Publications by authors named "L Nissi"

3 Publications

  • Page 1 of 1

Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit.

ESMO Open 2021 Jun 3;6(3):100175. Epub 2021 Jun 3.

University of Turku, Turku, Finland; Department of Oncology, Turku University Hospital, Turku, Finland; FICAN West Cancer Centre, Turku, Finland. Electronic address:

Background: Persistent smoking after cancer diagnosis is associated with increased overall mortality (OM) and cancer mortality (CM). According to the 2020 Surgeon General's report, smoking cessation may reduce CM but supporting evidence is not wide. Use of deep learning-based modeling that enables universal natural language processing of medical narratives to acquire population-based real-life smoking data may help overcome the challenge. We assessed the effect of smoking status and within-1-year smoking cessation on CM by an in-house adapted freely available language processing algorithm.

Materials And Methods: This cross-sectional real-world study included 29 823 patients diagnosed with cancer in 2009-2018 in Southwest Finland. The medical narrative, International Classification of Diseases-10th edition codes, histology, cancer treatment records, and death certificates were combined. Over 162 000 sentences describing tobacco smoking behavior were analyzed with ULMFiT and BERT algorithms.

Results: The language model classified the smoking status of 23 031 patients. Recent quitters had reduced CM [hazard ratio (HR) 0.80 (0.74-0.87)] and OM [HR 0.78 (0.72-0.84)] compared to persistent smokers. Compared to never smokers, persistent smokers had increased CM in head and neck, gastro-esophageal, pancreatic, lung, prostate, and breast cancer and Hodgkin's lymphoma, irrespective of age, comorbidities, performance status, or presence of metastatic disease. Increased CM was also observed in smokers with colorectal cancer, men with melanoma or bladder cancer, and lymphoid and myeloid leukemia, but no longer independently of the abovementioned covariates. Specificity and sensitivity were 96%/96%, 98%/68%, and 88%/99% for never, former, and current smokers, respectively, being essentially the same with both models.

Conclusions: Deep learning can be used to classify large amounts of smoking data from the medical narrative with good accuracy. The results highlight the detrimental effects of persistent smoking in oncologic patients and emphasize that smoking cessation should always be an essential element of patient counseling.
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http://dx.doi.org/10.1016/j.esmoop.2021.100175DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182259PMC
June 2021

Recurrence of head and neck squamous cell carcinoma in relation to high-risk treatment volume.

Clin Transl Radiat Oncol 2021 Mar 3;27:139-146. Epub 2021 Feb 3.

Department of Oncology, University of Turku and Turku University Hospital, Turku, Finland.

Background: Locoregional recurrence remains a major cause of failure in head and neck squamous cell carcinoma (HNSCC). Human papilloma virus (HPV)-associated HNSCCs generally have a good prognosis but may recur even after standard photon radiotherapy (RT). Another incentive in observing patterns of recurrence is increased use of highly conformal techniques such as proton therapy. We therefore studied geographic distribution of recurrent tumors in relation to the high-risk treatment volume in a cohort of patients with HNSCC receiving combined modality therapy.

Methods: Medical records of 508 patients diagnosed with HNSCC in 2010-2015 were reviewed. We identified a subgroup that had local and/or regional recurrence at hybrid positron emission tomography (PET)/computed tomography (CT) and/or magnetic resonance imaging (MRI). We adapted p16 as a surrogate marker for HPV-positivity and only patients with known p16 status were eligible for a detailed analysis where recurrent tumor was copied on the planning CT and the dose received by the recurrent tumor volume was determined using dose-volume histograms.

Results: Twenty-five patients who had received either cisplatin (n = 23) or cetuximab-enhanced (n = 2) RT were identified. 31 locoregional recurrent tumors were detected among 18 p16 negative and 7 p16 positive patients. Of recurrent tumors 14 (45%) were classified as in-field, 5 (16%) as marginal miss, and 12 (39%) as true miss. p16 positive patients had 4 in-field, 2 marginal, and 1 true miss. By contrast, p16 negative patients had 10 in-field, 3 marginal, and 11 true miss recurrences.

Conclusions: Both p16 positive and negative HNSCC recur in high-risk treatment volume despite the common view of high radiosensitivity of the former. Biomarkers predicting radioresistance should be characterized in p16 positive tumors before widely embarking on de-escalated CRT protocols. Another concern is how to decrease the number of true or marginal misses in p16 negative cases despite multimodality imaging-based target delineation.
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http://dx.doi.org/10.1016/j.ctro.2021.01.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902285PMC
March 2021

Electrophoretic mobility as a tool to separate immune adjuvant saponins from Quillaja saponaria Molina.

Int J Pharm 2015 Jun 31;487(1-2):39-48. Epub 2015 Mar 31.

Institut für Laboratoriumsmedizin, Klinische Chemie und Pathobiochemie, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum, Augustenburger Platz 1, D-13353 Berlin, Germany. Electronic address:

Quillaja saponins are used as adjuvants in animal vaccines but their application in human vaccination is still under investigation. Isolation and characterization of adjuvant saponins is very tedious. Furthermore, standardization of Quillaja saponins is critical pertaining to its application in humans. In this study, a convenient method based on agarose gel electrophoresis was developed for the separation of Quillaja saponins. Six different commercial Quillaja saponins were segregated by size/charge into numerous fractions. Each of the fractions was characterized by ESI-TOF-MS spectroscopy and thin layer chromatography. Real-time impedance-based monitoring and red blood cell lysis assay were used to evaluate cytotoxicity and hemolytic activities respectively. Two specific regions in the agarose gel (delimited by specific relative electrophoretic mobility values) were identified and characterized by exclusive migration of acylated saponins known to possess immune adjuvant properties (0.18-0.58), and cytotoxic and hemolytic saponins (0.18-0.94). In vivo experiments in mice with the isolated fractions for evaluation of adjuvant activity also correlated with the relative electrophoretic mobility. In addition to the separation of specific Quillaja saponins with adjuvant effects as a pre-purification step to HPLC, agarose gel electrophoresis stands out as a new method for rapid screening, separation and quality control of saponins.
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http://dx.doi.org/10.1016/j.ijpharm.2015.03.063DOI Listing
June 2015