Добірка наукової літератури з теми "378.147:796.012.656 (043.3)"

Background:DISCOVER 1 & 2, two double-blind, phase-3, psoriatic arthritis (PsA) trials of guselkumab (GUS, an IL-23 inhibitor), demonstrated significant improvement with GUS vs placebo (PBO) in signs and symptoms of PsA, with good tolerability, at week (w) 24 during the PBO-controlled period.1,2 Beyond w24, all patients (pts) switched to GUS. Continued treatment maintained efficacy through w52.3,4Objectives:To describe pooled safety results from the DISCOVER 1 & 2 trials through 1-year of GUS treatment.Methods:Adults with active PsA (DISCOVER 1: ≥3 tender/swollen joints and C-Reactive protein [CRP] ≥0.3 mg/dL; DISCOVER 2: ≥5 tender/swollen joints and CRP ≥0.6 mg/dL) were randomized to subcutaneous GUS 100 mg at w0, w4, then every 8 w (q8w); GUS 100 mg q4w; or PBO. At w24, PBO pts switched to GUS 100 mg q4w. Pts were biologic naive except ~30% pts in DISCOVER 1. Safety was reported through w60 in DISCOVER 1 and through w52 in DISCOVER 2.Results:Baseline characteristics were similar between treatment groups in the pooled studies. Through w24 and 1 year, numbers of pts per 100 patient years with ≥1 event were similar among treatment groups for adverse events (AEs), serious AEs, infections, serious infections, and discontinuations due to AE (Table 1). At 1 year, there were no cases of active tuberculosis, opportunistic infections (including candida), or inflammatory bowel disease in GUS-treated pts; 2 deaths in PBO pts; and low incidences that were similar across treatment groups for malignancy, major adverse cardiac events, and injection-site reactions. Incidence of anti-GUS antibodies was 4.5%, and most were not neutralizing. Mild elevations in serum hepatic transaminases and decreases in neutrophil counts were consistent at 1 year with the results at w24 (Table 1).Conclusion:GUS regimens of q8w and q4w were well tolerated in PsA pts through 1 year of treatment in the phase-3 DISCOVER trials, consistent with the w24 results. No meaningful differences between incidences of AEs were reported in the q8w and q4w groups. The safety profile of GUS in PsA pts is generally comparable with the previously established safety profile of GUS.References:[1]Deodhar A et al. Lancet. 2020;395:1115[2]Mease P et al. Lancet. 2020;395:1126[3]Ritchlin C et al. EULAR 2020 # SAT0397[4]McInnes I et al. EULAR 2020 # SAT0402Table 1.Number of Patients with AEs per 100 PY and Incidence of AEs of InterestTime Period24 Weeks1 Year*Treatment GroupPBOGUS SC 100 mgPBO to GUS‡GUS SC 100 mgDosing ScheduleMatchingq8wq4wGUSCombined†q4wq8wq4wGUSCombined‡ N3723753737483523753731100Total PY Follow-Up173173172346204384385589Patients with AEs per 100 PY, n (95% CI)≥1 AE143 (123, 166)148 (127, 171)154 (132, 178)151 (136, 167)92 (77, 108)114 (100, 130)115 (101, 131)109 (100, 117)≥1 Serious AE7.1 (3.7, 12)4.1 (1.6, 8.4)4.7 (2.0, 9.3)4.4 (2.5, 7.3)7.0 (3.8, 11.8)4.8 (2.9, 7.6)4.0 (2.2, 6.6)4.9 (3.6, 6.6)≥1 Infection50 (39, 62)47 (37, 59)52 (42, 65)49 (42, 58)39 (31, 49)41 (34, 48)38 (31, 45)39 (35, 44)≥1 Serious Infection1.7 (0.4, 5.1)0.6 (0.0, 3.2)1.8 (0.4, 5.1)1.2 (0.3, 3.0)2.5 (0.8, 5.8)1.3 (0.4, 3.1)0.8 (0.2, 2.3)1.3 (0.7, 2.3)Discontinued due to AE4.1 (1.6, 8.4)2.9 (1.0, 6.8)4.7 (2.0, 9.3)3.8 (2.0, 6.5)3.5 (1.4, 7.1)2.1 (0.9, 4.1)2.6 (1.3, 4.8)2.6 (1.7, 3.8)AEs of Interest§, n (%)Death2 (0.5)0000000Malignancy1 (0.3)2 (0.5)02 (0.3)1 (0.3)2 (0.5)03 (0.3)Major Adverse Cardiac Events1 (0.3)01 (0.3)1 (0.1)001 (0.3)1 (0.1)Opportunistic Infections00000000Tuberculosis00000000Inflammatory Bowel Disease1 (0.3)0000000Injection-Site Reaction1 (0.3)5 (1.3)4 (1.1)9 (1.2)4 (1.1)6 (1.6)9 (2.4)19 (1.7)Anti-GUS Antibody+-6/373 (1.6)9/371 (2.4)15/744 (2.0)14/350 (4.0)18/373 (4.8)17/371 (4.6)49/1094 (4.5)*Through w60 for DISCOVER 1 and w52 for DISCOVER 2; †Combined GUS q8w and q4w; ‡For patients who switched from PBO to GUS, only data on and after first GUS administration were included in this group; §PBO N=370.AE, adverse event; CI, confidence interval; GUS, guselkumab; PBO, placebo; PY, patient year; q4w, every 4 weeks; q8w, every 8 weeks; SC, subcutaneous; w, weekDisclosure of Interests:Christopher T. Ritchlin Grant/research support from: Received grant/research support from UCB Pharma, AbbVie, Amgen, consultation fees from UCB Pharma, Amgen, AbbVie, Lilly, Pfizer, Novartis, Gilead, Janssen, Proton Rahman Speakers bureau: Received speakers fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Grant/research support from: Received grant/research support from Janssen and Novartis, consultation fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Philip Helliwell Consultant of: Consultation fees paid to charity (AbbVie, Amgen, Pfizer, UCB) or himself (Celgene, Galapagos), Grant/research support from: Received grants/research support paid to charity (AbbVie, Janssen, Novartis), Wolf-Henning Boehncke Consultant of: Received consultation fees from Janssen, Grant/research support from: Received grant/research support from Janssen Research & Development, LLC, Iain McInnes Consultant of: Received consultation fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Received grant/research support from Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Alice B Gottlieb Speakers bureau: Received speakers fees from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Consultant of: Received consultation fees from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Grant/research support from: Received grant/research support from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Shelly Kafka Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Alexa Kollmeier Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Xie L Xu Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, May Shawi Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Shihong Sheng Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Prasheen Agarwal Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Bei Zhou Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Paraneedharan Ramachandran Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Philip J Mease Speakers bureau: Received speakers fees from Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, Consultant of: Received consultation fees from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB, Grant/research support from: Received grant/research support from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB.

Autoimmune thyroid disease is a serious medical problem in which various operative procedures are performed. The objective of the study is to explore the type of applied surgical procedures in autoimmune thyroid disease, advantages and disadvantages of various procedures, and criteria they have to meet. This is retrospective clinical study on 1478 patients, operated for Graves? toxic goiter (117 males and 795 females mean age 37.7) and Hashimoto thyroiditis (27 males and 539 females mean age 50.6) from 1995 to April 2005. Cancer in Graves? disease was found in 61 patients (6.7%), papillary in 60 (occult in 53 or 6.6%) and metastatic in 1, Hashimoto thyroiditis and thyroid cancer was found in 141 patients (24.9%), papillary in 116 or 20.5% (occult in 55 or 9.7%), follicular in 2 (0.3%), Hurthle in 11 (1.9%), medullary in 8 (1.4%), anaplastic in 2 (0.3%) and lymphoma in 3 (0.5%). We performed subtotal bilateral lobectomy in 344 (312 in Graves and 32 in Hashimoto), total lobectomy on one side with subtotal on the oposite in 307 (228 in Graves and 79 in Hashimoto); out of them, in 59 patients, the remnant was left in the region of the upper pole which we called atypic lobectomy. The most common procedure, total or near by total thyroidectomy, performed in 719 (371 in Graves and 349 in Hashimoto). One side lobectomy was performed in 103 patients with Hashimoto thyroiditis. Lymph node dissection was performed in 21 ( 1 in Graves and 20 in Hashimoto), in all central, in 10 lateral functional and in 6 mediastinal, in 15 patients with cancer and in 6 patients with benign disease. There was no operative mortality. In Graves? disease, there was postoperative bleeding in 4 (0.4%), wound infection in 2 (0.2%) recurrent pulsy in 18 (2%) and permanent hypoparathyroidism in 13 (1.4%). In Hashimoto thyroiditis, there was postoperative bleeding in 2 (0.4%), recurrent nerve pulsy in 11 (1.9%) and permanent hypoparathyroidism in 6 (1.1%). The most common surgical procedure in autoimmune thyroid disease is total thyroidectomy which is followed by low complication rate in specialised centers. Cancer is more frequent in Hashimoto than in Graves? disease.

Objective. To evaluate the adequacy of protein intakes now recommended as safe for infants and toddlers. Methods. Subjects were recovering malnourished infants, age 5.3 to 17.9 months, length age (LA) 2.5 to 6.4 months, weight age (WA) 1.5 to 5.2 months, weight/length (W/L) 78% to 100% of National Center for Health Statistics data; and toddlers age 11.4 to 31.6 months, LA 6.1 to 17.9 months, WA 3.9 to 12.0 months, W/L 79% to 99%. Infants were assigned at random to formulas with 5.5%, 6.7%, or 8.0% energy as 60:40 whey:casein protein. The 5.5% was based on FAO-WHO-UNU safe protein and average energy for ages 2.5 to 6.0 months. Toddlers received 4.7% (recommended for 6 to 18 months), 6.4%, or 8.0%. Identical concentrations (weight/kcal) of other nutrients were maintained; intakes were adjusted weekly to reach, in 90 days, the 50th percentile of weight for a LA 3 months greater than the initial one. Results. Infants consumed 125 ± 11 (SD), 116 ± 10, and 126 ± 14 kcal and 1.7 ± 0.1, 1.9 ± 0.2, and 2.5 ± 0.3 g protein Kg-1· d-1; gained 2.4 ± 0.7, 2.9 ± 0.7, and 2.6 ± 0.5 months in LA, and reached a W/L of 105 ± 5, 103 ± 6, and 105 ± 5% of reference. Sum of four fat-folds (Σ FF) grew 13.1 ± 6.9, 10.4 ± 4.8, and 11.7 ± 5.3 mm to 32.5 ± 5.2, 31.7 ± 4.7, and 30.5 ± 5.5 mm; arm muscle areas (AMA) 57%, 51%, 70% to 1004 ± 109, 1017 ± 110, and 1004 ± 116 mm2, still low; arm fat areas (AFA) 93%, 66%, and 93% to higher-than-normal 598 ± 105, 610 ± 101, and 541 ± 116 mm2. Regression of intake on weight gain estimated energy for maintenance + activity to be 81.0 ± 7.5 (SEM) kcal · kg-1· d-1, and cost of gain (storage + metabolic cost) as 7.6 ± 1.7 kcal/g, with no significant effect of % protein. Toddlers consumed 107 ± 9, 103 ± 12, and 105 ± 10 kcal and 1.3 ±0.1, 1.6 ± 0.2, and 2.1 ± 0.2 g protein kg-1 · d-1; gained 3.3 ± 0.7, 2.9 ± 0.6, and 3.3 ± 0.7 months in LA; to a W/L of 102 ± 1, 102 ± 3, and 101 ± 4%. Σ FF grew 9.2 ± 4.0, 7.4 ± 4.3, and 6.0 ± 3.8 to 28.9 ± 5.2, 30.5 ± 3.7, and 27.0 ± 2.7 mm; AMA 31%, 33%, and 34% to 1121 ± 115, 1124 ± 110, and 1117 ± 120 mm2; AFA 53%, 44%, and 45% to higher-than-normal 578 ± 106, 636 ± 99, and 569 ± 68 mm2. Cost of maintenance + activity was 70.8 ± 3.8 (SEM) kcal · kg-1 · d-1, that of weight gain 9.7 ± 1.35 kcal/g, with no effect of % protein. Conclusions. Within age groups, there were no significant protein-related differences in growth. In both infants and toddlers, high-energy intakes resulted in mild obesity, with lean body mass still deficient. Protein intakes two SD below the means in the lowest protein/energy cells, 1.5 g · kg-1 · d-1 for infants and 1.1 g · Kg-1 · d-1 for toddlers, should still be safe for nearly all children of comparable biological ages.

Background:Juvenile idiopathic arthritis (JIA) can cause considerable pain and disability in childhood and adulthood. Studies exploring the efficacy of medications in adult JIA patients are limited, although tumor necrosis factor inhibitors (TNFi) have been increasingly used in this patient group.Objectives:To explore the efficacy of TNFi ± comedication on disease activity in adult JIA patients, compared to a weighted rheumatoid arthritis (RA) cohort.Methods:Data from NOR-DMARD, a longitudinal observational study including patients > 18 years starting or switching DMARD treatment, was used [1]. Patients with a clinical JIA diagnosis, or patients with other inflammatory joint diseases diagnosed before 16 years were identified from the study population. RA patients were included for comparative purposes.Disease activity measurements and remission rates among patients starting treatment with TNFi ± comedication were collected at baseline, 3 and 6 months. Changes in disease activity and absolute remission rates after 3 and 6 months were calculated. Remission rates and change in disease activity from baseline were compared between JIA patients and a weighted RA cohort with weights based on age and gender, using linear and logistic regression for continuous and categorical variables, respectively.Results:281 JIA patients (68.9% female, mean (SD) age 32.1 (11.1) years, mean (SD) diagnosis duration 23.5 (12.2) years) and 1374 RA patients (71.6% female, mean (SD) age 52.7 (14.5) years, mean (SD) diagnosis duration 9.5 (10.0) years) were included in the analyses. Age, gender distribution and disease duration differed significantly between cohorts.Both groups had a significant improvement across all disease activity measures after 3 months (Table 1), which was maintained after 6 months across all measures except MHAQ. The RA group had a significantly greater 3- and 6-month improvement in SJC28. Both groups had an overall 6-month increase in absolute remission rates. The JIA group had a significantly higher 3-month DAS28 remission rate (Figure 1). This difference was not significant after 6 months, as remission rates from 3 to 6 months in the JIA group declined across all measures.Table 1.BaselineChange to 3 monthsChange to 6 monthsJIA*RA*Diff.§JIA*RA*Diff.§JIA*RA*Diff.§ESR, mm/h18.7 (18.9)25.5 (22.0)1.3 (-2.3 to 4.9)-7.4 (15.8)-7.6 (16.6)-0.3 (-4.4 to 3.8)-7.4 (16.8)-8.5 (18.2)0.0 (-5.7 to 5.7)SJC282.5 (3.6)5.5 (5.4)1.6 (1.3 to 2.0)-1.4 (3.4)-3.1 (4.7)-1.0 (-1.7 to -0.3)-1.6 (3.2)-3.5 (5.1)-1.0 (-1.9 to -0.1)TJC 284.0 (5.6)6.6 (6.4)1.3 (0.4 to 2.3)-1.8 (3.9)-3.1 (5.9)-0.6 (-1.4 to 0.2)-1.8 (3.9)-3.9 (6.2)-1.0 (-2.0 to 0.1)DAS283.6 (1.4)4.5 (1.6)0.3 (0.1 to 0.6)-1.2 (1.3)-1.2 (1.4)-0.0 (-0.3 to 0.3)-1.2 (1.3)-1.5 (1.4)-0.2 (-0.6 to 0.2)SDAI16.8 (10.6)23.1 (14.3)2.4 (0.3 to 4.5)-7.7 (9.9)-10.9 (12.7)-2.0 (-4.2 to 0.2)-7.9 (8.6)-13.2 (13.6)-2.8 (-5.8 to 0.2)PGA51.4 (26.3)49.9 (25.5)-4.0 (-8.5 to 0.5)-20.6 (26.7)-17.0 (26.7)2.7 (-2.2 to 7.6)-21.6 (25.3)-19.1 (28.7)3.4 (-3.0 to 9.8)MHAQ0.6 (0.5)0.7 (0.5)0.0 (-0.1 to 0.1)-0.24 (0.42)-0.22 (0.42)0.0(-0.1 to 0.1)-0.23 (0.40)-0.25 (0.45)0.0 (-0.1 to 0.1)*Mean (SD)§ Weighted group difference, RA coefficient (95 % confidence interval)Figure 1.Mean 3- and 6-month remission rates with error bars (SE)Conclusion:TNFi was equally effective in reducing disease activity in the JIA and RA cohort after 3 and 6 months, and in inducing remission after 6 months. Absolute remission rates in the JIA group declined from 3 to 6 months across all measures, and studies with longer duration are needed to explore the long-term efficacy of TNFi in the patient groups.References:[1]Kvien, T.K., et al., A Norwegian DMARD register: prescriptions of DMARDs and biological agents to patients with inflammatory rheumatic diseases. Clin Exp Rheumatol, 2005. 23(5 Suppl 39): p. S188-94.Disclosure of Interests:Imane Bardan: None declared, Karen Minde Fagerli: None declared, Joe Sexton: None declared, Gunnstein Bakland Speakers bureau: Abbvie, Consultant of: UCB, Pfizer, Novartis, Pawel Mielnik: None declared, Liz Marina Paucar Loli: None declared, Tore K. Kvien Speakers bureau: Fees for speaking: Amgen, Celltrion, Egis, Evapharma, Ewopharma, Hikma, Oktal, Sandoz, Sanofi, Consultant of: Fees for consulting: AbbVie, Amgen, Biogen, Celltrion, Eli Lilly, Gliead, Mylan, Novartis, Pfizer, Sandoz, Sanofi, Grant/research support from: Received research funding to Diakonhjemmet Hospital from Abbvie, Amgen, BMS, MSD, Pfizer and UCB, Eirik kristianslund: None declared, Anna-Birgitte Aga Grant/research support from: Dr. Aga reports personal fees from Abbvie, Eli Lilly, Novartis and Pfizer, outside the submitted work

9530 Background: Ultraviolet (UV)-induced high tumor mutation burden (TMB) of NACM is associated with response to anti-PD-1 monotherapy (aPD-1). Anatomic location of the primary lesion (reflecting UV exposure) and race (reflecting eumelanin level) may serve as surrogates for TMB and be associated with varying response and irAE patterns. Methods: Pts with advanced NACM receiving aPD-1 between 2009-2019 were retrospectively analyzed from 5 institutions in the US, Australia and China. Best response, survival (PFS and OS), and organ/system-specific irAEs were compared by race (Caucasian [C] vs non-Caucasian [NC]) and primary anatomic site. Results: Among 697 patients, 616 were C, 81 were NC. Complete response rate (CRR) was 24.8% (95%CI, 21.4-28.4) and 2.6% (95%CI, 0.3-9.1) and ORR was 54.9% (95%CI, 50.9-58.9) and 15.6% (95%CI, 8.3-25.6) in C and NC, respectively (both P<.001). Median PFS was 16.5 (95%CI, 12.0-23.1) and 5.2 (95%CI, 3.6-7.6) months, median OS was 60.5 (95%CI, 49.9-not reached [NR]) and 29.2 (95%CI, 17.9-NR) months, in C and NC, respectively (P<.001 and =.04). In multivariate analyses, C had significantly higher CRR (OR 13.4, 95%CI 3.1-57.4), ORR (OR 10.6, 95%CI 4.6-24.5), and longer PFS (HR 0.5, 95%CI 0.4-0.7) than NC. Compared to a head primary site, NACM from less UV-exposed regions had significantly lower CRR (upper trunk, OR 0.6, 95%CI 0.4-0.96; lower limb, OR 0.5, 95%CI 0.2-0.9), ORR (lower limb, OR 0.6, 95%CI 0.3-0.9) and poorer PFS (perineum/buttock, HR 2.1, 95%CI 1.2-3.5; lower limb, HR 1.6, 95%CI 1.2-2.2) and OS (perineum/buttock, HR 3.8, 95%CI 2.2-6.8; lower limb, HR 1.7, 95%CI 1.2-2.4). Overall irAE incidence was similar between C and NC but irAE subtypes varied. C had significantly higher incidence of GI (12.2%, 95%CI 9.5-15.3% vs 1.2%, 95%CI, 0.03-6.7%, P=.001), respiratory (10.3%, 95%CI 7.8-13.2% vs 0, P<.001) and grade 3/4 (15.4%, 95%CI 12.4-18.8% vs 6.2%, 95%CI 2.0-13.8%, P=.03) irAEs; and lower incidence of endocrine (13.8%, 95%CI 10.9-17.0% vs 32.1%, 95%CI 22.2-43.4%, P<.001) and liver (4.8%, 95%CI 3.2-7.1% vs 13.6%, 95%CI, 7.0-23.0%, P=.005) irAEs. IrAEs did not vary by primary NACM site. Conclusions: Race and primary site are independently correlated with distinct response and survival outcomes in pts with advanced NACM receiving aPD-1. IrAE subtypes vary by race although overall irAE incidence does not.

The aim of this paper was to identify which psycholinguistic variables are better predictors of performance for healthy participants in a picture naming task and in a picture categorization task. A correlation analysis and a Path analysis were carried out. The correlation analysis showed that naming accuracy and naming latency are significant and positively correlated with lexical frequency and conceptual familiarity variables, whereas they are negatively correlated with H index. Reaction times in the categorization task were negatively correlated with lexical frequency and conceptual familiarity variables and positively correlated with visual complexity variable. The Path analysis showed that subjective lexical frequency and H index are the better predictors for picture naming task. In picture categorization task, for reaction times, the better predictor variables were subjective lexical frequency, conceptual familiarity and visual complexity. These findings are discussed considering previous works on the field. References Akinina, Y., Malyutina, S., Ivanova, M., Iskra, E., Mannova, E., & Dragoy, O. (2015). Russian normative data for 375 action pictures and verbs. Behavior research methods, 47(3), 691-707. doi: 10.3758/s13428-014-0492-9 Alario, F. X., & Ferrand, L. (1999). A set of 400 pictures standardized for French: Norms for name agreement, image agreement, familiarity, visual complexity, image variability, and age of acquisition. Behavior Research Methods, Instruments, & Computers, 31(3), 531-552. Alario, F. X., Ferrand, L., Lagnaro, M., New, B., Frauenfelder, U. H., & Seguí, J. (2004). Pre­dictors of picture naming speed. Behavior Research Methods, Instruments and Computers, 36, 140-155. doi: 10.3758/BF03195559 Albanese, E., Capitani, E., Barbarotto, R., & Laiacona, M. (2000). Semantic category disso­ciations, familiarity and gender. Cortex, 36, 733-746. Almeida, J., Knobel, M., Finkbeiner, M., & Caramazza, A. (2007). The locus of the frequency effect in picture naming: When recognizing is not enough. Psychonomic Bulletin & Review, 14(6), 1177-1182. Arbuckle, J. L. (2003). AMOS 5.0. Chicago: SmallWaters. Bakhtiar, M., & Weekes, B. (2015). Lexico-semantic effects on word naming in Persian: Does age of acquisition have an effect? Memory & Cognition, 43(2), 298-313. doi: 10.3758/s13421-014-0472-4 Balota, D. A., Pilotti, M., & Cortese, J. M. (2001). Subjective frequency estimates for 2,938 monosyllabic words. Memory & Cognition, 29, 639-647. doi: 10.3758/BF03200465 Barbón, A., & Cuetos, F. (2006). Efectos de la Edad de Adquisición en tareas de Categorización Semántica. Psicológica, 27, 207-223. Barca, L., Burani, C., & Arduino, L. (2002). Word naming times and psycholinguistic norms for Italian nouns. Behavior Research Methods, Instruments and Computers, 34(3), 424-434. Barry, C., Morrison, C. M., & Ellis, A. W. (1997). Naming the Snodgrass and Vanderwart pictures: Effects of age of acquisition, frequency and name agreement. Quarterly Journal of Experimental Psychology, 50(A), 560-585. Bates, E., Burani, C., D´amico, S., & Barca, L. (2001). Word reading and picture naming in Italian. Memory and Cognition, 29(7), 986-999. Bates, E., D'Amico, S., Jacobsen, T., Székely, A., Andonova, E., Devescovi, A., . . . Tzeng, O. (2003). Timed picture naming in seven languages. Psychonomic Bulletin & Review 20(2), 344-380. doi: 10.3758/BF03196494 Berman, S., Friedman, D., Hamberger, M., & Snodgrass, J. G. (1989). Developmental picture norms: Relationships between name agreement, familiarity, and visual complexity for child and adult ratings of two sets of line drawings. Behavior Research Methods, Instruments, & Computers, 21(3), 371-382. Bonin, P., Boyer, B., Méot, A., Fayol, M., & Droit, S. (2004). Psycholinguistic norms for action photographs in French and their relationships with spoken and written latencies. Behavior Research Methods, Instruments, & Computers, 36, 127-139. doi: 10.3758/BF03195558 Bonin, P., Chalard, M., Méot, A., & Fayol, M. (2002). The determinants of spoken and written picture naming latencies. British Journal of Psychology, 93, 89-114. doi: 10.1348/ 000712602162463 Bonin, P., Peereman, R., Malardier, N., Méot, A., & Chalard, M. (2003). A new set of 299 pictures for psycholinguistic studies: French norms for name agreement, image agreement, conceptual familiarity, visual complexity, image variability, age of acquisition and naming latencies. Behavior Research Methods, Instruments, & Computers, 35, 158-167. Boukadi, M., Zouaidi, C., & Wilson, M. A. (2016). Norms for name agreement, familiarity, subjective frequency, and imageability for 348 object names in Tunisian Arabic. Behavior Research Methods, 48, 585-599. doi: 10.3758/s13428-015-0602-3 Brysbaert, M., Van Wijnendaele, I., & De Deyne, S. (2000). Age-of-acquisition effects in seman­tic processing tasks. Acta Psychologica, 104, 215-226. doi: 10.1016/S0001-6918(00)00021-4 Cameirão, M. L., & Vicente, S. G. (2010). Age-of-acquisition norms for a set of 1,749 Portuguese words. Behavior Research Methods, 42, 474-480. doi: 10.3758/BRM.42.2.474 Capitani, E., Laiacona, M., Barbarotto, R., & Trivelli, C. (1994). Living and nonliving categories: Is there a “normal” asymmetry? Neuropsychologia, 32, 1453-1463. Carroll, J. B., & White, M. N. (1973). Word frequency and age of acquisition as determiners of picture-naming latency. Quarterly Journal of Experimental Psychology, 25(1), 85-95. doi: 10.1080/14640747308400325 Cuetos, F., & Barbón, A. (2006). Word naming in Spanish. European Journal of Cognitive Psychology, 18, 415-436. Cuetos, F., Ellis, A., & Alvarez, B. (1999). Naming times for the Snodgrass and Vanderwart pictures in Spanish. Behavior Research Methods, Instruments and Computers, 31, 650-658. doi: 10.3758/BF03200741 Cycowicz, Y. M., Friedman, D., Rothstein, M., & Snodgrass, J. G. (1997). Picture naming by young children: Norms for name agreement, familiarity, and visual complexity. Journal of Experimental Child Psychology, 65(2), 171-237. doi: 10.1006/jecp.1996.2356 D´amico, S., Devescovi, A., & Bates, E. (2001). Picture naming and lexical access in italian children and adults. Journal of Cognition and Development, 2(1), 71-105. Dell´Acqua, R., Lotto, L., & Job, R. (2000). Naming times and standardized norms for the Italian PD/DPSS set of 266 pictures. Direct comparisons with American, English, French and Spanish published databases. Behavior Research Methods, Instruments, & Computers, 31, 588-615. Ellis, A. W., & Morrison, C. M. (1998). Real age of acquisition effects in lexical retrieval. Journal of Experimental Psychology: Learning, Memory & Cognition, 24, 515-523. doi: 10.1037/0278-7393.24.2.515 Forster, K. I., & Forster, J. C. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods Instruments and Computers, 35, 116-124. doi: 10.3758/BF03195503 Gaffan, D., & Heywood, C. (1993). A spurious category-specific visual agnosia for living things in normal human and nonhuman primates. Journal of Cognitive Neuroscience, 5(118-128). doi: 10.1162/jocn.1993.5.1.118 Humphreys, G. W., Riddoch, M. J., & Quinlan, P. T. (1988). Cascade processes in picture identification. Cognitive Neuropsychology, 5(1), 67-103. Iyer, G., Saccuman, C., Bates, E., & Wulfeck, B. (2001). A Study of Age-of-acquisition (AoA) Ratings in Adults. CRL Newsletter, 13(2), 3-16. Khwaileh, T., Body, R., & Herbert, R. (2014). A normative database and determinants of lexical retrieval for 186 Arabic nouns: Effects of psycholinguistic and morpho-syntactic variables on naming latency. Journal of Psycholinguistic Research, 43, 749-769. doi: 10.1007/ s10936-013-9277-z Khwaileh, T., Mustafawi, E., Herbert, R., & Howard, D. (2018). Gulf Arabic nouns and verbs: A standardized set of 319 object pictures and 141 action pictures, with predictors of naming latencies. Behavior Research Methods, 50(6), 2408-2425. doi: 10.3758/s13428-018-1019-6 Laws, K. R. (1999). Gender afects latencies for naming living and nonliving things: implications for familiarity. Cortex, 35, 729–733. Laws, K. R. (2000). Category-specificity naming errors in normal subjects: The influence of evolution and experience. Brain and Language, 75, 123-133. doi: 10.1006/brln.2000.2348 Laws, K. R., & Neve, C. (1999). A `normal` category-specific advantage for naming living things. Neuropsychologia, 37, 1263-1269. doi: 10.1016/S0028-3932(99)00018-4 Lloyd-Jones, T. J., & Humphreys, G. W. (1997). Perceptual differentiation as a source of category effects in object processing: evidence from naming and object decision. Memory and Cognition, 25, 18-35 doi: 10.3758/BF03197282 Manoiloff, L., Artstein, M., Canavoso, M., Fernández, L., & Seguí, J. (2010). Expanded norms for 400 experimental pictures in an Argentinean Spanish-speaking population. Behavior Research Methods, 42(2), 452-460. doi: 10.3758/BRM.42.2.452 Martein, R. (1995). Norms for name and concept agreement, familiarity, visual complexity and image agreement on a set of 216 pictures. Psychologica Belgica, 35, 205-225. Martínez-Cuitiño, M., Barreyro, J. P., Wilson, M., & Jaichenco, V. (2015). Nuevas normas semán­ticas y de tiempos de latencia para un set de 400 dibujos en español. Inter­disci­plinaria, 32(2), 289-305. Martínez-Cuitiño, M., & Vivas, L. (In press). Category or diagnosticity effect? The influence of color in picture naming tasks. Psychology and Neuroscience. doi: 10.1037/pne0000172 Meschyan, G., & Hernandez, A. (2002). Age of acquisition and word frequency: Determinants of object-naming speed and accuracy. Memory & Cognition, 30, 262-269. doi: 10.3758/ BF03195287 Morrison, C. M., Chappell, T. D., & Ellis, A. W. (1997). Age of Acquisition Norms for a Large Set of Object Names and Their Relation to Adult Estimates and Other Variables. The Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, 50(3), 528-559. doi: 10.1080/027249897392017 Morrison, C. M., Ellis, A. W., & Quinlan, P. T. (1992). Age of acquisition, not word frequency, affects object naming, not object recognition. Memory and Cognition, 20, 705-714. doi: 10.3758/BF03202720 Oldfield, R. C., & Wingfield, A. (1965). Response latencies in naming objects. Quart J Exp Psychol`, 17, 273-281. doi: 10.1080/17470216508416445 Protopapas, A. (2007). Check Vocal: A program to facilitate checking the accuracy and response time of vocal responses from DMDX. Behavior Research Methods, 39(4), 859-862. doi: 10.3758/BF03192979 Sanfeliu, M. C., & Fernández, A. (1996). A set of 254 Snodgrass-Vanderwart pictures standar­dized for Spanish: Norms for name agreement, image agreement, familiarity, and visual complexity. Behavior Research Methods, Instruments, & Computers, 28, 537-555. Shao, Z., Roelofs, A., & Meyer, A. S. (2012). Sources of individual differences in the speed of naming objects and actions: The contribution of executive control. The Quarterly Journal of Experimental Psychology, 65(10), 1927-1944. Snodgrass, J. G., & Vanderwart, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity and visual complexity. Journal of Experimental Psychology: Human Learning and Memory, 6, 174-215. doi: 10.1037//0278-7393.6.2.174 Snodgrass, J. G., & Yuditsky, T. (1996). Naming times for the Snodgrass and Vanderwart pictures. Behavior Research Methods, Instruments, y Computers, 28(4), 516-536. Székely, A., & Bates, E. (2000). Objective Visual Complexity as a Variable in Studies of Pictures Naming. CLR Newsletter, 12(2), 3-33. Székely, A., D’Amico, S., Devescovi, A., Federmeier, K., Herron, D., Iyer, G., . . . Bates, E. (2003). Timed picture naming: Extended norms and validation against previous studies. Behavior Research Methods, Instruments, & Computers, 35, 621-633. doi: 10.3758/ BF03195542 Tanaka-Ishii, K., & Terada, H. (2011). Word familiarity and frequency. Studia Linguistica, 65(1), 96-116. doi: 10.1111/j.1467-9582.2010.01176.x Vitkovitch, M., & Tyrrell, L. (1995). Sources of disagreement in object naming. Quarterly Journal of Experimental Psychology, 48(A), 822-848. doi: 10.1080/14640749508401419 Warrington, E. K., & McCarthy, R. A. (1983). Category-specific access dysphasia. Brain, 106, 859-879. doi: 10.1093/brain/106.4.859