Research Spotlight

Malec, J. F., J. M. Ketchum, F. M. Hammond, J. D. Corrigan, K. Dams-O’Connor, T. Hart, T. Novack, M. Dahdah, G. G. Whiteneck and J. Bogner (2019). “Longitudinal Effects of Medical Comorbidities on Functional Outcome and Life Satisfaction After Traumatic Brain Injury: An Individual Growth Curve Analysis of NIDILRR Traumatic Brain Injury Model System Data.” J Head Trauma Rehabil Feb 27. [Epub ahead of print].

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OBJECTIVE: To explore associations of specific physical and neuropsychiatric medical conditions to motor and cognitive functioning and life satisfaction over the first 10 years following traumatic brain injury (TBI). SETTING: Telephone follow-up through 6 TBI Model System centers. PARTICIPANTS: In total, 404 individuals or proxies with TBI enrolled in the TBI Model System longitudinal study participating in 10-year follow-up. DESIGN: Individual growth curve analysis. MAIN MEASURES: FIM Motor and Cognitive subscales, Satisfaction With Life Scales, and Medical and Mental Health Comorbidities Interview. RESULTS: Hypertension, diabetes, cancers, rheumatoid arthritis, and anxiety negatively affected the trajectory of motor functioning over time. Diabetes, cancers, chronic bronchitis, anxiety, and depression negatively impacted cognitive functioning. Numerous neuropsychiatric conditions (sleep disorder, alcoholism, drug addiction, anxiety, panic attacks, posttraumatic stress disorder, depression, and bipolar disorder), as well as hypertension, liver disease, and cancers, diminished life satisfaction. Other medical conditions had a negative effect on functioning and satisfaction at specific follow-up periods. CONCLUSION: Natural recovery after TBI may include delayed onset of functional decline or early recovery, followed by progressive deterioration, and is negatively affected by medical comorbidities. Results contribute to the growing evidence that TBI is most appropriately treated as a chronic medical condition complicated by a variety of comorbid conditions.

Menter, A., B. E. Strober, D. H. Kaplan, D. Kivelevitch, E. F. Prater, B. Stoff, A. W. Armstrong, C. Connor, K. M. Cordoro, D. M. R. Davis, B. E. Elewski, J. M. Gelfand, K. B. Gordon, A. B. Gottlieb, A. Kavanaugh, M. Kiselica, N. J. Korman, D. Kroshinsky, M. Lebwohl, C. L. Leonardi, J. Lichten, H. W. Lim, N. N. Mehta, A. S. Paller, S. L. Parra, A. L. Pathy, R. N. Rupani, M. Siegel, E. B. Wong, J. J. Wu, V. Hariharan and C. A. Elmets (2019). “Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with biologics.” J Am Acad Dermatol Feb 13. [Epub ahead of print].

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Psoriasis is a chronic, inflammatory multisystem disease that affects up to 3.2% of the US population. This guideline addresses important clinical questions that arise in psoriasis management and care, providing recommendations based on the available evidence. The treatment of psoriasis with biologic agents will be reviewed, emphasizing treatment recommendations and the role of the dermatologist in monitoring and educating patients regarding benefits as well as associated risks.

Levy, M. Y., L. J. McGarry, H. Huang, S. Lustgarten, S. Chiroli and S. Iannazzo (2019). “Benefits and risks of ponatinib versus bosutinib following treatment failure of two prior tyrosine kinase inhibitors in patients with chronic phase chronic myeloid leukemia: a matching-adjusted indirect comparison.” Curr Med Res Opin 35(3): 479-487.

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OBJECTIVE: Comparing the benefit-risk profiles of ponatinib vs. bosutinib in third-line (3L) treatment of chronic phase chronic myeloid leukemia (CP-CML) is challenging because their pivotal trials lacked comparator arms. To characterize the overall benefit-risk profile in 3L CP-CML patients treated with bosutinib vs. ponatinib, a matching-adjusted indirect comparison (MAIC) was performed to compare efficacy outcomes and treatment duration after adjusting for trial subjects’ baseline characteristics, and tolerability was assessed with an unadjusted comparison of study-drug discontinuation. METHODS: The MAIC was performed using published data from the pivotal bosutinib trial and the most recent individual-patient-level data on file from the pivotal ponatinib trial. RESULTS: Responses were more frequent and durable with ponatinib (n = 70 MAIC-adjusted) than with bosutinib (n = 119) – complete cytogenetic response (CCyR): 61% vs. 26%; Kaplan-Meier estimate of maintaining CCyR at 4 years: 89% vs. 54%. Median treatment duration was longer with ponatinib than with bosutinib: 38.4 vs. 8.6 months. Only 9% of ponatinib patients (n = 97 unadjusted) vs. 42% of bosutinib patients discontinued due to death, disease progression or unsatisfactory response; 19% vs. 24% discontinued due to adverse events. CONCLUSIONS: Based on these surrogate measures of patient benefit-risk profiles, ponatinib appears to provide a net overall benefit vs. bosutinib in 3L CP-CML.

Kandimalla, R., T. Ozawa, F. Gao, X. Wang and A. Goel (2019). “Gene Expression Signature in Surgical Tissues and Endoscopic Biopsies Identifies High-risk T1 Colorectal Cancers.” Gastroenterology Feb 21. [Epub ahead of print].

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We for the first time identify and validate a novel, mRNA-based signature for the identification of LNM in submucosal T1 CRC patients. Although we are enthused by the performance of our biomarkers even in pre-surgical biopsies, we would like to acknowledge that the overall performance of our assay in these biopsy tissues was somewhat lower that resected specimens (AUC of 0.72 vs. 0.88). Furthermore, it is encouraging to notice that the robustness of our current mRNA assay was quite comparable to the miRNA biomarkers that we reported previously. Currently we are planning prospective studies to evaluate the performance of both mRNA and miRNA panels – individually, as well as in combination – to determine whether a combined classifier may offer superior accuracy in identifying LNM in T1 CRCs, especially in pre-surgical biopsies. If successful, pre-surgical use of this signature might lead to reduction in ESD-associated complications (perforation or bleeding), as well as in reducing the overall healthcare economic burden from such expensive surgical procedures. Ours was a retrospective study; hence, future prospective studies must independently validate the robustness of these biomarkers prior to their translation into clinical practice. (Excerpt from text, p. 5.)

Izumi, D., F. Gao, S. Toden, F. Sonohara, M. Kanda, T. Ishimoto, Y. Kodera, X. Wang, H. Baba and A. Goel (2019). “A genomewide transcriptomic approach identifies a novel gene expression signature for the detection of lymph node metastasis in patients with early stage gastric cancer.” EBioMedicine Feb 13. [Epub ahead of print].

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BACKGROUND: Although identification of lymph node (LN) metastasis is a well-recognized strategy for improving outcomes in patients with gastric cancer (GC), currently there is lack of availability of adequate molecular biomarkers that can identify such metastasis. Herein we have developed a robust gene-expression signature for detecting LN metastasis in early stage GC by using a transcriptome-wide biomarker discovery and subsequent validation in multiple clinical cohorts. METHODS: A total of 532 patients with pathological T1 and T2 GC from 4 different cohorts were analyzed. Two independent datasets (n=96, and n=188) were used to establish a gene signature for the identification of LN metastasis in GC patients. The diagnostic performance of our gene-expression signature was subsequently assessed in two independent clinical cohorts using qRT-PCR assays (n=101, and n=147), and subsequently compared against conventional tumor markers and image-based diagnostics. FINDINGS: We established a 15-gene signature by analyzing multiple high throughput datasets, which robustly distinguished LN status in both training (AUC=0.765, 95% CI 0.667-0.863) and validation cohorts (AUC=0.742, 95% CI 0.630-0.852). Notably, the 15-gene signature was significantly superior compared to the conventional tumor markers, CEA (P=.04) and CA19-9 (P=.005), as well as computed tomography-based imaging (P=.04). INTERPRETATION: We have established and validated a 15-gene signature for detecting LN metastasis in GC patients, which offers a robust diagnostic tool for potentially improving treatment outcomes in gastric cancer patients. FUND: NIH: CA72851, CA181572, CA14792, CA202797, CA187956; CPRIT: RP140784: Baylor Sammons Cancer Center polot grants (AG), VPRT: 9610337, CityU 21101115, 11102317, 11103718; JCYJ20170307091256048 (XW).