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2. EP12.03-02 Previously Treated Advanced-Disease NSCLC KRAS G12C From a Canadian Multi-Institutional Real-World Evidence Database (CARMA)

Author

Zhan, L.J., primary, Barghout, S., additional, Raptis, S., additional, Al-Agha, F., additional, Popovacki, A., additional, Esfahanian, N., additional, Kasymjanova, G., additional, Proulx-Rocray, F., additional, Chan, S., additional, Richardson, M., additional, Brown, M.C., additional, Patel, D., additional, Dean, M.L., additional, Navani, V., additional, Moore, E., additional, Carvery, L., additional, Yan, E., additional, Cleary-Gosine, J., additional, Gibson, A.J., additional, Hubley, L., additional, Balaratnam, K., additional, Ngo, T., additional, Gill, A., additional, Black, M., additional, Sacher, A., additional, Bradbury, P.A., additional, Shepherd, F., additional, Leighl, N., additional, Cheema, P., additional, Kuruvilla, S., additional, Agulnik, J., additional, Banerji, S., additional, Juergens, R., additional, Blais, N., additional, Cheung, W., additional, Wheatley-Price, P., additional, Liu, G., additional, and Snow, S., additional

Published
2023
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4. EP06.01-001 The Longitudinal Impact of COVID-19 on the Diagnosis and Treatment of Lung Cancer at a Canadian Academic Centre: A Retrospective Chart Review

Author

Rizzolo, A., primary, Kasymjanova, G., additional, Pepe, C., additional, Friedmann, J.E., additional, Small, D., additional, Price-Gallagher, C., additional, Spicer, J., additional, Sirois, C., additional, Lecavalier-Barsoum, M., additional, Khalil, S., additional, Wang, H., additional, Spatz, A., additional, Cohen, V., additional, and Agulnik, J., additional

Published
2022
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5. EP04.02-004 The Patient Impact of Liquid Biopsy - Health-Related Quality of Life in Patients Undergoing Liquid Biopsy for Advanced Non-Small Cell Lung Cancer

Author

Corke, L., primary, Laskin, J., additional, Agulnik, J., additional, Laurie, S., additional, Hao, D., additional, Juergens, R., additional, Fernandes, R., additional, Le, L., additional, Law, J., additional, Ezeife, D., additional, Shookoohi, A., additional, Kasymjanova, G., additional, Kelly, S., additional, Nadon, T., additional, Lanman, R., additional, Kiedrowski, L., additional, and Leighl, N., additional

Published
2022
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13. Validation of Known Radiomics Biomarkers for Post-Treatment Local Response for SBRT-Treated NSCLC, Using Machine Learning.

Author

Ramasamy, G., Kasymjanova, G., Agulnik, J., Tsui, J.M.G., and Muanza, T.M.

Subjects
*CLINICAL decision support systems, *STEREOTACTIC radiotherapy, *NON-small-cell lung carcinoma, *ROOT-mean-squares, *RADIAL basis functions
Abstract

Medical images contain a wealth of pathophysiology information that can be extracted and used for clinical decision support systems. Indeed, radiomics features such as skewness, root mean square [Ben Man Fei Cheung et al. 2021], homogeneity and long-run-high-gray-level-emphasis [Kyle J Lafata et al. 2019] have been shown to predict local response for SBRT-treated NSCLC tumors. This guides personalized medicine and we wish to apply it to our cohort. That said, radiomics features are not stable [Mitchell Chen et al. 2023]. Thus, we attempt to validate for use in our institution. This study investigates the radiomic features of images and clinical parameters obtained from early-stage and oligometastatic non-small cell lung cancer (NSCLC) patients who underwent stereotactic body radiation therapy (SBRT) to predict local control. A single-institution retrospective review of patients' medical records (n = 98 patients; median age = 76 yrs; male/female ratio = 46/52; 116 lesions) treated with SBRT from 2009 to 2022 was conducted. Radiomics features (107 features) extracted from CT planning scans with an open-source software, along with patient clinical data were used. Response to SBRT was analyzed from follow-up scans. Response was defined as per RECIST criteria. Complete response (CR) or partial response (PR) lesions were responders (33 lesions) and stable disease (SD) or progressive disease (PD) were non-responders (83 lesions). Adaptive synthetic (ADASYN) sampling corrected the imbalance in responses. Classification models, which included support vector machines (SVM) with linear or radial basis function (RBF) kernels, random forests, adaptive boosting (AdaBoost) and multi-layer perceptron (MLP), were used. Models were trained using a 5-fold cross-validation scheme. Their performances were measured with the areas under the curve (AUC) of receiver operating characteristic (ROC) plots on the validation folds. Using permutation feature importance, predictive biomarkers were identified. The best model used a MLP classifier and had an AUC of 0.94+/-0.05. Treatment site, performance status, along with radiomic features such as first-order root mean squared intensity and GLSZM gray level non uniformity emerged as the most predictive. Other less but still predictive features included: first order skewness, GLCM joint entropy and cluster shade, GLSZM small-area-low-gray-level-emphasis and size-zone-non-uniformity-normalized, GLDM small-dependence-low-gray-level-emphasis and small-dependence-emphasis. Consistent with previous research, root mean squared intensity and skewness were found to be predictive biomarkers., In contrast, homogeneity and long-run-high-gray-level-emphasis did not emerge as biomarkers for local response prediction. Hence why in-house radiomics feature validation is crucial. This demonstrates the instability of certain predictive radiomic features when applied to external cohorts. [ABSTRACT FROM AUTHOR]

Published
2024
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25. P2.01-04 Reducing Time to Molecular Diagnosis for Advanced NSCLC in the Context of a Reference Testing Center

Author

Ali, A., primary, Singh Tamber, G., additional, Camilleri-Broet, S., additional, Cohen, V., additional, Spicer, J., additional, Wang, H., additional, Chong, G., additional, Munazzit, M., additional, Rousseau, C., additional, Sateren, W., additional, Fernandez, M., additional, Kasymjanova, G., additional, Owen, S., additional, Spatz, A., additional, Van Kempen, L., additional, and Agulnik, J., additional

Published
2018
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27. A012 – CURRENT UTILIZATION OF AEROBIC EXERCISE IN ADULT NEUROLOGICAL REHABILITATION BY CANADIAN PHYSIOTHERAPISTS

Author

Mehta, SP, MacDermid, JC, Butcher, SJ, Pikaluk, BJ, Heynen, NM, Chura, RL, Farthing, JP, Marciniuk, DD, MacKay-Lyons, M, Doyle, L, MacDonald, T, Law, M, Burgos-Martinez, G, Fleet, A, Che, M, MacKenzie, D, Page, S, Boe, S, Woznowski-Vu, A, Preuss, R, Shaw, JA, Connelly, DM, McWilliam, CL, Shaw, J, Sidhu, K, Kearney, C, Keeber, M, McKay, S, Hopkins-Rosseel, D, Bergsma, K, Van Bavel, C, Fricke, M, Swinamer, J, Winn, CS, Tryssenaar, J, Chisholm, BA, Hummelbrunner, JA, Kandler, LS, Jasper, L, Daniels, J, Haennel, RG, Johnson, R, Martin, B, Norman, KE, Booth, R, Chisholm, B, Ellerton, C, Jelley, W, MacPhail, A, Mooney, P, Mori, B, Taipalus, L, Thomas, B, Duval, G, Ghali, S, Nasirian, A, Santillo, G, Yang, XL, Thomas, A, McKinley, P, Kaizer, F, Desveaux, L, Nanavaty, G, Howell, P, Sundar, R, Ryan, J, Verrier, M, Dutton, TL, Langendoen, T, Marshall, J, Coghill, C, Pederson, C, Blechinger, C, Marshall, M, Hamilton, CB, Chesworth, BM, Styles-Tripp, F, Sheps, D, Bury, J, Bouliane, M, Glasgow, R, Otto, D, Luciak-Corea, C, Beaupre, L, Balyk, R, Carson, S, Graham, J, Hopman, W, Parsons, T, Sawant, A, Overend, T, Prasanna, SS, Korner-Bitensky, N, Ahmed, S, O’Donovan, MJ, Driver, H, Randhawa, BK, Farley, BG, Boyd, LA, Henderson, R, Najafi, B, Bansberg, J, Druja, G, Hinch, S, Sikkema, A, Subramanian, SK, LourenÇo, CB, Chilingaryan, G, Sveistrup, H, Levin, MF, King, J, Chamberland, P, Agar, A, Leger, R, Michaels, R, Poitras, R, Rawji, A, Skelton, D, Warren, M, Lavallée, L, LeBlanc, C, McKim, D, Woolnough, A, Cockburn, L, Wango, J, Benuh, E, Cleaver, S, Madill, SJ, Pontbriand-Drolet, S, Prud’homme-Delage, A, Tang, A, Dumoulin, C, Hiemstra, LA, Lafave, M, Kerslake, S, Heard, M, Buchko, G, Mohtadi, N, Auais, M, Eilayyan, O, Mayo, N, Otfinowski, C, Fung, J, Smallhorn, P, Diez, d’Aux N, Shan, He F, Li, L, Ren, Y, Perez, C, Spahija, J, Sadeghi, M, Ebrahimi, S, Maroufi, N, Jamshidi, AA, Chepeha, JC, Magee, DJ, Warren, S, Storey, AST, Brinkman, DM, Bauck, RA, Myrah, AM, Friess, SN, Webber, SC, Taphorn, A, Magnus, CRA, Arnold, CM, Johnston, G, Dal-Bello, Haas V, Basran, J, Krentz, JR, Berardi, D, Brizard, M, Brière, H, Charron, M, Gagnon, I, Tran, T, Kasymjanova, G, Grossman, M, Xenopoulos, T, Jagoe, T, Agulnik, J, Small, D, Kinlin, C, Marlow, T, Donald, LA, Tiessen, S, Cooper, N, Pryse-Phillips, S, Yoshida, K, Teachman, G, Wright, V, Fehlings, D, Young, N, McKeever, P, Parent, EC, Breitkreitz, R, Ladd, J, McIntosh, K, Pauls, D, Urhbach, S, Koppenhaver, S, Alderdice, C, Evans, J, Feldman, S, Robinson, S, White, L, Long, A, McDougall, M, Bonnet, F, Brososky, C, Hopcroft, L, Bester, L, Clement, D, Quigley, A, Sachdeva, M, Rourke, S, Nixon, S, Mendes, P, Robles, P, Mathur, S, Warmington, K, Kennedy, C, Lundon, K, Rozmovits, L, Lineker, S, Shupak, R, Schneider, R, Kennedy, CA, Soever, L, Passalent, L, Katie, Lundon K, Roots, RK, Bainbridge, L, Brown, H, Li, LC, Gillis, K, Augruso, A, Coe, T, O’Neill, A, Radford, L, Gibson, BE, O’Callaghan, L, Bath, B, Janzen, B, Lovo, Grona S, Bourassa, R, Reilly, J, Prendergast, M, Derbyshire, M, Anderson, CM, Friedman, D, Gilbert, G, Lazowski, D, Hurtubise, K, Cote, N, McGlasson, Emery, C, Woodhouse, L, Jones, A, Dickinson, D, Torrance, G, Landry, MD, Murphy, SM, Rivard, LM, Levac, D, Aisen, M, French, EH, Barclay-Goddard, R, Dubouloz, CJ, Schwartz, CE, Jam, B, Manns, PJ, McDonald, A, Ploughman, M, Evans, C, Zhan, J, Stevens, M, Asmundson, Gordon, Yardley, D, Funk, S, Yeung, E, Sinclair, L, Damp, Lowery C, Denehy, L, Ziegler, T, LaRocque, D, Clarke, L, Edge-Hughes, LM, Budiselic, S, Berney, S, Rankin, A, Juricic, M, Peddie, E, Johnson, A, and Seminowicz, DA

Subjects
Innovation in Education, Practice Models and Policy, Divisions, Abstracts, CPA Congress 2012, Proposals, Guest Editorial, Physiotherapy Research: Basic Science through Population Health, Best Practice
Published
2012

30. P3.02-055 Detecting ALK, ROS1 and RET Gene Translocations in Non-Small Cell Lung Cancer (NSCLC) with the NanoString Platform

Author

Wang, H., primary, Rijk, A., additional, Aguirre, M., additional, Wang, A., additional, Wang, K., additional, Dastani, Z., additional, Agulnik, J., additional, Cohen, V., additional, Small, D., additional, Pepe, C., additional, Sakr, L., additional, Kasymjanova, G., additional, Van Kempen, L., additional, and Spatz, A., additional

Published
2017
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32. An exploratory comparative analysis of tyrosine kinase inhibitors or docetaxel in second-line treatment of EGFR wild-type non-small-cell lung cancer: a retrospective real-world practice review at a single tertiary care centre

Author

Ma, K., Cohen, V., Kasymjanova, G., Small, D., Novac, K., Peterson, J., Levit, A., and Agulnik, J.

Subjects
advanced disease, second-line treatment, tyrosine kinase inhibitors, docetaxel, neoplasms, Non-small-cell lung cancer, respiratory tract diseases
Abstract

Treatment for advanced non-small-cell lung cancer (nsclc), especially in patients with wild-type EGFR, remains limited. Recently, erlotinib, a tyrosine kinase inhibitor (tki) targeting EGFR mutation, was approved as second-line treatment in EGFR wild-type nsclc. Despite evidence of better overall survival (os) with chemotherapy than with tki in second-line treatment, data on the use of tki in the real-life clinical setting remain limited. The present practice review of tki use for second- and third-line treatment in EGFR wild-type nsclc also compares clinical outcomes for tki and single-agent docetaxel as second-line treatment. Our retrospective cohort study included patients with EGFR wild-type nsclc treated at the Jewish General Hospital (Montreal, QC) between 2003 and 2013. Patients received a tki (erlotinib or gefitinib) in the second and third line or docetaxel in the second line. For each group, we determined os, disease control rate, progression-free survival (pfs), and event-free survival (efs). The tki group included 145 patients, with 92 receiving second-line treatment. In the control group, 53 patients received docetaxel as second-line therapy. In the tki group, os was 6.0 months, pfs, 2.7 months, and efs, 3.0 months. Comparing second-line treatments, os was 5.3 and 5.0 months respectively (p = 0.88), pfs was 2.5 and 1.8 months respectively (p = 0.041), and efs was 3.0 and 1.7 months respectively (p = 0.009). In our study cohort, second-line therapy for EGFR wild-type nsclc with tki (compared with docetaxel) was associated with statistically better pfs and efs and noninferior os. Those findings raise the question of whether efs should also be considered when choosing second-line treatment in this patient population.

Published
2015
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33. The predictive value of pre-treatment inflammatory markers in advanced non-small-cell lung cancer

Author

Kasymjanova, G., MacDonald, N., Agulnik, J.S., Cohen, V., Pepe, C., Kreisman, H., Sharma, R., and Small, D.

Subjects
Biomarkers in Oncology
Abstract

Accurate prediction of outcome in advanced non-small-cell lung cancer (NSCLC) remains challenging. Even within the same stage and treatment group, survival and response to treatment vary. We set out to determine the predictive value of inflammatory markers C-reactive protein (CRP) and white blood cells (WBCS) in patients with advanced NSCLC.Patients were assigned a prognostic index (PI): 0 for crp 10 mg/L or less and WBCS 11x10⁹/L or less, 1 if one of the two markers was elevated, and 2 if both markers were elevated. We then used chest computed tomography (CT) imaging to evaluate response after 2 cycles of chemotherapy treatment.Of 134 patients, 46 had a PI of 0; 60, a PI of 1; and 28, a PI of 2. Disease progressed in 41 patients. Progression was significantly more frequent among patients with a PI of 2 (p = 0.008). Median survival was 20.0 months for the PI 0 group, 10.4 months for the PI 1 group, and 7.9 months for the PI 2 group (p0.001). The PI was the only significant prognostic factor for survival even after adjustment for performance status, smoking, and weight loss (hazard ratio: 1.57; 95% confidence interval: 1.2 to 2.14; p = 0.004).Inflammatory state correlates significantly with both chemotherapy response and survival in stage IV NSCLC. The PI may provide additional guidance for therapeutic decision-making.

Published
2010

44. Epidermal growth factor receptor (EGFR) mutations detected by denaturing high performance liquid chromatography (dHPLC) in non-small cell lung cancer (NSCLC): Correlation with disease stage and response to tyrosine kinase inhibitors (TKI) therapy

Author

Agulnik, J. S., primary, Cohen, V., additional, Sun, S., additional, Ang, C., additional, Kasymjanova, G., additional, Chong, G., additional, Brandao, G., additional, Pepe, C., additional, Small, D., additional, and Miller, W. H., additional

Published
2008
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48. Clinicopathologic features and prognostic implications of epidermal growth factor receptor (EGFR) gene mutations detected by denaturing high-performance liquid chromatography (dHPLC) in non-small cell lung cancer (NSCLC)

Author

Cohen, V., primary, Agulnik, J. S., additional, Ang, C., additional, Kasymjanova, G., additional, Chong, G., additional, Tejada, N. A., additional, Pepe, C., additional, Batist, G., additional, Small, D., additional, and Miller, W. H., additional

Published
2007
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