ABSTRACT Non-pancreatic periampullary tumors have long been neglected, leading to blurred adjuvant treatment strategies. Recent research, like the ISGACA group’s study, is uncovering nuances

in chemotherapy efficacy for these diverse cancers. Tailored approaches show promise, with artificial intelligence (AI) aiding in personalized treatment plans. Periampullary cancer presents

a multifaceted and demanding oncological challenge, encompassing a diverse spectrum of tumors located in and around the Ampulla of Vater. While pancreatic ductal adenocarcinoma (PDAC)

stands as the most prevalent, other non-pancreatic malignancies, such as ampullary adenocarcinoma (comprising intestinal AmpIT or pancreaticobiliary AmpPB), duodenal adenocarcinoma (DAC),

strategies. In the current issue of the British Journal of Cancer, the ISGACA group presents an international multimethod cohort study evaluating the efficacy of various adjuvant

chemotherapy regimens for non-pancreatic periampullary cancers. The authors shed light on the intricacies of treatment outcomes in this patient population. Although the findings are nuanced

and at times inconclusive, they offer valuable insights into tailoring adjuvant therapies for different subtypes of non-pancreatic periampullary cancers. The overarching conclusion of the

study suggests that while adjuvant therapy may not universally improve overall survival (OS) and disease-free interval (DFI) for all non-pancreatic periampullary cancers, distinct benefits

were observed for certain subtypes. Notably, patients with ampullary adenocarcinoma (AmpPB) and distal cholangiocarcinoma (dCCA) exhibited improved OS with adjuvant chemotherapy regimens,

indicating the potential for tailored treatment approaches. In the context of AmpPB, the study emphasizes the need for further exploration into optimal adjuvant chemotherapy. Although

conclusive determinations regarding the most effective regimen were not reached, the data hint at a potential advantage of adjuvant treatment, especially for AmpPB, and not for AmpIT. This

underscores the ongoing importance of randomized studies to clarify the effectiveness of different treatment modalities and pinpoint histopathologic subsets that might experience greater

benefits. Similarly, concerning distal cholangiocarcinoma, the study echoes previous findings from the BILCAP trial, endorsing the use of capecitabine monotherapy as a standard adjuvant

treatment [3]. Interestingly, no significant improvement in survival outcomes from adjuvant chemotherapy was noted for DAC. Acknowledging the limitations such as variability in tumor

classification techniques, local treatment protocols, and incomplete data on chemotherapy dosages and completion rates, the study’s international multicenter approach stands as a notable

strength, providing valuable real-world insights into the effectiveness of adjuvant chemotherapy across diverse clinical settings. From a surgical perspective, whether the choice between

open, laparoscopic, or robotic pancreaticoduodenectomy techniques may affect decisions regarding adjuvant treatment remains unclear. Differences in operative complexity and postoperative

recovery could impact the timing and type of adjuvant therapy recommended. Therefore, surgical technique selection should also be studied in the context of subsequent adjuvant therapy

planning. Irrespective, the current paper by Uijterwijk et al. lays the groundwork for future research endeavors aimed at refining personalized adjuvant treatment approaches for

non-pancreatic periampullary cancers. While the study marks a significant progression in understanding the intricacies of adjuvant chemotherapy for non-pancreatic periampullary cancers, it

also underscores the imperative for ongoing research to elucidate optimal treatment approaches tailored to individual tumor subtypes. Given that cancer treatment is nowadays increasingly

algorithmic and data-centric, the integration of artificial intelligence (AI) in the management of non-pancreatic periampullary cancer presents a substantial opportunity in precision

oncology. Through the utilization of extensive datasets and machine learning algorithms, AI provides unparalleled prospects for customizing adjuvant treatment strategies for these intricate

malignancies. An essential advantage of AI lies in its capacity to amalgamate data from diverse origins, encompassing radiomics, genomics, oncopathomics, and surgomics, aspects not fully

explored in the ISGACA population cohort. Customized care for these inherently diverse malignancies necessitates a comprehensive approach that incorporates data from various sources and

utilizes AI to construct personalized treatment algorithms. Looking ahead, there is a call for research endeavors aimed at constructing and validating AI-driven predictive models for

non-pancreatic periampullary tumors. These endeavors should concentrate on amalgamating radiomics, genomics, oncopathomics, and surgomics data to formulate inclusive decision support tools

empowering clinicians to refine adjuvant treatment strategies based on individual patient traits and tumor biology. A parallel endeavor has been undertaken recently for pancreatic ductal

adenocarcinoma through the AiRGOS project [4]. In conclusion, the study presented by the ISGACA group offers valuable insights into the complexities of adjuvant chemotherapy for

non-pancreatic periampullary cancers. While it underscores the challenges and uncertainties in treatment decision-making, it also highlights the potential for tailored approaches to improve

outcomes for patients with specific tumor subtypes. Moreover, the integration of artificial intelligence in precision oncology holds promise for further optimizing adjuvant treatment

strategies and advancing personalized care for these complex malignancies. By leveraging AI and integrating data from multiple sources, clinicians can move towards a future of truly tailored

treatment approaches, improving outcomes for patients with non-pancreatic periampullary cancers. REFERENCES * Erdmann JI, Eskens FA, Vollmer CM, Kok NF, Groot Koerkamp B, Biermann K, et al.

Histological and molecular subclassification of pancreatic and nonpancreatic periampullary cancers: implications for (Neo) adjuvant systemic treatment. Ann Surg Oncol. 2015;22:2401–7.

https://doi.org/10.1245/s10434-014-4267-4 Article  CAS  PubMed  Google Scholar  * Conroy T, Castan F, Lopez A, Turpin A, Ben Abdelghani M, Wei AC, et al. Five-year outcomes of FOLFIRINOX vs

gemcitabine as adjuvant therapy for pancreatic cancer. JAMA Oncol. 2022;8:1571. https://doi.org/10.1001/jamaoncol.2022.3829 Article  PubMed  PubMed Central  Google Scholar  * Rizzo A, Brandi

G. BILCAP trial and adjuvant capecitabine in resectable biliary tract cancer: reflections on a standard of care. Expert Rev Gastroenterol Hepatol. 2021;15:483–5.

https://doi.org/10.1080/17474124.2021.1864325 Article  CAS  PubMed  Google Scholar  * Gumbs AA, Croner R, Abu-Hilal M, Bannone E, Ishizawa T, Spolverato G, et al. Surgomics and the

artificial intelligence, radiomics, genomics, oncopathomics and surgomics (AiRGOS) project. Artif Intell Surg. 2023;3:180–5. https://doi.org/10.20517/ais.2023.24 Article  Google Scholar 

Download references AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Hepatopancreatobiliary Surgery, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)

and Europe Hospitals, Brussels, Belgium Nouredin Messaoudi & Aude Vanlander * Department of General-, Visceral-, Vascular- and Transplantation Surgery, University of Magdeburg,

Magdeburg, Germany Andrew A. Gumbs * Department of Advanced & Minimally Invasive Surgery, American Hospital of Tbilisi, Tbilisi, Republic of Georgia Andrew A. Gumbs Authors * Nouredin

Messaoudi View author publications You can also search for this author inPubMed Google Scholar * Aude Vanlander View author publications You can also search for this author inPubMed Google

Scholar * Andrew A. Gumbs View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Nouredin Messaoudi: Editing, Supervision. Aude Vanlander: Writing

of original draft. Andrew A. Gumbs: Conceptualization, Administrative, Supervision, Editing. CORRESPONDING AUTHOR Correspondence to Andrew A. Gumbs. ETHICS DECLARATIONS COMPETING INTERESTS

Professor Gumbs is the Editor-in-Chief of the journal Artificial Intelligence Surgery, the CEO of Talos Surgical. Professors Gumbs and Messaoudi are co-author on the AiRGOS paper cited in

the references. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. RIGHTS AND

PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Messaoudi, N., Vanlander, A. & Gumbs, A.A. Optimizing adjuvant treatment strategies for non-pancreatic

periampullary cancers. _Br J Cancer_ 131, 617–618 (2024). https://doi.org/10.1038/s41416-024-02808-2 Download citation * Received: 03 April 2024 * Revised: 25 April 2024 * Accepted: 22 July

2024 * Published: 31 July 2024 * Issue Date: 07 September 2024 * DOI: https://doi.org/10.1038/s41416-024-02808-2 SHARE THIS ARTICLE Anyone you share the following link with will be able to

read this content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing

initiative