Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN99301435)
(2026) In BMC Cancer 26(1).- Abstract
Background: The integration of clinical decision support tools in medical practice is challenging and must be carefully undertaken, especially in cancer management. Noninvasive Lymph Node Status (NILS) is a web-based tool designed to estimate the probability of benign axillary lymph nodes in female patients with breast cancer scheduled for primary surgery. The aim was to identify barriers to NILS adoption in a clinical setting and assess whether intended users can operate the tool without significant errors or difficulties. Additionally, the study aimed to evaluate the appropriateness of result interpretation for decisions to abstain from sentinel lymph node biopsy (SNLB) and measure overall user satisfaction with the tool. Methods:... (More)
Background: The integration of clinical decision support tools in medical practice is challenging and must be carefully undertaken, especially in cancer management. Noninvasive Lymph Node Status (NILS) is a web-based tool designed to estimate the probability of benign axillary lymph nodes in female patients with breast cancer scheduled for primary surgery. The aim was to identify barriers to NILS adoption in a clinical setting and assess whether intended users can operate the tool without significant errors or difficulties. Additionally, the study aimed to evaluate the appropriateness of result interpretation for decisions to abstain from sentinel lymph node biopsy (SNLB) and measure overall user satisfaction with the tool. Methods: This mixed-methods multicenter on-site qualitative human factor validation study was conducted in a simulated clinical environment, replicating both real-world physical and digital conditions. Based on the identified target user population for the NILS model, twenty physicians comprised the cohort. The study used simulated clinical cases, the System Usability Scale (SUS), and the After-Scenario Questionnaire (ASQ) to evaluate usability and satisfaction. An oral interview was conducted after the evaluations. The study followed a structured protocol, with distinct roles assigned to the test participants, leader, and observer. Results: Twenty physicians from four hospitals, with a median of 9.5 years of specialist practice, participated. Most participants were surgeons (75%, N = 15), while the remaining 25% (N = 5) were oncologists. Usability scores were high, with a mean SUS score of 89.5 (“excellent”) and a mean ASQ score of 6.3 (Likert scale 1–7). Several interface challenges were identified, including difficulty in locating the reset and information buttons, the ability to enter values outside valid ranges (age and tumor size), and the risk of unintentionally modifying the entered values while scrolling. Conclusions: This study identified the key usability factors, barriers, and facilitators affecting the NILS model implementation. Physicians found the NILS interface easy to use and valued the presented risk estimates of benign axillary lymph node status in their decisions to perform or abstain from SLNB. Study-informed interface redesigns have been implemented. Iterative usability work in clinical settings is crucial for successful implementation. Trial registration: ISRCTN99301435.
(Less)
- author
- Allfelt, Anna
LU
; Bendahl, Pär Ola
LU
; Dihge, Looket
LU
; Ohlsson, Mattias
LU
; Rydén, Lisa
LU
and Skarping, Ida
LU
- organization
-
- LUCC: Lund University Cancer Centre
- PCDT
- Surgery (Lund)
- The Liquid Biopsy and Tumor Progression in Breast Cancer (research group)
- Surgery (research group)
- Breast Cancer Surgery (research group)
- Department of Earth and Environmental Sciences (MGeo)
- LU Profile Area: Natural and Artificial Cognition
- eSSENCE: The e-Science Collaboration
- Artificial Intelligence in CardioThoracic Sciences (AICTS) (research group)
- Department Office of Clinical Sciences, Malmö
- Breast cancer prevention & intervention (research group)
- publishing date
- 2026-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Axillary lymph nodes, Breast neoplasm, Decision aid, Human factors validation study, Sentinel lymph node biopsy, Staging
- in
- BMC Cancer
- volume
- 26
- issue
- 1
- article number
- 691
- publisher
- BioMed Central (BMC)
- external identifiers
-
- pmid:42204510
- scopus:105040512336
- ISSN
- 1471-2407
- DOI
- 10.1186/s12885-026-16161-5
- language
- English
- LU publication?
- yes
- id
- 964a3426-e844-4a7b-a3df-f8586833b88c
- date added to LUP
- 2026-08-24 08:50:28
- date last changed
- 2026-09-10 14:12:12
@article{964a3426-e844-4a7b-a3df-f8586833b88c,
abstract = {{<p>Background: The integration of clinical decision support tools in medical practice is challenging and must be carefully undertaken, especially in cancer management. Noninvasive Lymph Node Status (NILS) is a web-based tool designed to estimate the probability of benign axillary lymph nodes in female patients with breast cancer scheduled for primary surgery. The aim was to identify barriers to NILS adoption in a clinical setting and assess whether intended users can operate the tool without significant errors or difficulties. Additionally, the study aimed to evaluate the appropriateness of result interpretation for decisions to abstain from sentinel lymph node biopsy (SNLB) and measure overall user satisfaction with the tool. Methods: This mixed-methods multicenter on-site qualitative human factor validation study was conducted in a simulated clinical environment, replicating both real-world physical and digital conditions. Based on the identified target user population for the NILS model, twenty physicians comprised the cohort. The study used simulated clinical cases, the System Usability Scale (SUS), and the After-Scenario Questionnaire (ASQ) to evaluate usability and satisfaction. An oral interview was conducted after the evaluations. The study followed a structured protocol, with distinct roles assigned to the test participants, leader, and observer. Results: Twenty physicians from four hospitals, with a median of 9.5 years of specialist practice, participated. Most participants were surgeons (75%, N = 15), while the remaining 25% (N = 5) were oncologists. Usability scores were high, with a mean SUS score of 89.5 (“excellent”) and a mean ASQ score of 6.3 (Likert scale 1–7). Several interface challenges were identified, including difficulty in locating the reset and information buttons, the ability to enter values outside valid ranges (age and tumor size), and the risk of unintentionally modifying the entered values while scrolling. Conclusions: This study identified the key usability factors, barriers, and facilitators affecting the NILS model implementation. Physicians found the NILS interface easy to use and valued the presented risk estimates of benign axillary lymph node status in their decisions to perform or abstain from SLNB. Study-informed interface redesigns have been implemented. Iterative usability work in clinical settings is crucial for successful implementation. Trial registration: ISRCTN99301435.</p>}},
author = {{Allfelt, Anna and Bendahl, Pär Ola and Dihge, Looket and Ohlsson, Mattias and Rydén, Lisa and Skarping, Ida}},
issn = {{1471-2407}},
keywords = {{Axillary lymph nodes; Breast neoplasm; Decision aid; Human factors validation study; Sentinel lymph node biopsy; Staging}},
language = {{eng}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Cancer}},
title = {{Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN99301435)}},
url = {{http://dx.doi.org/10.1186/s12885-026-16161-5}},
doi = {{10.1186/s12885-026-16161-5}},
volume = {{26}},
year = {{2026}},
}