients highlighted the need for more information on the rationale behind choosing NT prior to surgery, the anticipated surgery and its likelihood of surgery occurring after NT, as well as general information prior to starting NT treatment. The need for seeing different members of the healthcare team, including ancillary services was also frequently cited as a recommendation for improving the experience of NT (n = 5). CONCLUSION: This study provides a framework to allow for a better understanding of the PDAC patient experience during NT and highlights opportunities to improve quality and quantity of life outcomes.

Textbook outcomes in hepatobiliary and pancreatic surgery.

The concept of textbook outcome (TO) has recently gained popularity in surgical research and has been used to evaluate the quality or success of different surgical procedures, including hepatopancreatobiliary (HPB) operations. TO consists of individual outcome parameters that each reflect different domains of care including structure, process, and individual outcomes; in turn, the composite TO metric represents the optimal course after a surgical episode. TO can be used to assess patient-level outcomes, hospital performance, center designation and quality metrics. In addition to being an outcome measurement, TO may also be linked to healthcare costs. Future efforts should be directed towards establishing a universal definition of TO in HPB surgery so that surgeons and hospitals can assess and compare outcomes, identify shortcomings and improve real world patient outcomes.

Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review.

BACKGROUND: Prediction of survival after the treatment of hepatocellular carcinoma (HCC) has been widely investigated, yet remains inadequate. The application of artificial intelligence (AI) is emerging as a valid adjunct to traditional statistics due to the ability to process vast amounts of data and find hidden interconnections between variables. AI and deep learning are increasingly employed in several topics of liver cancer research, including diagnosis, pathology, and prognosis. AIM: To assess the role of AI in the prediction of survival following HCC treatment. METHODS: A web-based literature search was performed according to the Preferred Reporting Items for Systemic Reviews and Meta-Analysis guidelines using the keywords "artificial intelligence", "deep learning" and "hepatocellular carcinoma" (and synonyms). The specific research question was formulated following the patient (patients with HCC), intervention (evaluation of HCC treatment using AI), comparison (evaluation without using AI), and outcome (patient death and/or tumor recurrence) structure. English language articles were retrieved, screened, and reviewed by the authors. The quality of the papers was assessed using the Risk of Bias In Non-randomized Studies of Interventions tool. Data were extracted and collected in a database. RESULTS: Among the 598 articles screened, nine papers met the inclusion criteria, six of which had low-risk rates of bias. Eight articles were published in the last decade; all came from eastern countries. Patient sample size was extremely heterogenous (n = 11-22926). AI methodologies employed included artificial neural networks (ANN) in six studies, as well as support vector machine, artificial plant optimization, and peritumoral radiomics in the remaining three studies. All the studies testing the role of ANN compared the performance of ANN with traditional statistics. Training cohorts were used to train the neural networks that were then applied to validation cohorts. In all cases, the AI models demonstrated superior predictive performance compared with traditional statistics with significantly improved areas under the curve. CONCLUSION: AI applied to survival prediction after HCC treatment provided enhanced accuracy compared with conventional linear systems of analysis. Improved transferability and reproducibility will facilitate the widespread use of AI methodologies.

Neoadjuvant treatment strategies for intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver malignancy and is increasing in incidence. Long-term outcomes are optimized when patients undergo margin-negative resection followed by adjuvant chemotherapy. Unfortunately, a significant proportion of patients present with locally advanced, unresectable disease. Furthermore, recurrence rates are high even among patients who undergo surgical resection. The delivery of systemic and/or liver-directed therapies prior to surgery may increase the proportion of patients who are eligible for surgery and reduce recurrence rates by prioritizing early systemic therapy for this aggressive cancer. Nevertheless, the available evidence for neoadjuvant therapy in ICC is currently limited yet recent advances in liver directed therapies, chemotherapy regimens, and targeted therapies have generated increasing interest its role. In this article, we review the rationale for, current evidence for, and ongoing research efforts in the use of neoadjuvant therapy for ICC.