Academic literature on the topic '+ 544.723.2.023.223'

Abstract Background. The prognostic significance of bone marrow (BM) fibrosis grade in pts with primary myelofibrosis (PMF) is debated. A fibrosis grade greater than 1 was associated with a 2-fold higher risk of death compared with pts with early/prefibrotic MF (grade 0) [Thiele J, Ann Hematol 2006]. Recent data suggest that more accurate prediction of survival is achieved when fibrosis grade is added to IPSS [Verner C, Blood 2008; Giannelli U, Mod Pathol 2012]. Aim. To analyze the prognostic impact of fibrosis in diagnostic BM samples of 540 WHO-2008 diagnosed PMF pts with extensive clinical and molecular information collected in 6 Italian centers belonging to AGIMM (AIRC-Gruppo Italiano Malattie Mieloproliferative). Methods. The clinical variables assessed were those previously identified as prognostically relevant in the IPSS score. Published methods were used to screen mutations of JAK2, MPL, CALR, EZH2, ASXL1, IDH1/2 and SRSF2. European consensus scoring system was used to grade fibrosis (on a scale of MF-0 to MF-3). The prognostic value of fibrosis with regard to overall survival (OS) was estimated by Kaplan-Meier method and Cox regression. Results. Pts' median age was 61y; median follow-up 3.7y; median OS 10.5y; 184 pts (34.1%) died. IPSS risk category: low 33.7%, Int-1 27.7%, Int-2 19.1%, High-risk 19.5%. Mutational rate: JAK2 V617F 62.6%, CALR 20.7% (type-1/1-like 77.7%, type2/2-like-2 21.4%), MPL W515 5.9%; 62 (11.5%) were triple negative (TN). 171 pts (31.7%) were High-Molecular Risk (HMR) category (Vannucchi AM, Leukemia 2013); mutation rate: EZH2 7.2%, ASXL1 22.2%, IDH1-2 2.4%, SRSF2 8.3%. According to fibrosis grading, 50 pts were MF-0 (9.3%), 180 MF-1 (33.3%), 196 MF-2 (36.3%), 114 MF-3 (21.1%). Compared with both MF-0 and MF-1, MF-2 and MF-3 pts presented more frequently constitutional symptoms (P<.0001), larger splenomegaly (P<.0001), greater risk of developing anemia (P<.0001) or thrombocytopenia (P=.003). We found a significant association (P<.0001) between IPSS higher/Int-2 risk categories and MF-2 and -3 (20.5% and 37.8%, respectively, vs 14.8% and 6.0% for MF-0 and -1). There was no correlation between fibrosis grade and phenotypic driver mutations; in particular, TN pts were equally distributed among MF fibrosis grades (10%, 10.6%, 14.3% and 8.8% from MF-0 to -3, respectively). Conversely, the frequency of HMR pts increased progressively according to fibrosis grade: 8 pts MF-0 (16%), 46 MF-1 (25.6%), 66 MF-2 (33.7%) and 51 MF-3 (44.7%) (P<.0001). In particular, we found a significant association between fibrosis grade and ASXL1 (12%, 15%, 23.5% and 36% from MF-0 to -3; P<.0001) and EZH2 (2%, 3.9%, 8.2%, 13.2%; P=.01) mutations. Also, pts with 2 or more HMR mutated genes were preferentially MF-2 or -3 ( 0%, 4.4% 10.2% and 10.5% from MF-0 to -3; P=.001). Median OS was significantly shorter in pts with MF-2 (OS 6.7y, HR 7.3, IC95% 2.7-20.0; P<.0001) and MF-3 (OS 7.2y, HR 8.7, IC95% 3.1-24.2; P<.0001) compared with MF-1 (14.7y; HR 3.9, IC95% 1.4-10.9, P=.008) and MF-0 (P<.0001) used as reference group (OS not reached) (Figure). Excluding MF-0, MF-2 and -3 maintained negative prognostic impact with HR 1.9 (1.3-2.6; P=.001) and 2.2 (1.5-3.3; P<.0001) respectively vs MF-1. The impact of fibrosis on OS was maintained when analysis was restricted to younger (≤65y) pts. In multivariate analysis using the individual IPSS variables, grade MF-2 and -3 were independently predictive of survival (HR 3.9 (1.4-10.8), and HR 4.2 (1.5-12.0), respectively, P=.008 for both). The negative impact on survival of MF-2/-3 was maintained regardless of IPSS category, HMR status, number of HMR mutated genes and driver mutations, included as covariates (Table). In low, Int-1 and Int-2, but not high-risk IPSS categories, MF-2/-3 associated with reduced survival (P<.03). Conclusions. Overall, these results indicate that higher grades (MF-2 and MF-3) of fibrosis correlate with defined clinical and molecular variables and independently negatively impact on OS in PMF, suggesting the opportunity to explore its value in the setting of clinical and molecular prognostic scores for PMF. Table. Multivariate Analysis Variables HR 95% CI P value HMR status 2.4 1.5-3.7 <.0001 HMR≥2mutations 4.3 2.8-6.4 .009 IPSS scoring Int1 2.9 1.6-5.1 <.0001 Int2 10.0 5.6-17.7 <.0001 High 9.7 5.5-17.2 <.0001 Driver mutations CALR type2 3.4 1.3-8.6 .010 JAK2/MPL 2.4 1.4-4.3 .003 TN 4.5 2.3-8.8 <.0001 Fibrosis MF-2/MF-3 3.8 1.4-10.6 .010 Figure 1. Figure 1. Disclosures Passamonti: Novartis: Consultancy, Honoraria, Speakers Bureau. Barbui:Novartis: Speakers Bureau. Vannucchi:Shire: Speakers Bureau; Novartis: Other: Research Funding paid to institution (University of Florence), Research Funding; Baxalta: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Context The National Athletic Trainers' Association and the American College of Sports Medicine have recommended removing American football uniforms from athletes with exertional heat stroke before cold-water immersion (CWI) based on the assumption that the uniform impedes rectal temperature (Trec) cooling. Few experimental data exist to verify or disprove this assumption and the recommendations. Objectives To compare CWI durations, Trec cooling rates, thermal sensation, intensity of environmental symptoms, and onset of shivering when hyperthermic participants wore football uniforms during CWI or removed the uniforms immediately before CWI. Design Crossover study. Setting Laboratory. Patients or Other Participants Eighteen hydrated, physically active men (age = 22 ± 2 years, height = 182.5 ± 6.1 cm, mass = 85.4 ± 13.4 kg, body fat = 11% ± 5%, body surface area = 2.1 ± 0.2 m2) volunteered. Intervention(s) On 2 days, participants exercised in the heat (approximately 40°C, approximately 40% relative humidity) while wearing a full American football uniform (shoes; crew socks; undergarments; shorts; game pants; undershirt; shoulder pads; jersey; helmet; and padding over the thighs, knees, hips, and tailbone [PADS]) until Trec reached 39.5°C. Next, participants immersed themselves in water that was approximately 10°C while wearing either undergarments, shorts, and crew socks (NOpads) or PADS without shoes until Trec reached 38°C. Main Outcome Measure(s) The CWI duration (minutes) and Trec cooling rates (°C/min). Results Participants had similar exercise times (NOpads = 40.8 ± 4.9 minutes, PADS = 43.2 ± 4.1 minutes; t17 = 2.0, P = .10), hypohydration levels (NOpads = 1.5% ± 0.3%, PADS = 1.6% ± 0.4%; t17 = 1.3, P = .22), and thermal-sensation ratings (NOpads = 7.2 ± 0.3, PADS = 7.1 ± 0.5; P &gt; .05) before CWI. The CWI duration (median [interquartile range]; NOpads = 6.0 [5.4] minutes, PADS = 7.3 [9.8] minutes; z = 2.3, P = .01) and Trec cooling rates (NOpads = 0.28°C/min ± 0.14°C/min, PADS = 0.21°C/min ± 0.11°C/min; t17 = 2.2, P = .02) differed between uniform conditions. Conclusions Whereas participants cooled faster in NOpads, we still considered the PADS cooling rate to be acceptable (ie, &gt;0.16°C/min). Therefore, if clinicians experience difficulty removing PADS or CWI treatment is delayed, they may immerse fully equipped hyperthermic football players in CWI and maintain acceptable Trec cooling rates. Otherwise, PADS should be removed preimmersion to ensure faster body core temperature cooling.

Background:Clinical patterns and disease burden of PsA varies in different parts of the world. Demographic studies from Indian subcontinent are sparseObjectives:To study the cutaneous, articular profile of PsA and describe their disease activity, disability and co-morbidities (CMs)Methods:This is a multicenter, cross-sectional, non-interventional study from Karnataka, India. All consecutive PsA patients defined by CASPAR or expert diagnosis were evaluated over 8 months from 17 Rheumatology centers across Karnataka using standard parameters such as PASI, DAPSA, Indian version of HAQ-DI1, psoriatic co-morbidity index2(Cidx) and MDA 5. Patient consent and EC obtainedResults:549 PsA patients were evaluated and their disease characteristics are shown in Table 1 & 2. PsA preceded psoriasis in in 81 (14.7%).Table 1.Patient characteristics (n=549)DEMOGRAPHICSPsACommonest age group of PsA (yrs)31-40PsA SubclassificationM:F6:5Symmetric polyarthritis216(40.7%)Type 1 PsoriasisType 2 Psoriasis279(55.8%)221(44.2%)Mean duration (yrs)Asymmetric oligoarthritis202(38.1%)Psoriasis8.8(±7.8)DIP predominant88(16.6%)PsA5.2(±6.3)Arthritis mutilans16(4.2%)PsA preceded psoriasis81(14.7%)Dactylitis182(33.9%)Family h/oPsoriasis107(19.7%)Enthesitis109(20.3%)PsA33(6%)Mean TJC686.3(±8.9)AS11(2%)Mean SJC683.5(±5.2)Uveitis5(0.9%)Type of PsoriasisPlaque253(59.9%)IBD3(0.5%)Erythrodermic 31(7.3%)Type I & II psoriasis did not differ in PASI, DAPSA, HAQ-DI or having a family h/o psoriasis. Type II psoriasis had higher Cidx than type I (p=0.0001). Pt pain VAS, DAPSA, PhyGA, PtGA & SJC significantly correlated with higher HAQ-DI (p<0.0001). TJC, ESR, CRP & PASI had minor correlation with HAQ-DI. Females had higher HAQ-DI compared to males (p=0.02). Knee joint involvement caused disability most frequently. Cidx was higher in males (p=0.008). Minor correlation was found between Cidx with age, HAQ-DI & DAPSA. Mean BMI of our cohort was 26.8(±14.8) kg/m2. 56.5% were overweight. Higher BMI was not associated with age, duration of arthritis, DAPSA, PASI, HAQ-DI & Cidx.Infections (any time) were recorded in 10.8%, of which skin was the commonest site in 38.9%; 30.5% of these needed hospitalizations.Conclusion:Despite mild skin disease in majority, more than half of the patients have moderate to severe joint activity. Mild to moderate functional disability in nearly half of our cohort indicate high burden of damage. High incidence of co-morbidities in PsA compared with general population is in line with published literature. In addition to aggressive control of articular activity, detection and control of co-morbidities must be an integral part of PsA management.References:[1]https://doi.org/10.1093/rheumatology/41.12.1457[2]http://dx.doi.org/10.1136/annrheumdis-2016-eular.4598Table 2.Disease characteristicsDISEASE ACTIVITYDISABILITYCO-MORBIDITIESMean PASI: 3.8(7.4)Mean HAQ-DI: 0.3(0.45)Mean Cidx: 0.98(1.6)Mild (PASI 0-5)480(80%)Mild-mod disability260(48.2%)N with 1 or more CMs232(42.3%)Severe (>10)57(10.6%)ADL with most frequent disabilityClimbing a flight of stairs 189(35%)HTNT2DMSmokingPsA severity19.8%16.6%5.4%3.2%Mean DAPSA: 18.8(16.6)ADL with highest disability scoreSitting cross-legged/squattingAnxietyIHDDyslipidemiaOthers3.1%2.3%2%<2% eachRemission100(19.9%)Low DA145(28.8%)Moderate DA137(27.2%)High DA123(24.5%)Family h/o CV dis/stroke72(15.2%)Disclosure of Interests:None declared

Aim. To evaluate the influence of combination of omega-3 polyunsaturated fatty acids and atorvastatin on the risk of atrial fibrillation (AF) after coronary bypass surgery (CBS). Material and methods. The study included 114 patients divided into 2 groups, one comprised of 59 ones (75,6% men of mean age 62,0±7,3 yr given conventional medication), the other including 55 patients (80,0% men of mean age 59,4±6,7 yr given omega-3 polyunsaturated fatty acids 5 days before (2 g/d) and during 3 weeks after CBS (1 g/d)). All patients were treated with atorvastatin at the outpatient stage. IL-6,8, 10 and C-reactive protein (CRP), fibrinogen, troponin, NT-proBNP, superoxide dismutase (SOD), and myeloperoxidase were measured at admittance and on day 3.7±1.4 after surgery. Results. AF developed on day 5.9±4.9 (mean) after surgery. Patients of group 2 tended to have fewer new episodes of arrhythmia although no significant difference between the groups was documented (9,1% vs 18,6%, р=0,12). Group 2 included more smokers (74,5% vs 45,8%, р=0,002) and patients with atherosclerosis of lower limb arteries (87,3% vs 71,2%, р=0,03) but fewer those consuming nitrates (39,0% vs 18,2%, р=0,01) and Ca antagonists (45,8% vs 21,8%, р=0,006).Mean dose of atorvastatin given to patients of groups 1 and 2 was 24.7±12.5 and 25.1±10.5 mg/d respectively (р=0,2), duration of its intake 14.6±12.7 and 21.5±19.3 months (р<0,001). There. was no significant difference between leukocyte count, leukogram, IL-8, IL-10, NT-proBNP, and troponin levels before and after CBS. Surgical myocardial revascularization caused a rise in leukocyte count, shifted the leukogram toward predominance of stab and segmented cells, increased IL-8, IL-10, fibrinogen, NT-proBNP, CRP, and troponin levels in both groups. IL-8 and IL-10 levels remained normal before and after surgery. Preoperative IL-6 level in group 1 was significantly higher than in group 2 (21,7±13,0 vs 2.5±2,2 pg/ml, р<0,001). Postoperatively, the difference was absent. The CRP level before surgery was high in both groups (3122.7±2175.8 vs 3670.8±2490.0 U/g) but decreased after CBS although remained higher in group 1 (1957.6±1660.3 vs 1069.8±630.2 U/g, р<0,001). Myeloperoxidase level increased postoperatively in both groups but the difference was insignificant. Fibrinogen and CRP in the postoperative period increased more significantly in group 2 than in group 1 (4,9±1,4 vs 4,4±1,1 g/l, р=0,02 and 8,6±2,2 vs 5,4±2,3 mg/l respectively, р<0,001). Conclusion. The study revealed an insignificant decrease in the number of AF episodes in the early post-CDS period in patients treated with omega-3 polyunsaturated fatty acids and atorvastatin compared with those given the latter medication alone. Also, fibrinogen and CRP levels as markers of inflammation increased while SOD antioxidative activity decreased.

Aims/Objectives/BackgroundGlobally, injuries cause more than 5 million deaths annually. Children and young people are a particularly vulnerable group and injuries are the leading cause of death in people aged 5–24 years globally and a leading cause of disability.In most low and middle-income countries where the majority of global child injury burden occurs, systems for routinely collecting injury data are limited. There is a continuing need for better data on childhood injuries and for injury surveillance.The aim of our study was to introduce a hospital-based injury surveillance tool – the first of its kind in Nepal and explore its feasibility. We undertook prospective collection of data on all injuries/trauma presenting to 2 hospital emergency departments to describe the epidemiology of paediatric hospital injury presentations and associated risk factors.Methods/DesignA new injury surveillance system for use in emergency departments in Nepal was designed and used to collect data on patients presenting with injuries. Data were collected prospectively in two hospitals 24 h a day over 12 months (April 2019 - March 2020) by trained data collectors using tablet computers.Abstract 432 Table 1Socio-demographic profile and characteristics of injury among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020 (N=2696)CharacteristicsFrequencyGender Male 1778 Female 918 Age groups 0–4 years 653 5–9 years 866 10–14 years 680 15–17 years 497 Median year (IRQ) 8 (5 – 13) Ethnicity/caste Janajati 1384 Brahmin/Chhetri 892 Dalit 148 Madhesi 146 Muslim 74 Others 50 Unknown 2 Place where injury occurred Home/Compound 1576 Highway/road/street 636 School 233 Recreational area 138 Workplace 76 Other 37 Activities at the time injury occurred Leisure/Play 1889 Travelling (other than to/from school/work) 296 Work 202 Travelling (to/from school/work) 184 Education 42 Organised sports 11 Other 52 Unknown 20 Intent of injury Unintentional 2560 Intentional (self-harm) 61 Intentional (assault) 75 Unintentional (n=2560) Fall 912 Animal or insect related 728 Road traffic injury 356 Injured by a blunt force 201 Stabbed, cut or pierced 176 Fire, burn or scald 65 Poisoning 52 Suffocation/choking 36 Electrocution 12 Drowning and submersion 7 Other 13 Unknown 2 Self-harm (n=61) Poisoning 38 Hanging, strangulation, suffocation 12 Stabbed, cut or pierced 6 Injured by blunt object 4 Other 1 Assault (n=75) Bodily force (physical violence) 43 Injured by blunt object 18 Stabbed, cut or pierced 8 Pushing from a high place 2 Poisoning 2 Sexual assault 1 Other 1 Nature of injury (one most severe) Cuts, bites or open wound 1378 Bruise or superficial injury 383 Fracture 299 Sprain, strain or dislocation 243 Internal injury 124 Head Injury/Concussion 83 Burns 67 Other 115 Unknown 2 Not recorded 2 Severity of injury No apparent injury 125 Minor 1645 Moderate 813 Severe 111 Not recorded 2 Disposition Discharged 2317 Admitted to hospital 164 Transferred to another hospital 179 Died 21 Leave Against Medical Advice (LAMA) 11 Unknown 2 Not recorded 2 Note:Not recorded = missing cases95% CI calculated using one proportion test and normal approximation method in Minitab.Abstract 432 Table 2Distribution of injuries by age-group, sex and mechanism of injury among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020Age groups & Sex0 - 4 years5 - 9 years10–14 years15–17 yearsMaleFemaleTotalIntent & mechanismsn (%)n (%)n (%)n (%)n (%)n (%)n (%)Unintentional Fall 239 (26.2) 328 (36.0) 249 (27.3) 96 (10.5) 636 (69.7) 276 (30.3) 912 (100) Animal or insect related 175 (24.0) 260 (35.7) 190 (26.1) 103 (14.1) 470 (64.6) 258 (35.4) 728 (100) Road traffic injury 49 (13.8) 108 (30.3) 86 (24.2) 113 (31.7) 223 (62.6) 133 (37.4) 356 (100) Injured by a blunt force 54 (26.9) 74 (36.8) 49 (24.4) 24 (11.9) 150 (74.6) 51 (25.4) 201 (100) Stabbed, cut or pierced 20 (11.4) 56 (31.8) 49 (27.8) 51 (29.0) 127 (72.2) 49 (27.8) 176 (100) Fire, burn or scald 42 (64.6) 10 (15.4) 9 (13.8) 4 (6.2) 27 (41.5) 38 (58.5) 65 (100) Poisoning 33 (63.5) 6 (11.5) 5 (9.6) 8 (15.4) 26 (50.0) 26 (50.0) 52 (100) Suffocation/choking 24 (66.7) 5 (13.9) 2 (5.6) 5 (13.9) 20 (55.6) 16 (44.4) 36 (100) Electrocution 2 (15.7) 0 (0.0) 3 (25.0) 7 (58.3) 10 (83.3) 2 (16.7) 12 (100) Drowning and submersion 1 (14.3) 1 (14.3) 3 (42.9) 2 (28.6) 3 (42.9) 4 (57.1) 7 (100) Other 6 (46.2) 4 (30.8) 3 (23.1) 0 (0.0) 10 (76.9) 3 (23.1) 13 (100) Unknown 2 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (100) 2 (100) Total 647 (25.3) 852 (33.3) 648 (25.3) 413 (16.1) 1702 (66.5) 858 (33.5) 2560 (100) Self-harm Poisoning 0 (0.0) 0 (0.0) 6 (15.8) 32 (84.2) 7 (18.4) 31 (81.6) 38 (100) Hanging 0 (0.0) 0 (0.0) 3 (25.0) 9 (75.0) 4 (33.3) 8 (66.7) 12 (100) Stabbed, cut or pierced 0 (0.0) 0 (0.0) 2 (33.3) 4 (66.7) 1 (16.7) 5 (83.3) 6 (100) Injured by blunt object 0 (0.0) 2 (50.0) 2 (50.0) 0 (0.0) 4 (100) 0 (0.0) 4 (100) Other 0 (0.0) 0 (0.0) 0 (0.0) 1 (100) 1 (100) 0 (0.0) 1 (100) Total 0 (0.0) 2 (3.3) 13 (21.3) 46 (75.4) 17 (27.9) 44 (72.1) 61 (100) Assault Bodily force (physical violence) 3 (7.0) 1 (2.3) 11 (25.6) 28 (65.1) 37 (86.0) 6 (14.0) 43 (100) Injured by blunt object 2 (11.1) 8 (44.4) 4 (22.2) 4 (22.2) 13 (72.2) 5 (27.8) 18 (100) Stabbed, cut or pierced 1 (12.5) 0 (0.0) 2 (25.0) 5 (62.5) 7 (87.5) 1 (12.5) 8 (100) Pushing from a high place 0 (0.0) 1 (50.0) 1 (50.0) 0 (0.0) 1 (50.0) 1 (50.0) 2 (100) Poisoning 0 (0.0) 1 (50.0) 0 (0.0) 1 (50.0) 1 (50.0) 1 (50.0) 2 (100) Sexual assault 0 (0.0) 0 (0.0) 1 (100) 0 (0.0) 0 (0.0) 1 (100) 1 (100) Other 0 (0.0) 1 (100) 0 (0.0) 0 (0.0) 0 (0.0) 1 (100) 1 (100) Total 6 (8.0) 12 (16.0) 19 (25.3) 38 (50.7) 59 (78.7) 16 (21.3) 75 (100) Abstract 432 Table 3Association of injury location, nature and severity with age among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020Age groups0 – 4 years5 – 9 years10–14 years15–17 yearsTotalChi-SquareInjury characteristicsn (%)n (%)n (%)n (%)n (%)P valueLocation of injury sustained Home/Compound 537 (34.1) 504 (32.0) 319 (20.2) 216 (13.7) 1576 (100) <0.001 Highway/road/street 85 (13.4) 196 (30.8) 190 (29.9) 165 (25.9) 636 (100) School 15 (6.4) 107 (45.9) 85 (36.5) 26 (11.2) 233 (100) Recreational area 9 (6.5) 44 (31.9) 55 (39.9) 30 (21.7) 138 (100) Workplace 1 (1.3) 4 (5.3) 19 (25.0) 52 (68.4) 76 (100) Other 6 (16.2) 11 (29.7) 12 (32.4) 8 (21.6) 37 (100) Total 653 (24.2) 866 (32.1) 680 (25.2) 497 (18.4) 2696 (100) Nature of injury Cuts, bites or open wound 328 (23.8) 506 (36.7) 314 (22.8) 230 (16.7) 1378 (100) <0.001 Bruise or superficial injury 81 (21.1) 99 (25.8) 118 (30.8) 85 (22.2) 383 (100) Fracture 48 (16.1) 101 (33.8) 112 (37.5) 38 (12.7) 299 (100) Sprain, strain or dislocation 48 (19.8) 78 (32.1) 72 (29.6) 45 (18.5) 243 (100) Internal injury 44 (35.5) 8 (6.5) 18 (14.5) 54 (43.5) 124 (100) Head Injury/Concussion 18 (21.7) 26 (31.3) 18 (21.7) 21 (25.3) 83 (100) Burns 42 (62.7) 9 (13.4) 10 (14.9) 6 (9.0) 67 (100) Other 41 (35.7) 38 (33.0) 18 (15.7) 18 (15.7) 115 (100) Unknown 2 (100) 0 (0.0) 0 (0.0) 0 (0.0) 2 (100) Total 652 (24.2) 865 (32.1) 680 (25.2) 497 (18.4) 2694 (100) Severity of injury No apparent injury 39 (31.2) 45 (36.0) 26 (20.8) 15 (12.0) 125 (100) <0.001 Minor 419 (25.5) 535 (32.5) 406 (24.7) 285 (17.3) 1645 (100) Moderate 171 (21.0) 262 (32.2) 225 (27.7) 155 (19.1) 813 (100) Severe 23 (20.7) 23 (20.7) 23 (20.7) 42 (37.8) 111 (100) Total 652 (24.2) 865 (32.1) 680 (25.2) 497 (18.4) 2694 (100) Abstract 432 Table 4Association of injury location, nature and severity with sex among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020SexMaleFemaleTotalChi-SquareInjury characteristicsn (%)n (%)n (%)P valueLocation of injury sustained Home/Compound 979 (62.1) 597 (37.9) 1576 (100) <0.001 Highway/road/street 421 (66.2) 215 (33.8) 636 (100) School 176 (75.5) 57 (24.5) 233 (100) Recreational area 111 (80.4) 27 (19.6) 138 (100) Workplace 62 (81.6) 14 (18.4) 76 (100) Other 29 (78.4) 8 (21.6) 37 (100) Total 1778 (65.9) 918 (34.1) 2696 (100) Nature of injury Cuts, bites or open wound 959 (69.6) 419 (30.4) 1378 (100) <0.001 Bruise or superficial injury 246 (64.2) 137 (35.8) 383 (100) Fracture 200 (66.9) 99 (33.1) 299 (100) Sprain, strain or dislocation 154 (63.4) 89 (36.6) 243 (100) Internal injury 50 (40.3) 74 (59.7) 124 (100) Head Injury/Concussion 59 (71.1) 24 (28.9) 83 (100) Burns 27 (40.3) 40 (59.7) 67 (100) Other 79 (68.7) 36 (31.3) 115 (100) Unknown 2 (100) 0 (0.0) 2 (100) Total 1776 (65.9) 918 (34.1) 2694 (100) Severity of injury No apparent injury 81 (64.8) 44 (35.2) 125 (100) 0.048 Minor 1102 (67.0) 543 (33.0) 1645 (100) Moderate 533 (65.6) 280 (34.4) 813 (100) Severe 60 (54.1) 51 (45.9) 111 (100) Total 1776 (65.9) 918 (34.1) 2694 (100) Abstract 432 Table 5Distribution of injuries by outcome and mechanism of injury among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020Outcome of injuryDischargedAdmittedTransferredDiedLAMAUnknownTotalIntent & mechanismsn (%)n (%)n (%)n (%)n (%)n (%)n (%)Unintentional Fall 787 (86.5) 65 (7.1) 53 (5.8) 0 (0.0) 4 (0.4) 1 (0.1) 910 (100) Animal/insect bite/sting 704 (96.7) 3 (0.4) 19 (2.6) 0 (0.0) 1 (0.1) 1 (0.1) 728 (100) Road traffic injury 260 (73.0) 47 (13.2) 44 (12.4) 5 (1.4) 0 (0.0) 0 (0.0) 356 (100) Injured by a blunt force 190 (94.5) 4 (2.0) 6 (3.0) 0 (0.0) 1 (0.5) 0 (0.0) 201 (100) Stabbed, cut or pierced 165 (93.8) 8 (4.5) 3 (1.7) 0 (0.0) 0 (0.0) 0 (0.0) 176 (100) Fire, burn or scald 52 (80.0) 12 (18.5) 1 (1.5) 0 (0.0) 0 (0.0) 0 (0.0) 65 (100) Poisoning 30 (57.7) 4 (7.7) 16 (30.8) 1 (1.9) 1 (1.9) 0 (0.0) 52 (100) Suffocation/choking/asphyxia 24 (66.7) 4 (11.1) 6 (16.7) 1 (2.8) 1 (2.8) 0 (0.0) 36 (100) Electrocution 7 (58.3) 2 (16.7) 2 (16.7) 1 (8.3) 0 (0.0) 0 (0.0) 12 (100) Drowning and submersion 4 (57.1) 0 (0.0) 0 (0.0) 3 (42.9) 0 (0.0) 0 (0.0) 7 (100) Other 12 (92.3) 1 (7.7) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 13 (100) Unknown 2 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (100) Total 2237 (87.5) 150 (5.9) 150 (5.9) 11 (0.4) 8 (0.3) 2 (0.1) 2558 (100) Self-harm Poisoning 5 (13.2) 8 (21.1) 23 (60.5) 0 (0.0) 2 (5.3) 0 (0.0) 38 (100) Hanging 1 (8.3) 0 (0.0) 1 (8.3) 10 (83.3) 0 (0.0) 0 (0.0) 12 (100) Stabbed, cut or pierced 6 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 6 (100) Injured by blunt object 4 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 4 (100) Other 1 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (100) Total 17 (27.9) 8 (13.1) 24 (39.3) 10 (16.4) 2 (3.3) 0 (0.0) 61 (100) Assault Bodily force (physical violence) 34 (79.1) 5 (11.6) 3 (7.0) 0 (0.0) 1 (2.3) 0 (0.0) 43 (100) Injured by blunt object 18 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 18 (100) Stabbed, cut or pierced 6 (75.0) 1 (12.5) 1 (12.5) 0 (0.0) 0 (0.0) 0 (0.0) 8 (100) Pushing from a high place 2 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (100) Poisoning 1 (50) 0 (0.0) 1 (50.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (100) Sexual assault 1 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (100) Other 1 (100) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (100) Total 63 (84.0) 6 (8.0) 5 (6.7) 0 (0.0) 1 (1.3) 0 (0.0) 75 (100) Abstract 432 Figure 1Seasonal variation of injuries identified by the injury surveillance system over a year among children attending emergency of hospitals in Makwanpur district, Nepal, April 2019 – March 2020Results/ConclusionsThe total number of ED patients with injury in the study was 10,154.2,696 were patients aged <18 years. Most injuries in children were unintentional and over half of children presenting with injuries were <10 years of age. Falls, animal bites/stings and road traffic injuries accounted for nearly 75% of all injuries with some (drowning, poisonings and burns) under-represented. Over half of injuries were cuts, bites and open wounds. The next most common injury types were superficial injuries (14.2%); fractures (11.1%); sprains/dislocations (9.0%). Child mortality was 1%.This is the biggest prospective injury surveillance study in a low or middle country in recent years and supports the use of injury surveillance in Nepal for reducing child morbidity and mortality through improved data.CHILD PAPER: RESULTS SECTIONTotal number of ED patients: 33046Total number of ED patient with injury: 10154 (adult=7458 & children=2696)8.2% (n=2696) patients with injury were children aged <18 yearsHetauda hospital: 2274 (84.3%)Chure hill hospital: 422 (15.7%)

Abstract Abstract 2298 The prevalence of prothrombotic markers and their association with thrombosis in pediatric solid tumor patients is not well defined. This study was aimed to discern the value of the following laboratory measures in assessment of thrombotic risk in pediatric patients with solid tumor: Prothrombin and activated partial thromboplastin times (PT and aPTT), D-dimer level, fibrinogen level, inherited and acquired hypercoagulability risk factors and soluble pro-inflammatory cytokines. Forty pediatric patients with newly-diagnosed malignancy and same number of age and sex-matched normal healthy controls were enrolled in the study. The median age was 7.5 and 8 years, respectively. Exclusion criteria included: history of autoimmune, hematologic, or chronic disease; history of chemotherapy administration; anticoagulant or anti-platelet therapy within 2 weeks of enrollment. Control subjects were selected from children undergoing elective surgery who had no known coagulation disorder and had not received anticoagulant or anti-platelet therapy within the previous 7 days. The following laboratory parameters were measured at the time of initial diagnosis: thromboelastography (TEG), thrombin generation assay (TGA), PT and aPTT, D-dimer level, fibrinogen level, lupus anticoagulant (LA) and anticardiolipin antibodies (ACA), interleukin (IL)-1b, IL-6, IL-8, and tumor necrosis factor (TNF)-α. Two years after completion of the laboratory component of the study, the patient cohort was retrospectively reviewed for the occurrence of thrombosis. Comparisons were made between patients vs. controls and patients with thrombosis vs. patients without thrombosis. As compared to controls, pediatric patients with newly diagnosed solid tumors demonstrated significantly higher prothrombotic markers, including TEG parameters, proinflammatory cytokines, and endogenous thrombin potentials assessed by TGA (Table 1). Among the 40 cancer patients, 4 (10%) experienced following thrombotic complications: cerebral sigmoid sinus thrombosis; right subclavian vein thrombosis; left internal jugular vein thrombosis; inferior vena cava thrombosis. All 4 patients had a hypercoagulable TEG profile as shown by increased maximum amplitude and elevated fibrinogen level at initial presentation. PT, fibrinogen level, and maximum amplitude of TEG were further predictive of thrombosis development in cancer patients (Table 2). Further studies are needed to support recommendations for prophylaxis of thrombosis in this vulnerable patient population.Table 1:Statistically significant parameters in cancer patients compared to controlsParameterN=40 Patients Median (range)N=40 Controls Median (range)P ValueFibrinogen (mg/dL)342 (202–734)266 (183–456)0.00D-dimer (μg/mL)1.4 (0.2–13.7)0.2 ((0.0–3.9)0.00Factor VIII (%)145 (59–361)100 (50–173)0.00ACA IgM (MPL)1.5 (0.0–7.4)1.2 (0.0–3.8)0.03Maximum amplitude (mm)66.9 (52.0–82.0)61.4 (55.0–68.0)0.00Coagulation index2.1 (−1.0–4.0)1.3 (0.0–3.0)0.00G (k d/sec)10.2 (5.4–23.1)8.0 (6.1–10.7)0.00AUC/ETP5300 (1970–6501)4864 (2300–5832)0.03IL-1β0.8 (0.1–6.5)0.5 (0.1–1.1)0.01IL-60.8 (0.1–18.8)0.2 (0.1–0.6)0.00TNF-α0.1 (0.0–2.3)0.1 (0.1–0.3)0.02Table 2:Statistically significant parameters in cancer patients with thrombosis compared to those without thrombosisParameterN=4 Thrombosis (+) Median (range)N=36 Thrombosis (−) Median (range)P ValuePT (sec)15.8 (15.6–18.2)13.9 (12.3–16.7)0.00Fibrinogen (mg/dL)579 (430–724)333 (202–734)0.00Maximum amplitude (mm)72.2 (67.3–74.8)66.4 (46.4–56.3)0.03G (k d/sec)13.3 (4.3–23.1)9.1 (10.3–14.8)0.03ACA IgM (MPL)4 (1–5)0 (0–16)0.04 Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction: PIK3CA mutations (mut) occur in ~40% of patients (pts) with HR+, HER2- ABC, and lead to phosphatidylinositol 3-kinase (PI3K) pathway hyperactivation, endocrine resistance, and poor survival in advanced disease. Alpelisib, an α-selective PI3K inhibitor and degrader, demonstrated efficacy in combination with fulvestrant in the Phase III SOLAR-1 trial in pts with PIK3CA-mut HR+, HER2- ABC. Notably, treatment benefit was not seen in pts without PIK3CA-mut tumors. Expert guidelines now recommend testing for PIK3CA mut at advanced diagnosis; however, data on PIK3CA mut prevalence in a broader population outside of clinical trials are limited. This real-world study snapshot describes the global prevalence of PIK3CA mut across geographic areas in HR+, HER2- ABC. Methods: This noninterventional, retrospective cohort study of ~2,000 adults (≥18 years) in ~20 countries from Europe, Asia, Middle East (ME), and Latin America (LA) is assessing the frequency of PIK3CA mut in HR+, HER2- ABC. Key inclusion criteria are histologically/cytologically confirmed estrogen/progesterone receptor-positive and HER2- ABC with available fresh or archival tumor tissue. The primary endpoint is the percentage of pts with PIK3CA-mut tumors, specifying each hotspot. Key secondary endpoints include the percentage of pts with PIK3CA-mut tumors by geographic region, demographics by PIK3CA status, clinical characteristics, number of lines of treatment in the advanced setting, and time to subsequent treatment by PIK3CA status. Tumor tissue samples are assessed at a local laboratory, at a minimum, for PIK3CA mut in C420R, E542K, E545A/D/G/K, Q546E/R, and H1047L/R/Y. All statistical analyses are descriptive, and the prognostic role of PIK3CA mut will be evaluated in the final analysis. Results: As of data cut-off (03 May 2021), 1,361 pts were enrolled in the Full Analysis Set, 574 (42.2%) of whom have tumors harboring a PIK3CA mut. Table 1 summarizes demographics and baseline characteristics in the mut and non-mut cohorts. Polymerase chain reaction and next-generation sequencing were the common methods used to assess PIK3CA mut in 570 (41.9%) and 625 (45.9%) of pts, respectively. PIK3CA mut rates are generally consistent across regions (30.7-44.0%, Table 2). Table 2 shows sample types and most common biomarker muts. Conclusions: In this study, PIK3CA mut rates, 43.0% in Asia, 44.0% in Europe, 40.9% in LA, and 30.7% in ME, were consistent across regions and closely followed previous reports, supporting the prevalence of this mut outside the trial setting and in a more diverse real-world pt population. The most common PIK3CA muts found in this study were H1047R, E545K, and E542K, consistent with SOLAR-1. PIK3CA mut rates were comparable in primary vs metastatic samples, supporting the existing body of evidence that PIK3CA mut are truncal and can be tested on any available tissue. Further analysis, including treatment-related information, will be presented. Table 1.Demographics, baseline characteristics, and disease history (Full Analysis Set)Mutant PIK3CANon-mutant PIK3CAAll patientsn=574n=787N=1,361Median age (range) at early disease diagnosisa50.0 (28.0-85.0)51.0 (23.0-83.0)51.0 (23.0-85.0)Median age (range) at advanced disease diagnosis57.0 (26.0-89.0)55.5 (23.0-87.0)56.0 (23.0-89.0)Median age (range) at enrollment59.5 (27.0-89.0)59.0 (23.0-87.0)59.0 (23.0-89.0)Sex, n (%)Female566 (98.6)778 (98.9)1,344 (98.8)Male8 (1.4)8 (1.0)16 (1.2)Unknown01 (0.1)1 (0.1)Race, n (%)White294 (51.2)418 (53.1)712 (52.3)Asian183 (31.9)239 (30.4)422 (31.0)Black or African American5 (0.9)13 (1.7)18 (1.3)Multiple1 (0.2)0 (0.0)1 (0.1)Unknown91 (15.9)117 (14.9)208 (15.3)Menopausal status at advanced disease diagnosis, n (%)bMutant PIK3CANon-mutant PIK3CAAll patientsn=566n=778N=1,344Postmenopausal410 (72.4)554 (71.2)964 (71.7)Premenopausal146 (25.8)214 (27.5)360 (26.8)Stage at initial diagnosis, n (%)Mutant PIK3CANon-mutant PIK3CAAll patientsn=574n=787N=1,361Recurrent breast cancerc299 (52.1)414 (52.6)713 (52.4)De novo advanced breast cancerd265 (46.2)357 (45.4)622 (45.7)Unknown10 (1.7)16 (2.0)26 (1.9)Time from early diagnosis to advanced disease, n (%)&lt;1 year32 (5.6)33 (4.2)65 (4.8)1 to &lt;2 years25 (4.4)25 (3.2)50 (3.7)2 to &lt;3 years29 (5.1)40 (5.1)69 (5.1)≥ 3 years149 (26.0)214 (27.2)363 (26.7)Extent of metastatic disease, n (%)Bone390 (67.9)456 (57.9)846 (62.2)Liver141 (24.6)204 (25.9)345 (25.3)Lung171 (29.8)245 (31.1)416 (30.6)Other127 (22.1)155 (19.7)282 (20.7)Number of metastatic sites, n (%)013 (2.3)21 (2.7)34 (2.5)1229 (39.9)324 (41.2)553 (40.6)&gt;1332 (57.8)442 (56.2)774 (56.9)aCensored patients initially diagnosed as de novo advanced breast cancer.bMenopausal status is applicable only to female patients. Sites are provided the option to choose from 1) Able to bear children, 2) Post-menopausal, or 3) Sterile - of childbearing age.cStage 0-IIIA at initial diagnosis.dStage IIIB, IIIC, or IV at initial diagnosis. Table 2.PIK3CA mutation status by region and sample typeFrequency of mutant PIK3CA by regionMutant/Number of patients% (95% CI)All patients574/1,36142.2 (39.5-44.9)Asia193/44943.0 (38.4-47.7)Europe312/70944.0 (40.3-47.8)Latin America27/6640.9 (29.0-53.7)Middle East42/13730.7 (23.1-39.1)Mutant PIK3CANon-mutant PIK3CAAll patientsn=574n=787N=1,361Region, n (%)Asia193 (33.6)256 (32.5)449 (33.0)Europe312 (54.4)397 (50.4)709 (52.1)Latin America27 (4.7)39 (5.0)66 (4.8)Middle East42 (7.3)95 (12.1)137 (10.1)Tumor tissue type, n (%)Archival tumor536 (93.4)754 (95.8)1,290 (94.8)Newly obtained tumor sample38 (6.6)33 (4.2)71 (5.2)Source of tumor biopsy, n (%)Primary372 (64.8)496 (63.0)868 (63.8)Metastatic202 (35.2)291 (37.0)493 (36.2)Most common PIK3CA mutationsa, n (%); 95% CIbH1047R197 (34.3); 95% CI (30.4-38.4)0197 (14.5); 95% CI (12.6-16.5)E545K100 (17.4); 95% CI (14.4-20.8)0100 (7.3); 95% CI (6.0-8.9)E542K66 (11.5); 95% CI (9.0-14.4)066 (4.8); 95% CI (3.8-6.1)aIncludes patients with double or multiple mutations.b95% Confidence Interval (CI) is calculated using exact binomial method. Citation Format: Pathmanathan Rajadurai, Tatiana Semiglazova, Alinta Hegmane, Fadi El Karak, Joanne W Chiu, Sudeep Gupta, Hamdy A Azim, Josef JEM Kitzen, Antoine Arnaud, Sina Haftchenary, Jiwen Wu, Lakshmi Menon-Singh, LaTonya Smith, Lyudmila Zhukova. PIK3CA registry: A noninterventional, descriptive, retrospective cohort study of PIK3CA mutations in patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-25.

Abstract Abstract 3442 Gains of 1q21 (CKS1B) in plasma cell neoplasms (PCNs) occur frequently and are generally thought to be indicative of an adverse prognosis. The International Myeloma Workshop Consensus Panel 2 (May 2011) found there is insufficient data to suggest routine use of 1q21 (CKS1B) in risk stratification of PCNs. This same Workshop confirmed that FISH testing in PCNs should be plasma cell (PC) specific. Despite this, many laboratories still perform conventional FISH (conv FISH) testing for PCNs primarily due to cost and labor constraints. This study had three objectives: 1) to examine the cytogenetic profile of patients with 1q21 abnormalities, 2) to observe if there was a difference between cytogenetic profiles and the incidence of each additional abnormality detected by cIg FISH vs. conv FISH, 3) to elucidate the significance of 1q21 in the prognosis of PCNs. The same probe set was used for both cIg and conv FISH: FGFR3/IGH [t(4;14)], IGH/MAF [t(14;16)], CCND1/IGH [t(11;14)], RB1/LAMP1 (13q14/13q34), TP53 [del(17)(p17.1)] and 1q21 (CKS1B). For conv FISH ≥200 nuclei/probe were scored. For cIg FISH 100 cIg+ cells were scored/probe and ≥25 cIg+ cells required for conclusive reporting. cIg FISH was performed on bone marrow aspirates in 276 cases (age range: 25–91 years); conv FISH 1007 cases (age range: 26–96 years) - all confirmed PCNs. For cIg FISH the %PC range was 0.3–95%; conv FISH 0.02–95%. With cIg FISH there were 246 (90%) abnormal, 14(5%) normal and 16 (5%) inconclusive results. Of the abnormal cases, 111 (45%) had gains of 1q21 (73 (66%) with 3 copies; 38 (34%) with ≥4 copies + [3+≥4 copies]), 127 (46%) had RB1 deletions (RB1−) or monosomy 13 (−13), and 77 (28%) had ‘other abnormalities' (no 1q21 or 13 abnormalities). For conv FISH there were 448 (44.5%) normal and 559 (55.5%) abnormal cases. Of the abnormal cases, 206 (20.5%) had gains of 1q21 (130 (63%) with 3 copies; 76 (37%) with ≥4 copies + [3+≥4 copies]), 240 (24%) RB1− or −13, and 221 (22%) ‘other abnormalities'. True amplification of 1q21 (CKS1B) [≥7–10 copies] was not observed by cIg or conv FISH. The detection rate (% cases) of each aberration occurring in the 111 1q21 positive cases detected by cIg FISH was: −13 31.9%, CCND1x3 23.9%, t(11;14) 10.9%, t(4;14) 9.4%, TP53− 6.9%, t(14;16) 6.5%, and RB1− 6.2%. For conv FISH it was: −13 8.5%, CCND1x3 6.8%, t(11;14) 2.9%, t(4;14) 2.5%, t(14;16) 1.9%, TP53− 1.8%, and RB1− 1.8%. Statistical analysis showed that the detection of additional aberrations in patients with 1q21 gains was significantly higher by cIg FISH compared to conv FISH (<0.0001). For cIg FISH 5.4% of the 1q21 patients had no other aberrations vs. 14.6% by conv FISH. The cytogenetic profile of the 1q21 positive cases identified by both technologies had a similar distribution of aberrations although the detection rates were quite different. The % cases: cIg vs. conv FISH was: t(4;14) 13.5% vs. 11.7%, t(14;16) 3.6% vs. 7.3%, t(11;14) 29.7% vs. 14.1%, TP53− 16.2% vs. 8.7%, RB1− 3.6% vs. 6.8%, −13 45% vs. 35.9%, CCND1x3 15.3% vs. 14.6%. Our conclusion is that cIg FISH significantly improves the detection rate of 1q21 abnormalities, the cytogenetic profiling of these patients, and allows more accurate risk stratification. 1q21 is important in the prognostic assessment of PCNs. With conv FISH, some 1q21 only patients (no other aberrations) will have false negative results leading to incorrect cytogenetic risk stratification. This rarely occurs with cIg FISH. Cytogenetic profiling of the other 1q21 cases can confirm high risk stratification if t(14;16), t(4;14) or TP53− is also present. If instead other favorable changes are present, the favorable prognosis is negated when there are ≥2 additional aberrations (≥3 changes are unfavorable). This will impact risk stratification. The results of this study advocate running a full panel of probes at diagnosis/follow up with the 1q21 probe, not just the high risk probes. This allows for cytogenetic profiling of 1q21 (CKS1B) positive cases thus aiding the cytogenetic risk stratification of patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: Large deletions involving the beta globin complex are relatively rare. They can be categorized generally into five groups by deletion size and/or location: 1) beta zero thalassemia (BZT); 2) delta beta thalassemia (DBT); 3) hereditary persistence of fetal hemoglobin (HPFH); 4) gamma delta beta thalassemia (GDBT); and 5) epsilon gamma delta beta thalassemia (EGDBT). These deletions are not well understood but often have significant clinical impact, either when present alone or in combination with other hemoglobin mutations. In this study, we analyze phenotypic and molecular data on a large number of cases with deletions in the beta globin gene complex to better classify these five groups of deletions as they occur in isolation. Methods: A query of the routine clinical testing patient files from the Mayo Clinic Metabolic Hematology and Molecular Genetics Laboratories from 2010 to 2015 identified 179 patients with a deletion confirmed by a Multiplex Ligation-dependent Probe Amplification (MLPA) assay. Twenty-four probes sets were placed from the 5' locus control region (LCR) to the 3' hypersensitivity region, spanning the beta globin gene complex. Using a Luminex LX200 flow cytometer, a gene dosage ratio was calculated for each probe set using the median fluorescent intensity value collected. The size and location of the deletion and patient phenotype were compared. Results: Of the 179 total cases, the following large deletions were identified: beta gene (HBB) (n = 47), delta (HBD) through HBB (n = 105), A-gamma (HBG2) through HBB (n = 20), and locus control region (LCR) through HBB (n = 7). One case had a deletion involving the LCR epsilon with the rest of the complex left intact. A subset (n = 60) of cases had compound hemoglobin mutations that altered the phenotype. The BZT cases had relatively high Hb A2 levels and variable Hb F levels consistent with promotor region loss. The main differences between DBT and HPFH included Hb F and Hb A2 levels. GDBT cases presented with median Hb F levels higher than that observed in DBTs, normal Hb A2, and microcytic anemia. EGDBT cases had variable features according to age of the patient and Hb F level; severe microcytic anemia was observed in neonates, milder microcytic anemia in young children, and microcytosis without anemia in an adult case. The phenotypic features of 119 patients with isolated large deletions are compiled in table 1. Conclusion: In general, all five categories of large deletions in an isolated heterozygous state can present with microcytic anemia and are typically benign with the exception of transient severe microcytic anemia in neonatal EGDBT cases. Although phenotypes associated with large deletions involving the beta globin gene complex are frequently distinctive, significant phenotypic overlap can be seen in a subset of cases. These cases require molecular analysis due to their clinical importance when in combination with another beta globin gene complex mutation for an adequate diagnosis and treatment approach. Table 1. Deletion type Age n HbF (%) HbA2 (%) Hb (g/dL) MCV (fL) RBC (10^12/L) RDW (%) MCH (pg/cell) BZT 20 6.3 (0.6-94.4) 6.8 (3.4-11.6) 11.1 (8.3-14.5) 65.4 (60.8-77.2) 5.4 (4.2-6.2) 19.2 (16.6-21.2) 20.9 (18.3-25.7) DBT 56 10.6 (2.7-22.4) 2.7 (2.5-3.1) 11.7 (8.6-14.4) 68.9 (61.3-83.5) 5.3 (4.1-7.3) 21.4 (18.2-26.8) 21.6 (19.9-39.2) HPFH 23 25.9 (17.6-39.7) 2.0 (1.5-2.4) 11.6 (8.1-16.7) 78.4 (60.2-101.9) 4.4 (3.0-6.3) 17.5 (14.1-22.3) 25.4 (17.6-29.7) GDBT 14 13.3 (8.2-19.0) 2.6 (1.8-2.7) 11.0 (8.6-14.1) 72.5 (57.9-82.1) 5.1 (3.5-6.2) 20.6 (17.4-23.5) 22 (17.9-25.1) EGDBT* 28 Y 1 0.3 3 13.3 59.4 6.9 15.4 19.2 1-4 Y 3 0.9 (0-1.6) 3.2 (2.9-3.5) 9.5 (8.8-13.3) 57.8 (57.6-59.4) 5.2 (4.9-6.9) 16.6 (15.4-17.4) 18.5 (18.1-19.2) <6 month 2 21.4 (14.8-27.9) 2.6 (2.2-2.9) 6.3 (6.0-6.6) 61.3 (59.9-62.6) 3.4 (3.3-3.3) 21.5 (21.2-21.7) 18.4 (18.1-18.7) medians, (min, max); *stratified by age Disclosures No relevant conflicts of interest to declare.

Background:Upadacitinib (UPA), an oral Janus kinase inhibitor, demonstrated significant improvements in signs, symptoms, and structural inhibition as monotherapy (mono) vs methotrexate (MTX) in MTX-naïve patients (pts) with rheumatoid arthritis (RA) through 48 weeks (wks).1Objectives:To report the efficacy and safety of UPA vs MTX mono up to 156 wks in pts with RA from the ongoing long-term extension (LTE) of the SELECT-EARLY trial.Methods:During the 48-wk double-blind study period, pts were randomized to UPA 15 or 30 mg once daily (QD) or MTX (titrated to 20 mg/wk by Wk 8). At Wk 26, pts who did not achieve Clinical Disease Activity Index (CDAI) remission (≤2.8) and had <20% improvement from baseline in tender or swollen joint count received blinded rescue therapy (addition of MTX for UPA groups and UPA 15 or 30 mg for MTX group). In the LTE, pts received open-label treatment once the last pt reached Wk 48. Efficacy assessments up to Wk 156 were summarized by randomized group and included American College of Rheumatology (ACR) responses, remission and low disease activity (LDA) measures, and change in modified Total Sharp Score (mTSS; up to 96 wks). Treatment-emergent adverse events (AEs) per 100 pt-years (PY) for pts on continuous mono were summarized through 156 wks. Non-responder imputation was used for binary endpoints for missing data and when pts received rescue therapy or prematurely discontinued the study drug.Results:Of 945 pts randomized and treated, 775 entered the LTE on study drug (including 57 rescued pts; MTX, 33; UPA 15 mg, 17; UPA 30 mg, 7). Overall, 161 (21%) pts discontinued during the LTE. At Wk 156, higher proportions of pts randomized to UPA achieved a 20/50/70% improvement in ACR response (ACR20/50/70), LDA, and remission vs MTX (Figure 1). Change from baseline in mTSS at Wk 96 favored UPA vs MTX (data not shown). Most AEs were numerically more frequent with UPA 30 mg. The overall rate of serious infection was numerically higher with UPA vs MTX (Table 1). Herpes zoster (HZ), neutropenia, non-melanoma skin cancer (NMSC), and creatine phosphokinase (CPK) elevation were more frequent with UPA vs MTX. Two active tuberculosis (TB) events were reported in each UPA arm; 3 adjudicated gastrointestinal (GI) perforation events were observed in the UPA 30 mg arm. Adjudicated major adverse cardiovascular events (MACEs) or venous thromboembolic events (VTEs) were comparable across treatment arms.Conclusion:UPA monotherapy showed sustained clinically meaningful responses including remission vs MTX through Wk 156 but higher rates of several AEs, including HZ, neutropenia, and CPK elevations; no new safety risks were observed compared with previous results.1,2References:[1]van Vollenhoven R, et al. Ann Rheum Dis 2019;78:376–7; 2. Cohen SB, et al. Ann Rheum Dis 2020;annrheumdis-2020-218510.Table 1.Safety overviewE/100 PY (95% CI)MTX mono(n=314; PY=601.9)UPA 15 mg QD mono(n=317; PY=703.4)UPA 30 mg QD mono(n=314; PY=687.6)Any AE240.2(228.0, 252.9)268.0(256.0, 280.4)292.5(279.8, 305.5)Any serious AE10.8 (8.3, 13.8)12.2 (9.8, 15.1)16.3 (13.4, 19.6)Any AE leading to discontinuation of study drug6.5 (4.6, 8.9)7.3 (5.4, 9.5)7.7 (5.8, 10.1)Any deatha0.7 (0.2, 1.7)0.9 (0.3, 1.9)1.0 (0.4, 2.1)Serious infection2.5 (1.4, 4.1)3.3 (2.1, 4.9)4.4 (2.9, 6.2)Opportunistic infection excluding TB and HZ0.2 (0.0, 0.9)0.1 (0.0, 0.8)0.3 (0.0, 1.1)HZ0.8 (0.3, 1.9)4.5 (3.1, 6.4)4.7 (3.2, 6.6)Active TB00.3 (0.0, 1.0)0.3 (0.0, 1.1)NMSC00.4 (0.1, 1.2)1.0 (0.4, 2.1)Malignancy other than NMSC1.0 (0.4, 2.2)0.6 (0.2, 1.5)1.2 (0.5, 2.3)Hepatic disorder14.1 (11.3, 17.5)12.5 (10.0, 15.4)15.0 (12.2, 18.2)GI perforationb000.4 (0.1, 1.3)Neutropenia2.2 (1.2, 3.7)4.5 (3.1, 6.4)5.7 (4.0, 7.8)CPK elevation1.8 (0.9, 3.3)7.7 (5.8, 10.0)15.4 (12.6, 18.6)MACEb0.3 (0.0, 1.2)0.4 (0.1, 1.2)0.6 (0.2, 1.5)VTEb0.3 (0.0, 1.2)0.4 (0.1, 1.2)0.6 (0.2, 1.5)Data were censored at the time of MTX or UPA addition for rescued ptsaIncludes treatment-emergent (≤30 days after the last dose of study drug) and non-treatment-emergent deaths. bAdjudicatedAcknowledgements:AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Russell Craddock, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.Disclosure of Interests:Ronald van Vollenhoven Speakers bureau: AbbVie, AstraZeneca, Biotest, Bristol-Myers Squibb, Galapagos, Gilead, GSK, Janssen, Pfizer, Sanofi, Servier, UCB, and Viela Bio, Consultant of: AbbVie, AstraZeneca, Biogen, Biotest, Bristol-Myers Squibb, Galapagos, Gilead, GSK, Janssen, Pfizer, Sanofi, Servier, UCB, and Viela Bio, Grant/research support from: Bristol-Myers Squibb, GSK, Eli Lilly, Pfizer, Roche, and UCB, Tsutomu Takeuchi Speakers bureau: AbbVie, AYUMI, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Dainippon Sumitomo, Eisai, Gilead, Mitsubishi Tanabe, Novartis, Pfizer, and Sanofi, Consultant of: Astellas, Chugai, and Eli Lilly, Grant/research support from: AbbVie, Asahi Kasei, Astellas, Chugai, Daiichi Sankyo, Eisai, Mitsubishi Tanabe, Nippon Kayaku, Shionogi, Takeda, and UCB, Jacob Aelion Grant/research support from: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos/Gilead, Genentech, GSK, Horizon, Janssen, Mallinckrodt, Nektar, Nichi-Iko, Novartis, Pfizer, Regeneron, Roche, Sanofi, Selecta, and UCB, Nilmo Chávez Speakers bureau: AbbVie, Janssen, and Pfizer, Consultant of: AbbVie, Janssen, and Pfizer, Grant/research support from: AbbVie, Galapagos, Gilead, Pfizer, and Sanofi, Pablo Mannucci Walter Consultant of: AbbVie, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech/Roche, GSK, Janssen, and UCB, Atul Singhal Consultant of: AbbVie, Aclaris, Amgen, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Gilead, Idorsia, Novartis, Oscotec, Pfizer, Regeneron, Roche/Genentech, Sanofi, Selecta, Takeda, UCB, and Viela Bio, Grant/research support from: AbbVie, Aclaris, Amgen, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Gilead, Idorsia, Novartis, Oscotec, Pfizer, Regeneron, Roche/Genentech, Sanofi, Selecta, Takeda, UCB, and Viela Bio, Jerzy Swierkot Speakers bureau: AbbVie, Accord, BMS, Janssen, MSD, Pfizer, Roche, Sandoz, and UCB, Consultant of: AbbVie, Accord, BMS, Janssen, MSD, Pfizer, Roche, Sandoz, and UCB, Grant/research support from: AbbVie, Accord, BMS, Janssen, MSD, Pfizer, Roche, Sandoz, and UCB, Alan Friedman Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Nasser Khan Shareholder of: May own stocks or options in AbbVie, Employee of: AbbVie, Yihan Li Shareholder of: May own stocks or options in AbbVie, Employee of: AbbVie, Xianwei Bu Shareholder of: May own stocks or options in AbbVie, Employee of: AbbVie, Justin Klaff Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Vibeke Strand Consultant of: AbbVie, Amgen, Arena, AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Celltrion, Eli Lilly, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen, Kiniksa, MSD, Myriad Genetics, Novartis, Pfizer, Regeneron, Sandoz, Sanofi, Setpoint, and UCB