Добірка наукової літератури з теми "666.221 : 681.7.031"

Abstract Introduction Chronotype refers to an individual’s preferred timing of sleep and wakefulness, which can be classified as ‘normal’ or ‘late’ chronotypes. The purpose of this study was to examine whether late sleep timing was associated with impaired mood and diabetes-related distress in persons with type 2 diabetes (T2D). Methods The study is a secondary analysis of pooled cross-sectional baseline data from two studies of treatment of obstructive sleep apnea (R01-DK96028) and insomnia (K24-NR016685) in persons with T2D. Sleep timing was measured by the bedtime from a 7-day sleep diary. “Normal” sleep timing was defined as bedtime between 9PM to 12AM ≥ 85% per week. “Late” sleep timing as bedtime after 12AM with normal sleep timing < 85% per week. Other sleep variables evaluated were sleep duration, daytime sleepiness (Epworth Sleepiness Scale [ESS]), and OSA severity (apnea-hypopnea index [AHI]). The Profiles of Mood States measured Total Mood Disturbance (TMD) and the subscales of Tension-Anxiety (T-A), Depression-Dejection (D-D), Anger-Hostility (A-H), Vigor-Activity (V-A), Fatigue-Inertia (F-I), and Confusion-Bewilderment (C-B). Diabetes-related distress was measured by the Problem Areas in Diabetes (PAID). Hierarchical multiple regression was performed to determine whether sleep timing was associated with mood and diabetes-related distress. Results The sample (N=296) had 61% with late sleep timing (n=181). Persons with normal vs late sleep timing were similar in age, sex, race, and education (p >.05). Persons with late sleep timing were less likely to be partnered, had shorter sleep duration and greater mood impairment (TMD and T-A, D-D, A-H, C-B subscales) than those with normal timing (all p values <.05); there was no significant difference by sleep timing in PAID scores (p=.256). Hierarchical regression analyses adjusting for demographics (age, sex, race, marital status, education level), clinical (HbA1c, BMI), and sleep variables (sleep duration, ESS, AHI) revealed that late sleep timing was not significantly associated with impaired mood (TMD and subscales) or PAID. However, ESS was statistically significant in predicting greater TMD (β=.310, p <.001), mood subscales (all p-values <.05) and PAID (β =.222, p <.001). Conclusion Daytime sleepiness, not late sleep timing, is a significant sleep-related symptom for increased mood impairment and diabetes-related distress in persons with T2D. Support (if any):

Background: We assessed long-term health-related quality of life (HRQoL) and functioning in adults receiving onabotulinumtoxinA for CM. Methods: Interim analysis of multicentre, prospective, observational study in adults naïve to botulinum toxin (NCT02502123). Mean change from baseline in Migraine-Specific Quality of Life (MSQ) score (primary); healthcare resource utilization (HRU) and work productivity (secondary) assessed in patients receiving 4 of 7 onabotulinumtoxinA treatments (Tx4; ~10 months). Results: Across treatments (baseline, n=196, post-Tx2, n=173, post-Tx4, n=137), the mean (SD) between-session interval and onabotulinumtoxinA dose was 13.1 weeks and 170.4 (17.2) U, respectively. MSQ scores increased significantly (P<0.0001) (baseline to post-Tx4; all role function domains). Patient percentages declined from baseline to post-Tx2 and post-Tx4 for emergency room visits (17.3%; 9.3%; 6.6%), hospital admissions (3.6%; 2.9%; 1.5%), and headache-related diagnostic testing (35.9%; 15.9%; 8.1%). The percentages of patients employed at baseline (73.5%) and post-Tx4 (72.3%) were similar. Hours worked increased slightly from baseline to post-Tx4 (28.0 [SD=15.4]; 29.4 [SD=16.0]). Headache-related missed work hours decreased (5.9 [SD=9.5]; 2.5 [SD=5.9]). Patients reported less headache-related impact on work productivity from baseline to post-Tx4 (5.4 [SD=2.1] vs 3.9 [SD=2.6]) and ability to perform daily activities (6.1 [SD=2.1] vs 4.2 [SD=2.8]). Conclusions: OnabotulinumtoxinA for CM improved HRQoL and work productivity and reduced HRU.

ObjectiveTo determine the proportion of patients surviving their cardiac surgery who experienced non-home discharge (NHD) over a 16-year period in Australia and New Zealand (ANZ).DesignRetrospective, multicentre, cross-sectional study over the time period 01 January 2004 to 31 December 2019.SettingAdult patients who underwent cardiac surgery from the Australia New Zealand Intensive Care Society Adult Patient Database (APD).ParticipantsAdult patients (age 18 and above) who underwent index coronary artery bypass grafting, cardiac valve surgery or combined valve/coronary surgery.ExposureThe primary exposure variable was the calendar year during the which the index surgery was performed.OutcomeThe primary outcome was NHD after the index surgery. NHD included discharge to locations such as nursing home, chronic care facility, rehabilitation and palliative care.ResultsWe analysed 252 924 index cardiac surgical admissions from 101 discrete sites with a median age of 68 years (IQR 60–76), of which 74.2% (187 662 out of 252 920) were males. Of these, 4302 (1.7%) patients died in hospital and 213 011 (84.2%) were discharged home, 18 010 (7.1%) were transferred to another hospital and 17 601 (7%) experienced NHD. In Australia, 14 457 (6.4%) of patients progressed to NHD, compared with 3144 (11.7%) in New Zealand. The rate of NHD increased significantly over time (adjusted OR per year=1.06, 95% CI, 1.06 to 1.07, p<0.001). Increasing age, female sex, non-elective surgery, surgery type and Acute Physiology and Chronic Health Evaluation III Score were all associated with significant increase in NHD.ConclusionsThere was significant increase in NHD after cardiac surgery over time in ANZ. This has significant clinical relevance for informed consent discussions between healthcare providers and patients, and for healthcare services planning.

Background For the reconstruction of acromioclavicular (AC) joint separation, several operative procedures have been described; however, the anatomic reconstruction of both coracoclavicular ligaments has rarely been reported. Purpose The aim of this biomechanical study is to describe a new procedure for anatomic reconstruction of the AC joint. Study Design Controlled laboratory study. Materials and Methods Forty fresh-frozen cadaveric shoulders were tested. Cyclic loading and a load-to-failure protocol was performed in vertical (native, n = 10; reconstructed, n = 10) and anterior directions (native, n = 10; reconstructed, n = 10) on 20 AC joints and repeated after anatomic reconstruction. Reconstruction of conoid and trapezoid ligaments was achieved by 2 TightRope devices (Arthrex, Naples, Florida). Dynamic, cyclic, and static loading until failure in vertical (n = 5) and horizontal (n = 5) directions were tested in native as well as reconstructed joints in a standardized setting. Results The native coracoclavicular ligaments in static load for vertical force measured 598 N (range, 409–687), elongation 10 mm (range, 6–14), and stiffness 99 N/mm (range, 67–130); static load for anterior force was 338 N (range, 186–561), elongation 4 mm (range, 3–7), and stiffness 140 N/mm (range, 70–210). The mean maximum static load until failure in reconstruction for vertical force was 982 N (range, 584–1330) ( P = .001), elongation 4 mm (range, 3–6) ( P < .001), and stiffness 80 N/mm (range, 66.6–105) ( P = .091); and for anterior static force 627 N (range, 364–973) ( P < .001), elongation 6.5 mm (range, 4–10) ( P = .023), and stiffness 78 N/mm (range, 46–120) ( P = .009). During dynamic testing of the native coracoclavicular ligaments, the mean amount of repetitions (100 repetitions per stage, stage 0–100 N, 100–200 N, 200–300 N, etc, and a frequency of 1.5 Hz) in native vertical direction was 593 repetitions (range, 426–683) and an average of 552 N (range, 452–683) load until failure. In vertical reconstructed testing, there were 742 repetitions (range, 488–893) ( P = .222; with a load until failure of 768 N (range, 486–900) ( P = .095). In the anterior direction load, the native ligament failed after an average of 365 repetitions (range, 330–475) and an average load of 360 N (range, 307–411), while reconstructed joints ended in 549 repetitions (range, 498–566) (P = .008J with a load until failure of 547 N (range, 490–585) ( P = .008). In all testing procedures, a preload of 5 N was performed. Conclusion The anatomic reconstruction of the AC joint using TightRope is a stable and functional anatomic reconstruction procedure. The reconstruction technique led to favorable in vitro results with equal or even higher forces than native ligaments. Clinical Relevance Through anatomic repair, stable function of the AC joint can be achieved in an anatomic manner.

Introduction The primary goal for treatment of higher-risk MDS patients (pts) is to improve overall survival (OS) and delay acute myeloid leukemia (AML) evolution. The IWG 2006 response criteria are used in clinical trials and in clinical practice for assessing efficacy of MDS therapies. These criteria were originally proposed by an international group of experts based on available data and consensus. In an ad hoc landmark analysis of the AZA-001 study using the 2006 IWG criteria, pts who achieved hematological improvement (HI), complete response (CR), marrow CR (mCR), or partial response (PR) demonstrated improved OS. The aim of this study is to validate the IWG 2006 response criteria among a large cohort of higher-risk MDS pts. Methods Pts with higher-risk MDS (intermediate-2 (Int-2) or High Risk by International Prognostic Scoring System (IPSS)) who had received treatment and for whom details of response and outcome were available were included from the MDS CRC database. Pts were also classified per IPSS-R. The best response to treatment was categorized per the published IWG 2006 response criteria as CR, PR, mCR, HI, stable disease (SD) or progressive disease (PD). The primary endpoint was OS. Results We identified 646 treated higher-risk MDS pts. Table-1 summarizes baseline characteristics. The first line treatment was hypomethylating agent-based therapy (HMA) in 470 pts (74%). The median duration of follow up was 23.2 months (mo) (95% CI: (19.9, 26.5). Median OS from diagnosis was significantly longer for pts with int-2 IPSS risk disease IPSS (26.2 mo (21.5, 29.7)) compared to those who were High Risk (18.8 mo (15.9, 23.6); (p = 0.026). Median OS from diagnosis also differed by IPSS-R category (p < 0.001): for pts with Low risk (n = 6) it was not reached; Intermediate risk it was 41.7 mo (31.8, NR); High Risk it was 28.4 mo (24.1, 33.2); and for pts with Very High it was 16.5 mo (15.3, 19.1). The best IWG 2006 response rate for first line therapy among evaluable pts (n=597) was CR in 93 pts (16%), mCR in 10 (2%), PR in 57(10%), HI in 60 (10%), SD in 233 (39%), and PD in 144 (24%). The median OS based on IWG 2006 best response for first line therapy was 41 mo for CR, 12 mo for mCR, 26 mo for PR, 13 mo for HI, 14 mo for SD and 7 mo for PD. (p <0.001). CR was associated with better outcome compared to all other response groups. Pts with PR, HI, and SD had better outcome compared to PD, and similar outcome among the 3 groups. There was no difference in rate of AML transformation among response groups except in PD pts compared to others. For pts who were treated with HMA as first line therapy, the best response rates by IWG 2006 criteria were CR in 15%, mCR in 2%, PR in 10%, HI in 12%, SD in 40% and PD in 21%. Median OS in mo from time of HMA therapy based on response was: CR 19 (16.3, NR), mCR: 9 (7.1, NR), PR: 13 (8.8, NR), HI: 11 (7.7, 19.0), SD: 11.0 (8.5, 12.6), and PD: 3 (2.3, 3.9). (p <0.001) The best response by IWG 2006 criteria remained predictive of OS after adjusting for IPSS-R risk group. HR 0.30 (95% CI 0.2-0.4) for CR, and 0.57 (95% CI 0.45-0.7) for mCR/PR/HI compared to PD, (p <0.001) Conclusions: The best response by IWG 2006 criteria to first line therapy in higher-risk MDS correlates with OS. Pts who achieved CR had the best OS, while pts who achieved SD or better response had improved outcome compared to PD, with mCR having an OS equivalent to SD. The CR by IWG 2006 response criteria can be used as a surrogate endpoint for OS in higher-risk MDS pts in randomized Phase II studies determining comparison arms of Phase III trials, and for regulatory purposes. Table 1. Baseline characteristics Variable Total n=646 Age Median 68 Gender Male 399/645(62%) Race White 566/633 (89%) t-MDS Yes 161/545/514 (30%) WHO RA RARS RCMD RAEB-I RAEB-II MDS-U MDS/MPN CMML 5/527 (1%) 7/527 (1%) 69/527 (13%) 1153/527 (29%) 284/527 (54%) 3/527 (1%) 5/527 (1%) 1/527 (1%) IPSS Intermediate-II High 468/646 (72%) 178/646 (28%) R-IPSS Very low Low Intermediate High Very High 0 6/621 (1%) 74/621 (12%) 211/621 (34%) 330/621 (53%) IPSS karyotype Good Intermediate Poor 135/642 (21%) 118/642 (18%) 389 /642 (61%) IPSS-R karyotype Very good Good Intermediate Poor Very poor 7/642 (1%) 137/642 (21%) 134/642 (21%) 118/642 (18%) 246/642 (38%) Allogeneic transplant Yes 158/554 (29%) First line therapy HMA Chemotherapy IMiDClinical trial other 470/634 (74%) 57/634 (9%) 43/634 (7%) 25/634 (4%) 38/634 (6%) Lab (mean) Hgb (n=514) Platelets (n=514) ANC (n=514) Bone marrow blasts (n=639) 9.2 94 1.6 10% Disclosures Komrokji: Novartis: Research Funding, Speakers Bureau; Incyte: Consultancy; Pharmacylics: Speakers Bureau; Celgene: Consultancy, Research Funding. Steensma:Incyte: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Onconova: Consultancy. Sekeres:TetraLogic: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Geographic barriers play a major role in access to health care and can increase health care utilization, especially in the Pediatric cancer patients where leukemia and treatment related complications are life threatening if not promptly managed. Objective: To assess health care utilization and costs in the pediatric ALL and AML population based on geographic distance from their primary cancer center based on the hypothesis that those living further away would incur greater cost due to delays in seeking and/or receiving care. Methods: To study this, we analyzed data from the Pediatric Health Information System (PHIS) database, which collects information for inpatient resource utilization at 45 children's hospitals in the USA. Data from patient's ≤ 21 years of age with the diagnosis of ALL or AML by ICD-9 code between the first quarter 2010 and the third quarter 2013 were used. The total number of hospitalizations and resources utilized and billed were measured 1 year following the index visit for ALL and 6 months for AML. Data collected were total cost / day, length of stay (LOS), and prevalence of ICU, TPN, and ventilator use. Stratified data depending on chemotherapy vs. non-chemotherapy stays were compared between children living <60 vs. >60 miles from the PHIS hospital using chi-square and Wilcoxon rank-sum statistics (Tables A & B). Results: Hospital admissions for chemotherapy (12,884) and non-chemotherapy (13,842) were recorded in the ALL group. Among chemotherapy admissions, no statistical significance in ICU, TPN or ventilator days in those <60 or ≥60 miles from a PHIS hospital was seen. There was significantly greater ICU (4.5% vs. 6.1%, p=0.001) and TPN (5.1% vs. 6.6%, p=0.004) use in children living >60 miles from the hospital admitted for non-chemo purposes. In children with AML, 2,855 chemo- and 1,414 non-chemo-related admissions were recorded. Those admitted for chemo living >60 miles away, had longer LOS, and more ICU use (4.1% vs. 6.7%, p=0.09), yet had lower cost per day. Those admitted for non-chemo purposes living ≥60 miles away had more prevalent ICU (8.3% vs. 14.5%, p=0.03) and TPN use (9.7% vs. 15.7%, p=0.06), and greater hospitalization cost and cost per day. Conclusion: Geographic distance from cancer centers increases health care resource consumption and cost especially in the unplanned admissions for complications in children with ALL and AML. Prospective studies are needed to confirm the resource utilization and costs associated with geographic distance from cancer center resources and should be considered in pediatric cancer center outreach planning. Table A. ALL Overall % <60 miles % ≥60 miles % p-value Chemo Admit Total Admits - N 12884 10663 (82.8%) 2221 (17.2%) ICU Use 0.4% 0.4% 0.4% 0.969 TPN Use 4.9% 5% 4.9% 0.860 Ventilator .004% .0038% .0045% 0.870 LOS (d): Median [IQR] 3 [2, 4] 3 [2, 4] 3 [2, 4] 0.367 Cost (US$): Median [IQR] 7820.5 [4850.4, 12251.3] 7861.9 [4862.6, 12395] 7666.9 [4825.2, 11647.3] 0.059 Cost/Day: Median [IQR] 2478.9 [1729.6, 3525.3] 2532.3 [1753.9, 3564.7] 2276.3 [1677, 3347] <.001 Non-Chemo Admit Total Admits - N 13842 11542 (83.4%) 2300 (16.6%) ICU Use 4.8% 4.5% 6.1% 0.001 TPN Use 5.4% 5.1% 6.6% 0.004 Ventilator 1.4% 1.4% 1.4% 0.938 LOS (d): Median [IQR] 3 [2, 7] 3 [2, 7] 3 [2, 7] 0.408 Cost (US$): Median [IQR] 8448.4 [4515.3, 18007.6] 8439.7 [4535.4, 18001.3] 8469.2 [4433, 18021.8] 0.706 Cost/Day: Median [IQR] 2559.1 [1866.4, 3580] 2578.8 [1888.1, 3595.5] 2438.6 [1786.2, 3476.8] <.001 Table B. AML Overall <60 miles ≥60 miles p-value Chemo Admit Total Admits - N 2855 2306 (80.8%) 549 (19.2%) ICU Use 4.60% 4.10% 6.70% 0.009 TPN Use 8.70% 8.70% 8.70% 0.958 Ventilator 0.90% 0.80% 1.30% 0.264 LOS (d): Median [IQR] 22 [5, 28] 22 [4, 28] 23 [6, 27] 0.010 Cost (US$): Median [IQR] 35483.6 [11914.3, 63738.3] 34782.5 [11339.9, 64075.8] 38384.5 [12817.1, 62315.9] 0.329 Cost/Day: Median [IQR] 2284.5 [1686.8, 3129.8] 2318 [1726.2, 3175.4] 2166.6 [1548.7, 2925.8] 0.002 Non-Chemo Admit Total Admits - N 1414 1165 (82.4%) 249 (17.6%) ICU Use 9.40% 8.30% 14.50% 0.003 TPN Use 10.70% 9.70% 15.70% 0.006 Ventilator 3.10% 2.80% 4.40% 0.191 LOS (d): Median [IQR] 7 [3, 17] 7 [3, 17] 8 [2, 17] 0.294 Cost (US$): Median [IQR] 17518.8 [7172.6, 46880.9] 16018.1 [7031.4, 42745.5] 23406.8 [7959.3, 58444.2] 0.014 Cost/Day: Median [IQR] 2967.8 [2085.7, 4053.9] 2907.4 [2086.1, 3914.9] 3317.8 [2063, 4590.2] 0.022 Disclosures No relevant conflicts of interest to declare.

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 Introduction In Colombia Breast cancer (BC), is the most frequent and has the highest mortality rate among all types of cancer. There are few studies of the genomic profile in unselected affected population by BC in Colombia. Some of these studies have only tested the presence of variants reported as founders named “Colombian Profile”.We conducted a large-scale genomic analysis using Whole Exome Sequencing (WES) to evaluate germline mutations in unselected BC patients. Methods This trial included 299 unselected BC female patients aged over 18 years old, without personal and family history of germline BC risk mutations.The protocol was approved by the IRC and EC of Fundación Cardioinfantil (FCI). All patients signed informed consent before recruitment.Genomic DNA was extracted from peripheral blood samples and was used to WES (Novogene Inc. Beijing, China). The variants were filtered using VarSeq v2.1.1 software, following the criteria: missense, non-sense, frameshift, and intronic variants, we additionally considered a MAF ≤0.01 for ATM, CHEK2, and PALB2 genes.Clinical significance of each variant was annotated according to the ACMG/AMP and ENIGMA guidelines.MLPA was assessed using the commercial kit SALSA MLPA Probemix P002-D1 for BRCA1 and P090-C1 for BRCA2 (MRC-Holland, Amsterdam).This study was financially supported by an unrestricted grant from Pfizer. Results This abstract is the first report from 299 patients. To determine the presence of germline variants in the patients a WES was performed. Here we describe the pathogenic and probably pathogenic mutations in BRCA1, BRCA2, ATM, CHEK2, PALB2. We found BRCA1/2 alterations were found in 3.7% of the patients (11 patients, IC 95% 1.7-5.6%), 5 patients in BRCA1 and 6 patients in BRCA2 (1.7% IC 95% 0.7-4%, and 2% IC 95% 0.9-4.4% respectively). We found 29 patients had mutations unrelated to BRCA1/2 (9.5% IC 95% 5.8-11.7%). The most frequently affected gene was ATM (17 patients, 5.7% IC95% 3.6-9%). Discussion and conclusion We found that 12.2% of the population of the study were carriers of a pathogenic/likely pathogenic variant in the evaluated genes, and interestingly 9.5% of them corresponded to non-BRCA1/2 genes. ATM variants have a prevalence of 5.7% in the whole population and represent 42% of all the variants. Other mutations in genes like BRCA2, ATM and CHEK2 were exclusive in non-TNBC. Meanwhile, BRCA1 and PALB2 mutations had higher frequencies in TNBC. We identified five novel mutations.We demonstrate that LGRs are not an important molecular cause in non-hereditary cases of BC.27% of the carriers of mutations in BRCA1/2 did not fulfilled NCCN criteria and 82% of the mutations are not described in “Colombian Profile”. These findings demonstrate the particular genetic profile in an unselected population with breast cancer, and this highlights the importance of WES as a molecular diagnostic tool. We think that universal germline testing in cancer should be considered. Baseline demographic and clinical characteristics Demographic and clinical characteristics of patients with pathogenic and likely pathogenic mutationsVariableBRCA1 n (%, IC 95%)BRCA2 n (%, IC 95%)ATM n (%, IC 95%)PALB2 n (%, IC 95%)CHEK2 n (%, IC 95%)Median age37.4 (22.4 – 54.3)45.5 (36.2 – 54.7)53.1 (45.4 – 60.7)55.8 (27.9 – 83.5)NA*Age≤ 50 years4 (80, 11.1 – 99.2%)4 (66.7, 14.8 – 95.8%)8 (47.1, 23.5 – 80%)2 (50, 24.7 – 97.5)NA*&gt; 50 years1 (20, 0.7 – 88.9%)2 (33.3, 4 – 85%)9 (52.9, 28 – 76.5%)2 (50, 24.7 – 97.5)OverweightYes4 (80, 11 – 99-2%)(33.3, 4 – 85%)9 (52.9, 28 – 76.5%) 3 (75, 0.4 – 99.5%)NA*No1 (20, 0.8 – 88.9%)(66.7, 14.9 – 94.8%)8 (47, 23.5 – 80%)1 (25, 0.4 – 95.9%)Estrogen receptor(+)2 (0.9%, 0.2 – 3.5%)5 (2.2%, 0.9 – 5.3%)16 (7.1%, 4.4 – 11.3%)3 (1.3%, 0.4 – 4.1%)3 (1.3%, 0.4 – 4.1%)(-)3 (4.3%, 1.4 – 12.6%)1 (1.4%, 0.2 – 9.6%)1 (1.4%, 0,2 – 9.6%)1 (1.4%, 0.2 – 9.6%)1 (1.4%, 0.2 – 9.6%)Progesterone receptor(+)2 (0.9%, 0.2 – 3.5%)5 (2.2%, 0.9 – 5.3%)13 (6%, 3.7 – 10.5%)3 (1.3%, 0.4 – 4.1%)4 (1.9%, 0.7 – 5%)(-)3 (4.3%, 1.4 – 12.6%)1 (1.4%, 0,2 – 9.6%)4 (4%, 1.7 – 11.7%)1 (1.4%, 0.2 – 9.6%)0HER-2 3+Yes1 (1.3%, 0.2 – 8.5%)1 (1.3%, 0.2 – 8.5%)4 (5%, 1.9 – 12.7%)1 (1.3%, 0.2 – 8.5%)2 (2.5%, 0.6 – 9.6%)No4 (1.9%, 0.7 – 4.9%)5 (2.3, 0.1 – 5.5%)13 (6%, 3.5- 10.2%)3 (1.4%, 0.4 – 4.3%)2 (0.9%, 0.2 – 3.7%)ER/Pgr y HER-2 negativeYes2 (5.1, 1.3 – 18.7%)001 (2.5%, 0-3 – 16.5%)0No3 (1.2%, 0.4 – 3.6%)6 (2.3%, 1 – 5.1%)17 (6.6%, 4-2 – 10.4%)3 (1.2%, 0.4 – 3.6%)4 (1.6%, 0.6 – 4.1%)Ki67&lt;20%0 1 (16.7, 0.9 – 81%) 5 (29.4, 11.5 – 57.1)0NA*≥20%5 (100%)5 (83.3, 18.6 – 99%)12 (70.6, 42.8 – 88.5%)4 (100%)Median tumoral size mm (min-max)24 (19.6 – 47.8)21 (12.5 – 29.5)24.9 (19.6 – 30.3)27.6 (0 – 59)NA* Lymph nodes involvementYes1 (0.7%, 0.1 – 4.6%)2 (1.3%, 0.3 – 5.2%)10 (6.7%, 3.6 – 12.1%)3 (2%, 0.6 – 6.1%)4 (2.7%, 1 – 7%)1No4 (2.7%, 1 – 7%)4 (2.7%, 1 – 7%)7 (4.7%, 2.2 – 9.5%)1 (0.7%, 0.1 – 4.6%)0MetastasisYes00001 (9%, 1.1 – 46.6%)2No5 (1.9%, 0.8 – 4.5%)6 (2.3%, 1 – 5%)17 (5.7%, 3.5 – 9.3%)4 (1.5 – 0.5 – 4%)3 (1.1%, 0.4 – 3.5%)Clinical stage (AJCC)I2 (40, 3.7 – 91.9%)1 (16.7, 0.9 – 81.3%)4 (23.5, 81 – 51.8%)0NA*II2(40 3.7 – 91.9%)4 (66.7, 14.8 – 95.8%)7 (41.2, 19.3 – 67.3%)4 (100%)III1 (20, 0.7 – 88.9%)1 (16.7, 0.9 – 81.3%)6 (23-3, 15.2 – 62.3%)0IV0000Family history for cancerYes4 (80, 11.1 – 99.2%)5 (83.3, 9 – 81.4%)13 (76.5 – 48.2 – 91.9%)2 (50, 2- 97.5%)NA*No1 (20, 0.7 – 88-9)1 (16.7, 0.9 – 81.4%)4 (23, 8 – 51.8%)2 (50, 2- 97.5%)NCCN criteriaYes4 (2.4%, 0.9 – 6.3%)4 (2.4%, 0.9 – 6.3%)NA*NA*NA*No1 (0.8%, 0.1 – 5.9%)2 (1.7%, 0.4 – 6.6%)Colombian profileYes1 (50%, 19 – 98%)31(50%, 19 – 98%)3NA*NA*NA*No4 (13.5%, 5 – 35.5%)5 (17%, 7 – 40%) Citation Format: Diana Carolina Sierra-Díaz, Adrien Morel, Dora Janeth Fonseca, Nora Contreras, Mariana Angulo-Aguado, Valentina Balaguera, Kevin Llinás-Caballero, Isabel Munevar, Mariana Borras, Mauricio Lema, Henry Idrobo, Daniela Trujillo, Norma Serrano, Ana Isabel Orduz, Diego Lopera, Jaime Gonzalez, Gustavo Rojas, Paula Londoño, Ray Manneh, Catalina Quintero, Paul Laissue, Rodrigo Cabrera, Carlos M Restrepo, William Mantilla. Genetic profile of germline mutations in unselected women with breast cancer in a Colombian population [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 P3-07-05.

Abstract BACKGROUND Risk reducing bilateral salpingo-oophorectomy (rrBSO) can provide up to a 90% reduction in the risk of developing ovarian cancer in women who are carriers of pathogenic variants in the BRCA1 and BRCA2 genes. National guidelines recommend risk reducing rrBSO once childbearing is complete and/or between the ages of 35-45. Previous studies have found that a large percentage of women who are eligible for rrBSO do not undergo the procedure and surgery is often done at later ages than recommended in the national guidelines. Research on factors associated with the uptake and timing of rrBSO is limited. Our study describes the percentages of women who are BRCA1 or BRCA2 carriers who elected rrBSO and ascertains the timing of the surgery relative to recommended age guidelines. We also identify patient characteristics associated with uptake of rrBSO. METHODS We conducted a retrospective cohort study in a large, integrated healthcare system in Southern California. The study population included women who were identified as BRCA1 or BRCA2 carriers in our electronic health record by ICD 9 and ICD 10 codes, and by review of our internal Cancer DNA database. Inclusion criteria included adults 18 years and older who were members of Kaiser Permanente Southern California between 2008 - 2018. Exclusion criteria included patients with an established diagnosis of ovarian cancer, with rrBSO at the time of study entry, and who were KP members for less than 12 months. Crude logistic regression models were used to determine odds ratios and 95% confidence intervals for associations between patient variables and uptake of rrBSO. RESULTS Of the 2,592 patients in the cohort, 1,326 were BRCA1 carriers and 1,266 were BRCA2 carriers. 1,003 (38.6%) women underwent rrBSO at a median age of 48.0 years (IQR: 42.0, 57.0). For the entire cohort, 38.6% identified as Caucasian, 30% identified as Hispanic/Latin American/Caribbean, 9.4% identified as Ashkenazi Jewish, 8.6% identified as Asian/Pacific Islander, and 1.5% identified as Black/African, and 1.4% identified as Near East/Middle Eastern. The baseline characteristics of our cohort can be seen in Table 1. Ovarian malignancy was incidentally detected on pathology evaluation in 1.5% of patients who elected rrBSO. The odds of rrBSO were lower among those who had used oral contraceptives for more than one year compared to those who hadn’t (OR=0.18, 95% CI: 0.11-0.30). A family history of ovarian cancer or breast cancer were also associated with higher odds of rrBSO, (OR=1.45, 95% CI: 1.21-1.73) and (OR=1.75; 95% CI: 1.48-2.08), respectively. The odds of rrBSO were also higher for those with a personal history of breast cancer (OR=2.29, 95% CI: 1.95-2.70). CONCLUSIONS In this large cohort of women who were BRCA1 and BRCA2 carriers and who were eligible for rrBSO, only a third of patients underwent risk reducing surgery. Among those who did undergo surgery, the median age at the time of procedure was higher than what is recommended in national guidelines. Family history of breast cancer and/or ovarian cancer, as well as personal history of breast cancer were associated with women selecting rrBSO. Table 1.No Oophorectomy (N=1589)rrBSO (N=1003)Total (N=2592)p valueAge at BRCA diagnosis&lt;0.00011 N158910032592 Mean (SD)43.9 (15.73)49.5 (11.11)46.1 (14.38) Median42.048.345.5 Range(18.1-95.7)(19.8-79.7)(18.1-95.7)Gene0.03522 BRCA1839 (52.8%)487 (48.6%)1326 (51.2%) BRCA2750 (47.2%)516 (51.4%)1266 (48.8%)Race/Ethnicity0.01002 African72 (4.5%)61 (6.1%)133 (5.1%) Ashkenazi Jewish134 (8.4%)110 (11%)244 (9.4%) Asian/Pacific Islander138 (8.7%)86 (8.6%)224 (8.6%) Black24 (1.5%)14 (1.4%)38 (1.5%) Hispanic/Latin American/Caribbean486 (30.6%)291 (29%)777 (30%) Multiple2 (0.1%)2 (0.2%)4 (0.2%) Native American/Alaskan2 (0.1%)0 (0%)2 (0.1%) Near East/Mideast24 (1.5%)13 (1.3%)37 (1.4%) White/Caucasian (Western/Northern/Central European)611 (38.5%)389 (38.8%)1000 (38.6%) Other77 (4.8%)37 (3.7%)114 (4.4%) Unknown19 (1.2%)0 (0%)19 (0.7%)Oral contraceptive use ≥ 1 year&lt;0.00012 N1456 (91.6%)987 (98.4%)2443 (94.3%) Y133 (8.4%)16 (1.6%)149 (5.7%)Family history of ovarian cancer0.00012 N1236 (77.8%)710 (70.8%)1946 (75.1%) Y353 (22.2%)293 (29.2%)646 (24.9%)Family history of breast cancer&lt;0.00012 N650 (40.9%)284 (28.3%)934 (36%) Y939 (59.1%)719 (71.7%)1658 (64%)Personal history of breast cancer&lt;0.00012 N1094 (68.8%)492 (49.1%)1586 (61.2%) Y495 (31.2%)511 (50.9%)1006 (38.8%)Age at prophylactic surgery NN/A893893 Mean (SD)49.6 (10.36)49.6 (10.36) Median48.048.0 Q1, Q342.0, 57.042.0, 57.0 Range(21.0-80.0)(21.0-80.0)Ovarian cancer&lt;0.00012 N1589 (100%)988 (98.5%)2577 (99.4%) Y0 (0%)15 (1.5%)15 (0.6%)1Kruskal Wallis 2Chi-Square Citation Format: Karen W Kwan, Stephanie W Morton, Joanie Chung. Timing and acceptance of bilateral prophylactic salpingo-oophorectomy among BRCA1 and BRCA2 mutation carriers enrolled in an integrated community-based health care system [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 P2-09-04.

Abstract G-CSF alone or in conjunction with chemotherapy is the most commonly used regimen to mobilize hematopoietic progenitor cells into peripheral blood (PB) for stem cell harvest. However, in about 10–30 % of patients when mobilized with this regimen, their hematopoietic progenitor cells are not effectively mobilized. We have adopted an approach of using higher doses of G-CSF from 16 to 36 ug/kg patient body weight to mobilize hematopoietic progenitor cells in patients that are poorly mobilized. Poor mobilization (PM) is defined as peak pre-apheresis PBCD34 count of &lt; 20 cells/uL, and good mobilization (GM) is defined as peak pre-apheresis PBCD34 count of ≥20 cells/uL in the expected mobilization time frame. In this study, we retrospectively assess our experience using this mobilization approach regarding its efficacy and safety. The success of stem cell transplantation was evaluated based on neutrophil engraftment defined as an ANC (absolute neutrophil count) &gt;500/uL, and platelet engraftment as a platelet count &gt;20,000/uL without platelet transfusions for 2 consecutive days, respectively, as well as day 15 lymphocyte count. Safety of stem cell mobilization, apheresis collection, and stem cell infusion were also evaluated. The results are shown in the tables below. Efficacy and safety of stem cell mobilization and collection Groups I (GM + L) II (GM + H) III (PM + L) IV (PM + H) L: low dose G-CSF (5-12 ug/kg); H: high dose G-CSF (15-36 ug/kg). Median (Range); No. (%) No. (patients/collections) 232/485 62/273 10/40 56/290 Peak PBCD34 (/uL) 85 (21-1320) 30 (21-99) 17 (11-20) 13.5 (5-20) CD34 yield (10^6) per recipient Kg wt/apheresis 3.7 (0.4-37.8) 1.2 (0.2-11.1) 1 (0.4-2.7) 0.7 (0.1-2.89) Total CD34 yield (10^6) per recipient kg wt 9.5 (3.2-37.8) 6.1 (3.2-17.9) 4.6 (2.2-7.2) 4.4 (1.08-6.66) GCSF toxicity (Pain, headache, etc) None 230 (47.4%) 161 (59%) 18 (45%) 158 (54.5%) Mild, no pain meds 155 (32%) 80 (29.3%) 18 (45%) 77 (26.6%) Moderate, requiring NSAIDS 49 (10.1%) 23 (8.4%) 1 (2.5%) 31 (10.7%) Severe, requiring Narcotics 51 (10.5%) 9 (3.3 %) 3 (7.5%) 24 (8.3%) Apheresis Toxicity (none) 87.8% 89.4% 85% 89% Apheresis Toxicity (mild to moderate) 12.2% 10.6% 15% 11% Efficacy and safety of stem cell infusion and engraftment Groups I II III IV Median (Range) No. (Patients /Infusions) 232/249 48/54 8/8 32/32 Total CD34 (10^6)/recipient kg wt infused 5.8 (2.5-18.9) 4.7 (2.0-8.8) 4.1 (2.1-5.9) 3.5 (2.4-5.8) Days to ANC of 500 10 (7-16) 10 (7-12) 10 (9-12) 10 (6-12) Days to platelet of 20,000/uL 10 (6-33) 10 (8-30) 13 (8-34) 10 (8-24) Day 15 (+/− 3) lymphocyte count (x 1000/uL) 0.53 (0-2.96) 0.38 (0.01-1.25) 0.43 (0.24-0.75) 0.74 (0.22-3.69) DMSO toxicity (none) 93.6% 77.8% 75% 90.6% DMSO toxicity (yes) 6.4% 22.2% 25% 9.4% In summary, multiple collections of autologous peripheral blood progenitor cells through hyperstimulation by G-CSF in poor mobilizers is an effective alternative approach for stem cell harvest. This approach results in successful engraftment, and is safe and well tolerated by patients.