Academic literature on the topic '[378.22:004.056]:378 (410) (043.3)'

Abstract Objective To investigate a new microarray-based method for single nucleotide polymorphisms (SNP) genotyping, and to study the role of 5,10-methylenetetrahydrofolate reductase(MTHFR) SNP in hematological malignancy pathogenesis in the Chinese population. Methods Prepared a aimed gene microarray based on cDNA microarray theory, dual-color fluorescenece hybridization was used for detecting SNP loci, sequencing was performed to confirm the results. In order to prepare the function SNP detection microarray, three different functionalized glass slides were selected, which were modified with 3-aminopropyltriethoxysilane (APTES), poly-l-lysine and glutaraldehyde, respectively. In order to obtain satisfied signal intensity, the ultraviolet crosslinking energy and the immobilized DNA concentration were optimized. By using the above SNP microarray, MTHFR C677T and A1298C SNP loci of 157 controls and 127 patients with hematological malignancy[30 multiple myeloma(MM),28 non-Hodgkin’s lymphoma(NHL), 22 acute lymphoblastic leukemia(ALL),40 acute myeloid leukemia(AML),7 chronic myeloid leukemia (CML)] from Jiangsu province were detected. Results Based on the immobilization efficiency, APTES modified glass slides were selected to fabricate DNA microarrays. The optimal ultraviolet crosslinking energy was 400 mJ and the optimal concentration of immobilized DNA was 300 mg/ml. Homozygous wild type, heterozygote type and homozygous mutant type yielded green, yellow and red fluorescence, respectively. Sequencing validated the results.The allele frequencies of MTHFR677C, 677T were 58.7%, 41.3% in patients and 66.9%, 33.1% in controls, respectively; the frequencies of 677CC, 677CT, 677TT genotype were 37.8%, 41.7%, 20.5% in patiens and 45.9%, 42.0%, 12.1% in controls, respectively. The allele frequencies of MTHFR1298A, 1298C were 83.1%, 16.9% in patients and 84.1%, 15.9% in controls, respectively; the frequencies of 1298AA, 1298AC, 1298CC genotype were 70.9%, 24.4%, 4.7% in patiens and 69.4%, 29.3%, 1.3% in controls, respectively. In multivariate analysis, significant difference was observed in the allele frequencies of C677T(χ2=4.08, P=.043) and in the genotype frequency of 677TT(OR 2.09, 95%CI 1.04–4.20, P=.039). The frequencies of 677TT (33.3%) and 1298CC(6.7%) in MM group were found significantly higher than in control group(OR 8.92, 95%CI 1.06–75.24, P=.006; OR=4.80, 95%CI 1.56–14.73, P=.044), resectively. No associations were found between any polymorphisms and susceptibilities to ALL, AML and NHL. Conclusions This microarray-based method is accurate, high-throughput and cheap, suitable for SNP genotyping in a large of individuals. MTHFRC677T polymorphisms influence the risk of hematological malignancy in Chinese population. Both MTHFR677TT and MTHFR1298CC genotype are susceptive to MM.

Background:Differences in efficacy outcomes favouring males vs females with rheumatoid arthritis (RA) have been reported with conventional synthetic (cs) disease-modifying antirheumatic drugs (DMARDs) and tumour necrosis factor inhibitors; results with Janus kinase inhibitors are less clear.Objectives:To assess the impact of sex on efficacy, safety and persistence in tofacitinib RA clinical trials.Methods:Efficacy and safety analyses included data pooled from Phase (P)3 randomised controlled trials (RCTs) of patients (pts) with RA and an inadequate response (IR) to methotrexate (NCT00847613; NCT00853385) or ≥1 DMARD (NCT00856544) who received tofacitinib 5 or 10 mg twice daily (BID), adalimumab (ADA) 40 mg Q2W or placebo (PBO), with background csDMARDs. Persistence analyses of pts receiving tofacitinib 5 or 10 mg BID ± csDMARDs used data pooled from two long-term extension trials (NCT00661661; NCT00413699). Efficacy outcomes to Month (M)12 included: ACR20/50/70 responses, changes from baseline (Δ; BL) in DAS28-4(ESR), CDAI, HAQ-DI and FACIT-F, and DAS28-4(ESR) remission (<2.6). Safety was evaluated to M24 for tofacitinib and ADA. Kaplan-Meier persistence analysis estimated time to discontinuation.Results:2265 pts were included from P3 RCTs. Demographics and BL characteristics were comparable across sexes and treatments. Tofacitinib or ADA vs PBO generally led to significantly higher ACR20/50/70 responses in both sexes through M6. To M12, ACR20/50/70 responses were broadly comparable across active treatments and between sexes, with significant differences favouring males at some time points, including M3 (Figure 1). Statistically significant differences favouring males vs females were observed in DAS28-4(ESR) remission rates at most time points, including M3 (Figure 1); a similar trend was observed for ΔDAS28-4(ESR). ΔCDAI, ΔHAQ-DI and ΔFACIT-F significantly favoured males vs females receiving tofacitinib 5 mg BID at most time points, while ΔHAQ-DI and ΔFACIT-F tended to favour females receiving tofacitinib 10 mg BID. Rates of adverse events (AEs), serious AEs (SAEs), severe AEs and discontinuations due to AEs were slightly higher in females vs males with tofacitinib 5 mg BID; this was generally reversed with tofacitinib 10 mg BID and ADA (Table 1). AEs of special interest (AESI) were comparable between sexes with tofacitinib and ADA, although low event numbers limit interpretation (Table 1). Time to all-cause discontinuation and discontinuation due to AEs/lack of efficacy with tofacitinib 5 mg BID was similar between sexes. Numerical differences favouring females vs males were observed for time to all-cause discontinuation and discontinuation due to AEs with tofacitinib 10 mg BID.Table 1.Safety summary to M24 in pooled DMARD-IR P3 RCTsTofacitinib5 mg BIDTofacitinib10 mg BIDADAPts with events,n (%)Females(N=707)Males(N=133)Females(N=698)Males(N=137)Females(N=162)Males(N=42)AEs562 (79.5)85 (63.9)529 (75.8)107 (78.1)119 (73.5)30 (71.4)SAEs107 (15.1)17 (12.8)71 (10.2)24 (17.5)13 (8.0)6 (14.3)Severe AEs86 (12.2)12 (9.0)55 (7.9)22 (16.1)14 (8.6)5 (11.9)Discontinuations due to AEs87 (12.3)10 (7.5)88 (12.6)10 (7.3)17 (10.5)5 (11.9)Death6 (0.8)4 (3.0)03 (2.2)1 (0.6)2 (4.8)AESISerious infections28 (4.0)6 (4.5)27 (3.9)6 (4.4)2 (1.2)1 (2.4)All HZ (non-serious/serious)35 (5.0)7 (5.3)43 (6.2)5 (3.6)2 (1.2)3 (7.1)MACE5 (0.7)02 (0.3)3 (2.2)03 (7.1)Malignancies (excl. NMSC)7 (1.0)1 (0.8)9 (1.3)1 (0.7)01(2.4)NMSC2 (0.3)5 (3.8)4 (0.6)2 (1.5)1 (0.6)1 (2.4)Venous thromboembolism3 (0.4)03 (0.4)1 (0.7)00HZ, herpes zoster; MACE, major adverse cardiovascular events; NMSC, non-melanoma skin cancerConclusion:Efficacy outcomes with tofacitinib and ADA were generally higher in males and comparable in females vs previously reported mixed population response rates for advanced therapies. Safety findings did not reveal a consistent pattern between sexes. Tofacitinib persistence was similar between sexes.Acknowledgements:Study sponsored by Pfizer Inc. Medical writing support was provided by Christina Viegelmann, CMC Connect, and funded by Pfizer Inc.Disclosure of Interests:H Niall Jones Consultant of: Pfizer Inc, Vibeke Strand Consultant of: AbbVie, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Celltrion, Corrona, Eli Lilly, Galapagos, Genentech/Roche, Gilead, GlaxoSmithKline, Ichnos, Inmedix, Janssen, Kiniksa, Merck, Myriad Genetics, Novartis, Pfizer Inc, Regeneron, Samsung, Sandoz, Sanofi, Scipher, SetPoint Medical, UCB, Hendrik Schulze-Koops Consultant of: AbbVie, Amgen, Biogen, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead Sciences, Hexal Sandoz, Hospira, Janssen-Cilag, MSD, Novartis, Pfizer Inc, Roche, UCB, Grant/research support from: Novartis, Pfizer Inc, Eduardo Mysler Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Janssen, Pfizer Inc, Roche, Sanofi, Grant/research support from: Eli Lilly, Pfizer Inc, Roche, Cassandra Kinch Shareholder of: Pfizer Canada ULC, Employee of: Pfizer Canada ULC, David C Gruben Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Rebecca Germino Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Lihi Eder Speakers bureau: AbbVie, UCB, Consultant of: AbbVie, Celgene, Eli Lilly, Novartis, Pfizer Inc, UCB, Grant/research support from: AbbVie, Eli Lilly, Pfizer Inc, UCB

Abstract ATRA combined to anthracycline based chemotherapy is the reference treatment of newly diagnosed APL and a role for maintenance treatment is supported by many studies, but some controversies remain, like the role of AraC. Methods: We performed a joint analysis of pts &lt; 65 yrs included in studies LPA99 (Spanish PETHEMA) and APL 2000 (French -Belgian-Swiss APL group) to address some of those issues. In LPA99, pts received ATRA combined to Idarubicin (IDA) for induction, followed by 3 consolidation courses, 2 with IDA and 1 with mitoxantrone (MTZ, at cumulative dose of 50 mg/m2), and maintenance with intermittent ATRA and continuous 6MP + MTX during 2 years. Pts with high (WBC &gt; 10000/mm3) and intermediate (WBC &lt; 10000/mm3, platelets &lt; 40000/mm3) Sanz score also received ATRA during consolidation courses and higher cumulative dose of IDA (100 mg/m2), vs low risk pts (no consolidation ATRA, cumulative IDA: 80 mg/m2). No AraC was administered in LPA99 trial. For APL 2000, we restricted the analysis to treatment groups that received AraC: pts with low or intermediate Sanz score received induction with ATRA and DNR (60 mg/m2/d x 3) + AraC (200 mg/m2/d x 7) followed by consolidation with a similar course and a final DNR (45 mg/m2/d x 3) + AraC (1 g/m2/12h x 8) course and the same maintenance as in LPA99. High risk patients received the same treatment, but with intrathecal CNS prophylaxis and, in pts &lt; 60 years, AraC 2g/m2/12h x 8 during the last course. Median follow up was 30 and 22 months in LPA99 (412 pts) and APL 2000 (180 pts), respectively. Comparisons were adjusted on age, gender, WBC and platelet counts. Results: In low and intermediate risk patients (308 LPA99 pts, 97 APL 2000 pts), the CR rates, 2 year cumulative incidence of relapse (CIR), EFS and survival were 96% and 99% (p = 0.2), 2.5% and 6.9% (p = 0.05), 93% and 91% (p = 0.6), 95% and 97% (p = 0.3) in LPA99 and APL 2000 trials, respectively. In high risk patients (104 LPA99 pts, 83 APL 2000 pts), the CR rate, 2 year CIR, EFS and survival were 84% and 95% (p = 0.02), 16.0% and 3.3% (p = 0.06), 69.2% and 88.0% (p = 0.01), 82.4% and 91.2% (p = 0.04) in LPA 99 and APL 2000, respectively. Four relapses in high risk pts involved the CNS in LPA99, vs. none in APL 2000. Three and 5 pts in LPA99 and APL 2000 respectively, died in CR, from treatment toxicity. Conclusion: This analysis suggests than in pts with WBC &lt; 10000/mm3, the current PETHEMA approach yields even fewer relapses than a classical ATRA + DNR + AraC regimen, while being less myelosuppressive. This may be due to the anthracyclines used (IDA and MTZ instead of DNR) and/or to the higher cumulative dose of anthracyclines used in LPA99 trial, and possibly also to consolidation ATRA for intermediate risk pts. On the other hand, in pts with high WBC counts, APL 2000 results yielded better EFS and survival and a strong trend for fewer relapses (including relapses involving the CNS), suggesting a beneficial role for AraC, possibly at high dose, in this subset of patients

Background:DISCOVER 2 (DISC 2) is a Phase 3 trial of anti-IL-23-specific mAb guselkumab (GUS) in psoriatic arthritis (PsA) pts, who experience impaired physical function, resulting in disability, work productivity loss, and economic consequences.1Objectives:To evaluate the effect of GUS on impaired work productivity and daily activity in DISC 2 using the Work Productivity and Activity Impairment Questionnaire: Psoriatic Arthritis (WPAI-PsA).Methods:Bio-naïve adults with active PsA despite nonbiologic DMARDs &/or NSAIDs received subcutaneous GUS 100 mg every (q) 4 weeks (W); GUS 100 mg W0, W4, q8W; or placebo (PBO). WPAI-PsA assesses, due to PsA over the previous week, work time missed (absenteeism), impairment while working (presenteeism), and impaired overall work productivity (absenteeism + presenteeism) and daily activity. Percentage change from baseline was analyzed for WPAI-PsA domains using mixed-effect model repeated measure (MMRM). Indirect savings from improved overall work productivity were estimated with 2018 US mean yearly wage estimate (all occupations).2Results:At Week 24, impaired overall work productivity and daily activity were improved 20-22% in GUS-treated and 10-11% in PBO-treated pts (Table). Potential yearly indirect savings from improved overall work productivity was $10,242 with GUS q8W and $10,404 with GUS q4W vs $5,648 with PBO; $4,594 and $4,756 difference, respectively.Conclusion:Improvement in overall work productivity and daily activity was greater with GUS versus PBO among pts with moderate-to-severe PsA, resulting in potential annual incremental economic gains.References:[1]Tillett W et al. Rheumatol (Oxford). 2012;51:275–283.[2]US Bureau of Labor Statistics. May 2018 National Occupational Employment and Wage Estimates United States.https://www.bls.gov/oes/current/oes_nat.htm#00-000Table.Model-based estimates of mean change from baseline in WPAI-PsA domains% change from baselinePBOGUS 100 mg q8WGUS 100 mg q4WW16W24W16W24W16W24Work time missed (absenteeism), n155152141145145143LSMean-4.6 (-7.2,-1.9)-3.5 (-6.4,-0.6)-3.5 (-6.2,-0.7)-3.1 (-6.1,-0.1)-4.7 (-7.4,-2.0)-3.8 (-6.8,-0.8)LSMean diff1.1 (-2.6,-4.8)*0.4 (-3.7,4.5)*-0.2 (-3.9,3.5)*-0.3 (-4.4,3.8)*Impairment while working (presenteeism), n131130125129133130LSMean-10.3 (-13.9,-6.7)-10.2 (-13.7,-6.7)-16.1 (-19.7,-12.4)-19.4 (-22.9,-15.9)-15.1 (-18.7,-11.5)-19.5 (-23.0,-16.0)LSMean diff-5.8 (-10.8,-0.8)†-9.2 (-14.0,-4.4)‡-4.8 (-9.7,0.1)*-9.3 (-14.1,-4.5)‡Overall work productivity impairment (absenteeism + presenteeism), n131130125129133130LSMean-11.2 (-15.0,-7.5)-10.9 (-14.6,-7.1)-15.9 (-19.7,-12.2)-19.7 (-23.4,-16.0)-15.8 (-19.5,-12.1)-20.0 (-23.7,-16.3)LSMean diff-4.7 (-9.9,0.5)*-8.8 (-14.0,-3.7)‡-4.6 (-9.7,0.5)*-9.2 (-14.3,-4.0)‡Daily activity impairment, n244244247246243245LSMean-10.6 (-13.3,-7.9)-10.3 (-13.1,-7.6)-17.1 (-19.8,-14.4)-21.5 (-24.2,-18.7)-17.0 (-19.7,-14.3)-20.5 (-23.2,-17.7)LSMean diff-6.5 (-10.2,-2.8)‡-11.1 (-15.0,-7.4)‡-6.5 (-10.2,-2.7)‡-10.2 (-14.0,-6.4)‡Data are % (95% CI)*p>0.05, †p<0.05,‡p<0.001LSmeans, p values based on MMRMLSmean diffs, p values vs PBOAcknowledgments:NoneDisclosure of Interests:Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, William Tillett Grant/research support from: AbbVie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer Inc, UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, MSD, Pfizer Inc, UCB, Speakers bureau: AbbVie, Amgen, Celgene, Lilly, Janssen, Novartis, Pfizer Inc, UCB, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Bei Zhou Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Prasheen Agarwal Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Steve Peterson Employee of: Janssen Research & Development, LLC, Chenglong Han Employee of: Janssen Research & Development, LLC

Abstract Treatment for pediatric acute myeloid leukemia (AML) involves multiple courses of intensive chemotherapy leading to prolonged neutropenia with substantive infection risks. Patients are typically hospitalized at each course for the duration of chemotherapy and associated marrow aplasia. Evaluations of early discharge and outpatient supportive care in adult AML patients demonstrate comparable mortality and shorter lengths of stay compared to standard discharge. Similar data in the pediatric setting are limited. We used data from the Pediatric Health Information System (PHIS) to evaluate course-specific mortality and resource utilization in AML patients who were discharged prior to count recovery relative to comparable patients who remained hospitalized. We used a cohort of children treated for new onset AML at children's hospitals in the US contributing to PHIS. Analyses were restricted to patients considered eligible for discharge prior to count recovery. Patients were categorized at each course as early or standard discharge. Discharges within 3 days after chemotherapy completion were considered “early”. Course-specific follow-up started on the last day of chemotherapy and continued until the earliest of: start of the subsequent course, death, or 50 days after commencement of chemotherapy. Resource utilization was determined based on daily billing data and reported as days of use per 100 hospital days. Case fatality rates and duration of hospitalization were compared using chi-square and Wilcoxon rank sum tests. Poisson regression with inpatient days as offset was used to compare resource use by discharge status. The study population included 996 patients representing 2358 courses. Fewer patients were discharged early following Induction I (7%) compared to subsequent courses (22-24%). Rates of early discharge varied greatly by hospital ranging from 0% to 100%. Across courses, patients discharged early experienced 8-12 fewer inpatient days (all p<0.001) despite readmission rates >90%. Case fatality rates were low across courses (0-1.3%) and did not differ significantly by discharge status. However, more early discharge patients required ICU level care at each course (7.2-18.1%) compared to standard discharge patients (2.0%-8.7%; all p <0.02). Table 1 presents resource utilization by discharge status with corresponding rate ratios (RR). Rates of antibiotic, vasopressor, and oxygen therapy use were each consistently elevated for early discharge patients. Following Intensification I and II, blood product use was also higher among those discharged early. The data suggest a similar overall survival and shorter hospitalization following early compared to standard discharge. However, based on increased rates of vasopressor and antibiotic use, early discharge patients may be at greater risk for life-threatening chemotherapy-related infectious complications. Table 1: Resource utilization (per 100 hospital days) by Discharge Status Early Discharge Standard Discharge Adjusted1 RR (95% CI) Antibiotics Induction I 153.6 131.5 1.17 (1.00, 1.36)* Induction II 146.7 89.7 1.64 (1.48, 1.81)* Intensification I 144.2 95.1 1.52 (1.38, 1.67)* Intensification II 162.4 117.0 1.39 (1.27, 1.52)* Antifungals Induction I 78.9 91.6 0.87 (0.72, 1.05) Induction II 84.1 90.2 0.93 (0.86, 1.01) Intensification I 79.3 87.9 0.90 (0.82, 1.00) Intensification II 80.6 84.1 0.96 (0.86, 1.07) Antivirals Induction I 6.2 11.6 0.56 (0.20, 1.56) Induction II 4.0 5.9 0.58 (0.41, 1.11) Intensification I 8.7 13.1 0.66 (0.39, 1.12) Intensification II 5.7 13.0 0.44 (0.19, 0.98) Blood Products Induction I 34.6 29.9 1.16 (0.99, 1.35) Induction II 26.9 24.2 1.12 (0.99, 1.26) Intensification I 28.4 20.5 1.38 (1.11, 1.72)* Intensification II 39.1 29.1 1.34 (1.17, 1.55)* Vasopressors Induction I 2.4 0.4 6.47 (2.67, 15.7)* Induction II 3.5 0.7 5.04 (2.13, 12.0)* Intensification I 3.6 0.5 6.62 (2.91, 15.0)* Intensification II 3.8 1.0 3.69 (1.74, 7.83)* Parenteral nutrition Induction I 14.5 17.0 0.85 (0.43, 1.70) Induction II 10.3 9.5 1.09 (0.64, 1.86) Intensification I 7.5 6.1 1.24 (0.76, 2.02) Intensification II 11.0 8.4 1.30 (0.87, 1.96) Supplemental Oxygen Induction I 4.6 0.9 4.95 (1.87, 13.1)* Induction II 2.0 0.5 3.86 (1.89, 7.92)* Intensification I 1.6 0.7 2.33 (1.15, 4.77)* Intensification II 4.7 1.6 2.93 (1.44, 5.93)* 1adjusted for age, race, sex, and insurance status; *statistically significant Disclosures No relevant conflicts of interest to declare.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. 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