R Nandra1, J Forsberg2, R Grimer3. 1. Bone Tumor Service, The Royal Orthopaedic Hospital, Bristol Road South, Birmingham B31 2AP, United Kingdom. Electronic address: rajpalnandra@nhs.net. 2. Section of Orthopaedics and Sports Medicine, Department of Molecular Medicine and Surgery, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden. Electronic address: jonathan.forsberg@ki.se. 3. Bone Tumor Service, The Royal Orthopaedic Hospital, Bristol Road South, Birmingham B31 2AP, United Kingdom.
Abstract
AIM: Only 1 in 100 of primary care consultations regarding new soft tissue lumps (STL) are malignant and are susceptible to a delay in diagnosis. We aimed to generate a Bayesian Belief Network to estimate the likelihood of malignancy in patients to facilitate the initial evaluation of a STL and improve timing and quality of referrals to specialist treatment centres. METHODS: We evaluated all patients referred with a new STL between 1996 and 2007. Variables investigated focused on patient factors, symptoms and STL characteristics. Relevant data was extracted and coded for statistical analysis. RESULTS: 3018 patients with a STL were assessed, of which 1563 (52%) were benign and 1455 (48%) malignant. The features most conditionally associated with the outcome of interest (Benign or Malignant) are referred to as first-degree associates, and are increasing size, age, size of the lump, and duration of symptoms, in that order. On cross validation, this model demonstrated an AUC of 0.77 (95%C.I. 0.75-0.79). CONCLUSIONS: For the first time, we have described the hierarchal relationship between factors and created an aide memoire, larger than a golf ball and growing, to trigger referral to tertiary tumor units. Importantly, we found pain to be a poor discriminatory factor. We hope our findings will lead to greater awareness and earlier diagnosis of STL.
AIM: Only 1 in 100 of primary care consultations regarding new soft tissue lumps (STL) are malignant and are susceptible to a delay in diagnosis. We aimed to generate a Bayesian Belief Network to estimate the likelihood of malignancy in patients to facilitate the initial evaluation of a STL and improve timing and quality of referrals to specialist treatment centres. METHODS: We evaluated all patients referred with a new STL between 1996 and 2007. Variables investigated focused on patient factors, symptoms and STL characteristics. Relevant data was extracted and coded for statistical analysis. RESULTS: 3018 patients with a STL were assessed, of which 1563 (52%) were benign and 1455 (48%) malignant. The features most conditionally associated with the outcome of interest (Benign or Malignant) are referred to as first-degree associates, and are increasing size, age, size of the lump, and duration of symptoms, in that order. On cross validation, this model demonstrated an AUC of 0.77 (95%C.I. 0.75-0.79). CONCLUSIONS: For the first time, we have described the hierarchal relationship between factors and created an aide memoire, larger than a golf ball and growing, to trigger referral to tertiary tumor units. Importantly, we found pain to be a poor discriminatory factor. We hope our findings will lead to greater awareness and earlier diagnosis of STL.
Authors: Maria Anna Smolle; Dimosthenis Andreou; Per-Ulf Tunn; Joanna Szkandera; Bernadette Liegl-Atzwanger; Andreas Leithner Journal: EFORT Open Rev Date: 2017-10-17
Authors: Joshua M Lawrenz; James P Norris; Marcus C Tan; Eric T Shinohara; John J Block; Elizabeth J Davis; Vicki L Keedy; Jennifer L Halpern; Ginger E Holt; Herbert S Schwartz Journal: Int J Surg Oncol Date: 2020-12-07
Authors: Madelaine Hettler; Julia Kitz; Ali Seif Amir Hosseini; Manuel Guhlich; Babak Panahi; Jennifer Ernst; Lena-Christin Conradi; Michael Ghadimi; Philipp Ströbel; Jens Jakob Journal: Cancers (Basel) Date: 2022-09-05 Impact factor: 6.575
Authors: Eugenie Younger; Olga Husson; Lindsey Bennister; Jeremy Whelan; Roger Wilson; Andy Roast; Robin L Jones; Winette Ta van der Graaf Journal: BMC Cancer Date: 2018-10-17 Impact factor: 4.430
Authors: Mohammed H A Alramdan; Ömer Kasalak; Lukas B Been; Albert J H Suurmeijer; Derya Yakar; Thomas C Kwee Journal: Skeletal Radiol Date: 2021-04-26 Impact factor: 2.199