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Sekii R, Kato S, Horita N, Utsunomiya D. Prognostic role of late gadolinium-enhanced MRI in confirmed and suspected cardiac sarcoidosis: meta-analysis. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024:10.1007/s10554-024-03191-y. [PMID: 39012402 DOI: 10.1007/s10554-024-03191-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 07/03/2024] [Indexed: 07/17/2024]
Abstract
The prognostic implications of late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) in the context of cardiac sarcoidosis (CS) have attracted considerable attention. Nevertheless, a subset of studies has undistinguished confirmed and suspected CS cases, thereby engendering interpretative ambiguities. In this meta-analysis, we evaluated the differences in cardiac MRI findings and their prognostic utility between confirmed and suspected CS. A literature search was conducted using PubMed, Web of Science, and Cochrane libraries to compare the findings of cardiac MRI and its prognostic value in CS and suspected CS. A meta-analysis was performed to compare the prevalence of LGE MRI, odds ratios, and hazard ratios for predicting cardiac events in both groups. A total of 21 studies encompassing 24 different populations were included in the meta-analysis (CS: 393 cases, suspected CS: 2151 cases). CS had a higher frequency of LGE of the left ventricle (87.2% vs. 36.4%, p < 0.0001) and right ventricle (62.1% vs. 23.8%, p = 0.04) than suspected CS. In patients with suspected CS, the presence of left ventricular LGE was associated with higher all-cause mortality [odds ratio: 5.70 (95%CI: 2.51-12.93), p < 0.0001, I2 = 8%, p for heterogeneity = 0.37] and ventricular arrhythmia [odds ratio: 15.51 (95%CI: 5.65-42.55), p < 0.0001, I2 = 0, p for heterogeneity = 0.94]. In contrast, in CS, not the presence but extent of left ventricular LGE was a significant predictor of outcome (hazard ratio = 1.83 per 10% increase of %LGE (95%CI: 1.43-2.34, p < 0.001, I2 = 15, p for heterogeneity = 0.31). The presence of left ventricular LGE was a strong prognostic factor in suspected sarcoidosis. However, the extremely high prevalence of left ventricular LGE in confirmed CS suggests that the quantitative assessment of LGE is useful for prognostic estimation.
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Kobayashi N, Matsumoto H, Somekawa K, Kaneko A, Fukuda N, Muraoka S, Ohtsu Y, Hirata M, Nagasawa R, Kubo S, Murohashi K, Fujii H, Aoki A, Watanabe K, Horita N, Hara Y, Kaneko T. Geographic and economic influences on benralizumab prescribing for severe asthma in Japan. Sci Rep 2024; 14:15190. [PMID: 38956390 PMCID: PMC11219854 DOI: 10.1038/s41598-024-65407-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 06/19/2024] [Indexed: 07/04/2024] Open
Abstract
Benralizumab, a monoclonal antibody targeting IL-5 receptors, reduces exacerbations and oral corticosteroid requirements for severe, uncontrolled eosinophilic asthma. In Japan, geographic disparities in asthma outcomes suggest differential prescribing and access. This study aimed to quantify regional prescribing variations for benralizumab nationwide. Using Japan's National Database (NDB) of insurance claims (2009-2019), benralizumab standardized claim ratios (SCRs) were calculated for 47 prefectures. Correlations between SCRs and other biologics' SCRs, economic variables like average income, and physician densities were evaluated through univariate analysis and multivariate regressions. Income-related barriers to optimal prescribing were examined. Wide variation emerged in benralizumab SCRs, from 40.1 to 184.2 across prefectures. SCRs strongly correlated with omalizumab (r = 0.61, p < 0.00001) and mepolizumab (r = 0.43, p = 0.0024). Average monthly income also positively correlated with benralizumab SCRs (r = 0.45, p = 0.0016), whereas lifestyle factors were insignificant. Respiratory specialist density modestly correlated with SCRs (r = 0.29, p = 0.047). In multivariate regressions, average income remained the most robust predictor (B = 0.74, p = 0.022). Benralizumab SCRs strongly associate with income metrics more than healthcare infrastructure/population factors. Many regions show low SCRs, constituting apparent prescribing gaps. Access barriers for advanced asthma therapies remain inequitable among Japan's income strata. Addressing affordability alongside specialist allocation can achieve better prescribing quality and asthma outcomes.
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Ledesma JR, Ma J, Zhang M, Basting AVL, Chu HT, Vongpradith A, Novotney A, LeGrand KE, Xu YY, Dai X, Nicholson SI, Stafford LK, Carter A, Ross JM, Abbastabar H, Abdoun M, Abdulah DM, Aboagye RG, Abolhassani H, Abrha WA, Abubaker Ali H, Abu-Gharbieh E, Aburuz S, Addo IY, Adepoju AV, Adhikari K, Adnani QES, Adra S, Afework A, Aghamiri S, Agyemang-Duah W, Ahinkorah BO, Ahmad D, Ahmad S, Ahmadzade AM, Ahmed H, Ahmed M, Ahmed A, Akinosoglou K, AL-Ahdal TMA, Alam N, Albashtawy M, AlBataineh MT, Al-Gheethi AAS, Ali A, Ali EA, Ali L, Ali Z, Ali SSS, Allel K, Altaf A, Al-Tawfiq JA, Alvis-Guzman N, Alvis-Zakzuk NJ, Amani R, Amusa GA, Amzat J, Andrews JR, Anil A, Anwer R, Aravkin AY, Areda D, Artamonov AA, Aruleba RT, Asemahagn MA, Atre SR, Aujayeb A, Azadi D, Azadnajafabad S, Azzam AY, Badar M, Badiye AD, Bagherieh S, Bahadorikhalili S, Baig AA, Banach M, Banik B, Bardhan M, Barqawi HJ, Basharat Z, Baskaran P, Basu S, Beiranvand M, Belete MA, Belew MA, Belgaumi UI, Beloukas A, Bettencourt PJG, Bhagavathula AS, Bhardwaj N, Bhardwaj P, Bhargava A, Bhat V, Bhatti JS, Bhatti GK, Bikbov B, Bitra VR, Bjegovic-Mikanovic V, Buonsenso D, Burkart K, Bustanji Y, Butt ZA, Camargos P, Cao Y, Carr S, Carvalho F, Cegolon L, Cenderadewi M, Cevik M, Chahine Y, Chattu VK, Ching PR, Chopra H, Chung E, Claassens MM, Coberly K, Cruz-Martins N, Dabo B, Dadana S, Dadras O, Darban I, Darega Gela J, Darwesh AM, Dashti M, Demessa BH, Demisse B, Demissie S, Derese AMA, Deribe K, Desai HD, Devanbu VGC, Dhali A, Dhama K, Dhingra S, Do THP, Dongarwar D, Dsouza HL, Dube J, Dziedzic AM, Ed-Dra A, Efendi F, Effendi DE, Eftekharimehrabad A, Ekadinata N, Ekundayo TC, Elhadi M, Elilo LT, Emeto TI, Engelbert Bain L, Fagbamigbe AF, Fahim A, Feizkhah A, Fetensa G, Fischer F, Gaipov A, Gandhi AP, Gautam RK, Gebregergis MW, Gebrehiwot M, Gebrekidan KG, Ghaffari K, Ghassemi F, Ghazy RM, Goodridge A, Goyal A, Guan SY, Gudeta MD, Guled RA, Gultom NB, Gupta VB, Gupta VK, Gupta S, Hagins H, Hailu SG, Hailu WB, Hamidi S, Hanif A, Harapan H, Hasan RS, Hassan S, Haubold J, Hezam K, Hong SH, Horita N, Hossain MB, Hosseinzadeh M, Hostiuc M, Hostiuc S, Huynh HH, Ibitoye SE, Ikuta KS, Ilic IM, Ilic MD, Islam MR, Ismail NE, Ismail F, Jafarzadeh A, Jakovljevic M, Jalili M, Janodia MD, Jomehzadeh N, Jonas JB, Joseph N, Joshua CE, Kabir Z, Kamble BD, Kanchan T, Kandel H, Kanmodi KK, Kantar RS, Karaye IM, Karimi Behnagh A, Kassa GG, Kaur RJ, Kaur N, Khajuria H, Khamesipour F, Khan YH, Khan MN, Khan Suheb MZ, Khatab K, Khatami F, Kim MS, Kosen S, Koul PA, Koulmane Laxminarayana SL, Krishan K, Kucuk Bicer B, Kuddus MA, Kulimbet M, Kumar N, Lal DK, Landires I, Latief K, Le TDT, Le TTT, Ledda C, Lee M, Lee SW, Lerango TL, Lim SS, Liu C, Liu X, Lopukhov PD, Luo H, Lv H, Mahajan PB, Mahboobipour AA, Majeed A, Malakan Rad E, Malhotra K, Malik MSA, Malinga LA, Mallhi TH, Manilal A, Martinez-Guerra BA, Martins-Melo FR, Marzo RR, Masoumi-Asl H, Mathur V, Maude RJ, Mehrotra R, Memish ZA, Mendoza W, Menezes RG, Merza MA, Mestrovic T, Mhlanga L, Misra S, Misra AK, Mithra P, Moazen B, Mohammed H, Mokdad AH, Monasta L, Moore CE, Mousavi P, Mulita F, Musaigwa F, Muthusamy R, Nagarajan AJ, Naghavi P, Naik GR, Naik G, Nair S, Nair TS, Natto ZS, Nayak BP, Negash H, Nguyen DH, Nguyen VT, Niazi RK, Nnaji CA, Nnyanzi LA, Noman EA, Nomura S, Oancea B, Obamiro KO, Odetokun IA, Odo DBO, Odukoya OO, Oh IH, Okereke CO, Okonji OC, Oren E, Ortiz-Brizuela E, Osuagwu UL, Ouyahia A, P A MP, Parija PP, Parikh RR, Park S, Parthasarathi A, Patil S, Pawar S, Peng M, Pepito VCF, Peprah P, Perdigão J, Perico N, Pham HT, Postma MJ, Prabhu ARA, Prasad M, Prashant A, Prates EJS, Rahim F, Rahman M, Rahman MA, Rahmati M, Rajaa S, Ramasamy SK, Rao IR, Rao SJ, Rapaka D, Rashid AM, Ratan ZA, Ravikumar N, Rawaf S, Reddy MMRK, Redwan EMM, Remuzzi G, Reyes LF, Rezaei N, Rezaeian M, Rezahosseini O, Rodrigues M, Roy P, Ruela GDA, Sabour S, Saddik B, Saeed U, Safi SZ, Saheb Sharif-Askari N, Saheb Sharif-Askari F, Sahebkar A, Sahiledengle B, Sahoo SS, Salam N, Salami AA, Saleem S, Saleh MA, Samadi Kafil H, Samadzadeh S, Samodra YL, Sanjeev RK, Saravanan A, Sawyer SM, Selvaraj S, Senapati S, Senthilkumaran S, Shah PA, Shahid S, Shaikh MA, Sham S, Shamshirgaran MA, Shanawaz M, Sharath M, Sherchan SP, Shetty RS, Shirzad-Aski H, Shittu A, Siddig EE, Silva JP, Singh S, Singh P, Singh H, Singh JA, Siraj MS, Siswanto S, Solanki R, Solomon Y, Soriano JB, Sreeramareddy CT, Srivastava VK, Steiropoulos P, Swain CK, Tabuchi T, Tampa M, Tamuzi JJLL, Tat NY, Tavakoli Oliaee R, Teklay G, Tesfaye EG, Tessema B, Thangaraju P, Thapar R, Thum CCC, Ticoalu JHV, Tleyjeh IM, Tobe-Gai R, Toma TM, Tram KH, Udoakang AJ, Umar TP, Umeokonkwo CD, Vahabi SM, Vaithinathan AG, van Boven JFM, Varthya SB, Wang Z, Warsame MSA, Westerman R, Wonde TE, Yaghoubi S, Yi S, Yiğit V, Yon DK, Yonemoto N, Yu C, Zakham F, Zangiabadian M, Zeukeng F, Zhang H, Zhao Y, Zheng P, Zielińska M, Salomon JA, Reiner Jr RC, Naghavi M, Vos T, Hay SI, Murray CJL, Kyu HH. Global, regional, and national age-specific progress towards the 2020 milestones of the WHO End TB Strategy: a systematic analysis for the Global Burden of Disease Study 2021. THE LANCET. INFECTIOUS DISEASES 2024; 24:698-725. [PMID: 38518787 PMCID: PMC11187709 DOI: 10.1016/s1473-3099(24)00007-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 12/09/2023] [Accepted: 01/08/2024] [Indexed: 03/24/2024]
Abstract
BACKGROUND Global evaluations of the progress towards the WHO End TB Strategy 2020 interim milestones on mortality (35% reduction) and incidence (20% reduction) have not been age specific. We aimed to assess global, regional, and national-level burdens of and trends in tuberculosis and its risk factors across five separate age groups, from 1990 to 2021, and to report on age-specific progress between 2015 and 2020. METHODS We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021) analytical framework to compute age-specific tuberculosis mortality and incidence estimates for 204 countries and territories (1990-2021 inclusive). We quantified tuberculosis mortality among individuals without HIV co-infection using 22 603 site-years of vital registration data, 1718 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, 680 site-years of mortality surveillance data, and 9 site-years of minimally invasive tissue sample (MITS) diagnoses data as inputs into the Cause of Death Ensemble modelling platform. Age-specific HIV and tuberculosis deaths were established with a population attributable fraction approach. We analysed all available population-based data sources, including prevalence surveys, annual case notifications, tuberculin surveys, and tuberculosis mortality, in DisMod-MR 2.1 to produce internally consistent age-specific estimates of tuberculosis incidence, prevalence, and mortality. We also estimated age-specific tuberculosis mortality without HIV co-infection that is attributable to the independent and combined effects of three risk factors (smoking, alcohol use, and diabetes). As a secondary analysis, we examined the potential impact of the COVID-19 pandemic on tuberculosis mortality without HIV co-infection by comparing expected tuberculosis deaths, modelled with trends in tuberculosis deaths from 2015 to 2019 in vital registration data, with observed tuberculosis deaths in 2020 and 2021 for countries with available cause-specific mortality data. FINDINGS We estimated 9·40 million (95% uncertainty interval [UI] 8·36 to 10·5) tuberculosis incident cases and 1·35 million (1·23 to 1·52) deaths due to tuberculosis in 2021. At the global level, the all-age tuberculosis incidence rate declined by 6·26% (5·27 to 7·25) between 2015 and 2020 (the WHO End TB strategy evaluation period). 15 of 204 countries achieved a 20% decrease in all-age tuberculosis incidence between 2015 and 2020, eight of which were in western sub-Saharan Africa. When stratified by age, global tuberculosis incidence rates decreased by 16·5% (14·8 to 18·4) in children younger than 5 years, 16·2% (14·2 to 17·9) in those aged 5-14 years, 6·29% (5·05 to 7·70) in those aged 15-49 years, 5·72% (4·02 to 7·39) in those aged 50-69 years, and 8·48% (6·74 to 10·4) in those aged 70 years and older, from 2015 to 2020. Global tuberculosis deaths decreased by 11·9% (5·77 to 17·0) from 2015 to 2020. 17 countries attained a 35% reduction in deaths due to tuberculosis between 2015 and 2020, most of which were in eastern Europe (six countries) and central Europe (four countries). There was variable progress by age: a 35·3% (26·7 to 41·7) decrease in tuberculosis deaths in children younger than 5 years, a 29·5% (25·5 to 34·1) decrease in those aged 5-14 years, a 15·2% (10·0 to 20·2) decrease in those aged 15-49 years, a 7·97% (0·472 to 14·1) decrease in those aged 50-69 years, and a 3·29% (-5·56 to 9·07) decrease in those aged 70 years and older. Removing the combined effects of the three attributable risk factors would have reduced the number of all-age tuberculosis deaths from 1·39 million (1·28 to 1·54) to 1·00 million (0·703 to 1·23) in 2020, representing a 36·5% (21·5 to 54·8) reduction in tuberculosis deaths compared to those observed in 2015. 41 countries were included in our analysis of the impact of the COVID-19 pandemic on tuberculosis deaths without HIV co-infection in 2020, and 20 countries were included in the analysis for 2021. In 2020, 50 900 (95% CI 49 700 to 52 400) deaths were expected across all ages, compared to an observed 45 500 deaths, corresponding to 5340 (4070 to 6920) fewer deaths; in 2021, 39 600 (38 300 to 41 100) deaths were expected across all ages compared to an observed 39 000 deaths, corresponding to 657 (-713 to 2180) fewer deaths. INTERPRETATION Despite accelerated progress in reducing the global burden of tuberculosis in the past decade, the world did not attain the first interim milestones of the WHO End TB Strategy in 2020. The pace of decline has been unequal with respect to age, with older adults (ie, those aged >50 years) having the slowest progress. As countries refine their national tuberculosis programmes and recalibrate for achieving the 2035 targets, they could consider learning from the strategies of countries that achieved the 2020 milestones, as well as consider targeted interventions to improve outcomes in older age groups. FUNDING Bill & Melinda Gates Foundation.
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Tanaka K, Meguro A, Hara Y, Endo L, Izawa A, Muraoka S, Kaneko A, Somekawa K, Hirata M, Otsu Y, Matsumoto H, Nagasawa R, Kubo S, Murohashi K, Aoki A, Fujii H, Watanabe K, Horita N, Kato H, Kobayashi N, Takeuchi I, Nakajima A, Inoko H, Mizuki N, Kaneko T. HLA-DQA1*01:03 and DQB1*06:01 are risk factors for severe COVID-19 pneumonia. HLA 2024; 104:e15609. [PMID: 39041300 DOI: 10.1111/tan.15609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 06/28/2024] [Accepted: 07/10/2024] [Indexed: 07/24/2024]
Abstract
The clinical spectrum of COVID-19 includes a wide range of manifestations, from mild symptoms to severe pneumonia. HLA system plays a pivotal role in immune responses to infectious diseases. The purpose of our study was to investigate the association between HLA and COVID-19 severity in a Japanese population. The study included 209 Japanese COVID-19 patients aged ≥20 years. Saliva samples were collected and used to determine the HLA genotype by HLA imputation through genome-wide association analyses. The association between HLA genotype and COVID-19 severity was then evaluated. The allele frequency was compared between patients with respiratory failure (severe group: 91 cases) and those without respiratory failure (non-severe group: 118 cases), categorising the data into three time periods: pre-Omicron epidemic period, Omicron epidemic period, and total period of this study (from January 2021 to May 2023). In comparing the severe and non-severe groups, the frequencies of the HLA-DQA1*01:03 (35.1% vs. 10.5%, odds ratio [OR] = 4.57, corrected p [pc] = 0.041) and -DQB1*06:01 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) alleles were significantly higher in the severe group during the pre-Omicron epidemic period. During the Omicron epidemic period, HLA-DQB1*06 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) was significantly higher in the severe group. During total period of this study, HLA-DQA1*01:03 (30.2% vs. 14.4%, OR = 2.57, corrected pc = 0.0013) and -DQB1*06:01 (44.5% vs. 26.7%, OR = 2.20, pc = 0.013) alleles were significantly higher in the severe group. HLA-DQB1*06:01 and -DQA1*01:03 were in strong linkage disequilibrium with each other (r2 = 0.91) during total period of this study, indicating that these two alleles form a haplotype. The frequency of the HLA-DQA1*01:03-DQB1*06:01 in the severe group was significantly higher than in the non-severe group during pre-Omicron epidemic period (32.4% vs. 7.9%, OR = 5.59, pc = 0.00072), and total period of this study (28.6% vs. 13.1%, OR = 2.63, pc = 0.0013). During Omicron epidemic period, the haplotype did not demonstrate statistical significance, although the odds ratio indicated a value greater 1. Frequencies of the HLA-DQA1*01:03 and -DQB1*06:01 alleles were significantly higher in severe COVID-19 patients, suggesting that these alleles are risk factors for severe COVID-19 pneumonia in the Japanese population.
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Kato S, Azuma M, Kodama S, Horita N, Utsunomiya D. Catheter ablation of atrial fibrillation improves outcomes in heart failure: An updated meta-analysis. ESC Heart Fail 2024. [PMID: 38923812 DOI: 10.1002/ehf2.14919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 06/10/2024] [Indexed: 06/28/2024] Open
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Kishimoto M, Iwayama T, Horita N, Fukumoto T. Case report: Usefulness of a picosecond Alexandrite laser therapy on atypical henna-induced Riehl's melanosis inferred from immunohistochemical analyses. Front Med (Lausanne) 2024; 11:1401938. [PMID: 38919937 PMCID: PMC11196749 DOI: 10.3389/fmed.2024.1401938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 05/27/2024] [Indexed: 06/27/2024] Open
Abstract
Riehl's melanosis is a pigmented dermatitis that manifests as brown-gray facial pigmentation with pigment incontinence and infiltration of cells in the upper dermis. The associated inflammation is induced by a variety of products such as drugs and cosmetics. Henna, commonly referred to as a hypoallergenic cosmetic, has been reported to cause Riehl's melanosis in some cases. Although skin depigmenting agents have been occasionally used, satisfactory results have not been obtained and no established therapeutic strategies exist to treat Riehl's melanosis. Meanwhile, picosecond lasers effectively treat other hyperpigmentation disorders. In this study, we report safe and effective treatment of henna induced-atypical Riehl's melanosis using a 755-nm picosecond Alexandrite laser. Immunohistochemical analyses revealed a potential role of CD8-positive lymphocytes in henna-induced inflammation and hyperpigmentation of the basal layer, and a role of melanophages in the pigmented dermis of Riehl's melanosis.
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Yamamoto S, Horita N, Hara J, Sasamoto M, Kanemitsu Y, Hara Y, Obase Y, Kaneko T, Niimi A, Mukae H. Benefit-Risk Profile of P2X3 Receptor Antagonists for Treatment of Chronic Cough: Dose-Response Model-Based Network Meta-Analysis. Chest 2024:S0012-3692(24)00693-7. [PMID: 38857780 DOI: 10.1016/j.chest.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 05/05/2024] [Accepted: 05/07/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Refractory or unexplained chronic cough disrupts quality of life and burdens health care systems around the world. The P2X3 receptor antagonist gefapixant is approved in many countries for its antitussive effects, but taste disturbances are a common adverse effect. Four newer, more selective P2X3 receptor antagonists have been developed to address this problem. RESEARCH QUESTION How does the benefit-risk profile vary across the five available P2X3 receptor antagonists? STUDY DESIGN AND METHODS A systematic review and network meta-analysis was conducted to evaluate the efficacy of P2X3 receptor antagonists, including gefapixant, sivopixant, eliapixant, camlipixant, and filapixant. Primary outcomes were a reduction rate in 24-h cough frequency and incidence of taste disturbance. Dose-response curves and median effective dose (ED50) were calculated. Effect size at ED50 was ranked according to the surface under the cumulative ranking curve. The confidence was evaluated by Confidence In Network Meta-Analysis. RESULTS Sixteen randomized controlled trials involving 4,904 participants were analyzed. The gefapixant regimen demonstrated an ED50 of 90.7 mg/d for cough frequency reduction. Gefapixant showed the highest antitussive effectiveness at ED50 (reduction rate in 24-h cough frequency: median, 28.1%; 95% credible interval [CrI], 21.0%-35.6%; ranked 1 of 5; moderate certainty) but the highest prevalence of taste disturbance (absolute risk difference per 100 patients: median, 38; 95% CrI, 27-51; ranked 5 of 5; high certainty) and the highest prevalence of discontinuation. Camlipixant had a well-balanced profile (reduction rate in 24-h cough frequency: median, 14.7%; 95% CrI, 5.4%-26.0%; ranked 3 of 5; low certainty; and taste disturbance; absolute risk difference per 100 patients; median, 2; 95% CrI, 1-6; ranked 2 of 5; low certainty). Placebo had a mean of 33.1% reduction in 24-h cough frequency. INTERPRETATION When used at safe doses, gefapixant had a favorable risk-benefit profile compared with the other four agents. Camlipixant showed initial promise, which may be further investigated by phase III trials currently underway. CLINICAL TRIAL REGISTRATION UMIN000050622; URL.
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Zhou S, Horita N, Shao T, Harrington M, Fujiwara Y. Endocrine adverse events in patients with cancer receiving perioperative immune checkpoint blockade: a meta-analysis of randomized controlled trials. Ther Adv Med Oncol 2024; 16:17588359241257874. [PMID: 38845790 PMCID: PMC11155360 DOI: 10.1177/17588359241257874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Accepted: 05/10/2024] [Indexed: 06/09/2024] Open
Abstract
Background Perioperative use of immune checkpoint blockade (ICB) improves survival in patients with early-stage cancer. Treatment-related adverse events (AEs), frequently involve the endocrine system which may increase perioperative complications and affect quality of life. Objective We conducted a meta-analysis to elucidate the impact of adding ICB to conventional neoadjuvant/adjuvant therapy on the incidence of endocrine AEs. Design A systematic review and meta-analysis of randomize-controlled trials (RCTs). Data sources and methods A systematic search of PubMed, Embase, Web of Science, and Cochrane library was performed for RCTs comparing groups with and without the addition of ICB to conventional perioperative therapy in patients with cancer. Outcomes included all-grade and grade 3-5 thyroiditis, hyperthyroidism, hypothyroidism, adrenal insufficiency, hypophysitis, type 1 diabetes mellitus, and hyperglycemia. The odds ratios (ORs) of all-grade and grade 3-5 endocrine were pooled using the random-effect model meta-analysis. Results Twenty-four RCTs comprising 12,199 patients were identified for meta-analysis. The addition of ICB was associated with higher incidence of thyroiditis [all grade: OR = 3.53 (95% confidence interval (CI): 1.88-6.64)], hyperthyroidism [all-grade: 7.18 (4.30-12.01); grade 3-5: 3.93 (1.21-12.82)], hypothyroidism [all-grade: 5.39 (3.68-7.90); grade 3-5: 3.63 (1.18-11.11)], adrenal insufficiency [all-grade: 3.82 (1.88-7.79); grade 3-5: 5.91 (2.36-14.82)], hypophysitis [all-grade: 10.29 (4.97-21.3); grade 3-5: 5.80 (1.99-16.92)], and type 1 diabetes mellitus [all-grade: 2.24 (1.06-4.74); grade 3-5: 3.49 (1.21-10.08)]. The cumulative incidence of each grade 3-5 endocrine AE was low (<1.3%). No grade 5 AEs leading to death were observed. Conclusion The addition of neoadjuvant/adjuvant ICB to conventional therapy was associated with an increased incidence of several endocrine AEs. Clinicians should be aware of the risk of endocrinopathy from the perioperative ICB use to facilitate risk-benefit discussion with patients with early-stage cancer. Trial registration The protocol of this research was registered in PROSPERO (CRD42022332624).
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Adachi S, Kirino Y, Higashitani K, Hirahara L, Maeda A, Horita N, Takase-Minegishi K, Yoshimi R, Nakajima H. Targeting enhanced cell death represents a potential therapeutic strategy for VEXAS syndrome. Rheumatol Adv Pract 2024; 8:rkae065. [PMID: 38854419 PMCID: PMC11157137 DOI: 10.1093/rap/rkae065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/08/2024] [Indexed: 06/11/2024] Open
Abstract
Objectives To unravel the mechanisms underlying cell death in the vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome using peripheral blood samples and to assess the clinical value of this knowledge. Methods Nine patients undergoing treatment for VEXAS syndrome at Yokohama City University Hospital were included in this study. Monocytes and neutrophils were isolated from peripheral blood and then monocytes were differentiated into polarized macrophages. Viable cell counts, cell death assays and measurements of various indicators such as high mobility group box 1 (HMGB1) concentration, extracellular adenosine triphosphate (ATP) concentration, annexin V level and caspase 1, 3 and 7 activities were performed. Results Elevated cell death of monocytes and neutrophils was observed in VEXAS syndrome patients, as indicated by cultured cell counts and cell death assays. Annexin V assays and measurements of caspase 1, 3 and 7 activities suggested increased apoptosis and pyroptosis in these cells. Serum HMGB1 levels were significantly elevated in VEXAS syndrome patients and decreased after prednisolone (PSL) dose escalation. Monocytes and neutrophils from the VEXAS group exhibited heightened extracellular ATP secretion, which was significantly reduced by soluble PSL co-culture. Conclusion This study confirms increased cell death of monocytes and neutrophils and damage-associated molecular patterns in VEXAS syndrome, and these findings may be valuable for drug screening, therapeutic strategies and as biomarkers.
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Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2204-2256. [PMID: 38762325 PMCID: PMC11121021 DOI: 10.1016/s0140-6736(24)00685-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/29/2024] [Accepted: 04/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. METHODS Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. FINDINGS In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]). INTERPRETATION Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. FUNDING Bill & Melinda Gates Foundation.
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2100-2132. [PMID: 38582094 PMCID: PMC11126520 DOI: 10.1016/s0140-6736(24)00367-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/15/2024] [Accepted: 02/22/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation.
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Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2057-2099. [PMID: 38521087 PMCID: PMC11122687 DOI: 10.1016/s0140-6736(24)00550-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/28/2023] [Accepted: 03/15/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Accurate assessments of current and future fertility-including overall trends and changing population age structures across countries and regions-are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. METHODS To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FINDINGS During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06) to 2·23 (2·09-2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1-canonically considered replacement-level fertility-in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7-29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59-2·08) in 2050 and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6-43·1) in 2050 and 54·3% (47·1-59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in 2050 and 7·1% (4·4-10·1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. INTERPRETATION Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FUNDING Bill & Melinda Gates Foundation.
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Tobe-Gai R, Tolani MA, Tolossa T, Tonelli M, Topor-Madry R, Topouzis F, Touvier M, Tovani-Palone MR, Trabelsi K, Tran JT, Tran MTN, Tran NM, Trico D, Trihandini I, Troeger CE, Tromans SJ, Truyen TTTT, Tsatsakis A, Tsermpini EE, Tumurkhuu M, Udoakang AJ, Udoh A, Ullah A, Ullah S, Ullah S, Umair M, Umakanthan S, Unim B, Unnikrishnan B, Upadhyay E, Urso D, Usman JS, Vaithinathan AG, Vakili O, Valenti M, Valizadeh R, Van den Eynde J, van Donkelaar A, Varga O, Vart P, Varthya SB, Vasankari TJ, Vasic M, Vaziri S, Venketasubramanian N, Verghese NA, Verma M, Veroux M, Verras GI, Vervoort D, Villafañe JH, Villalobos-Daniel VE, Villani L, Villanueva GI, Vinayak M, Violante FS, Vlassov V, Vo B, Vollset SE, Volovat SR, Vos T, Vujcic IS, Waheed Y, Wang C, Wang F, Wang S, Wang Y, Wang YP, Wanjau MN, Waqas M, Ward P, Waris A, Wassie EG, Weerakoon KG, Weintraub RG, Weiss DJ, Weiss EJ, Weldetinsaa HLL, Wells KM, Wen YF, Wiangkham T, Wickramasinghe ND, Wilkerson C, Willeit P, Wilson S, Wong YJ, Wongsin U, Wozniak S, Wu C, Wu D, Wu F, Wu Z, Xia J, Xiao H, Xu S, Xu X, Xu YY, Yadav MK, Yaghoubi S, Yamagishi K, Yang L, Yano Y, Yaribeygi H, Yasufuku Y, Ye P, Yesodharan R, Yesuf SA, Yezli S, Yi S, Yiğit A, Yigzaw ZA, Yin D, Yip P, Yismaw MB, Yon DK, Yonemoto N, You Y, Younis MZ, Yousefi Z, Yu C, Yu Y, Zadey S, Zadnik V, Zakham F, Zaki N, Zakzuk J, Zamagni G, Zaman SB, Zandieh GGZ, Zanghì A, Zar HJ, Zare I, Zarimeidani F, Zastrozhin MS, Zeng Y, Zhai C, Zhang AL, Zhang H, Zhang L, Zhang M, Zhang Y, Zhang Z, Zhang ZJ, Zhao H, Zhao JT, Zhao XJG, Zhao Y, Zhao Y, Zhong C, Zhou J, Zhou J, Zhou S, Zhu B, Zhu L, Zhu Z, Ziaeian B, Ziafati M, Zielińska M, Zimsen SRM, Zoghi G, Zoller T, Zumla A, Zyoud SH, Zyoud SH, Murray CJL, Gakidou E. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2162-2203. [PMID: 38762324 PMCID: PMC11120204 DOI: 10.1016/s0140-6736(24)00933-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. METHODS The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. FINDINGS Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). INTERPRETATION Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. FUNDING Bill & Melinda Gates Foundation.
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Y, Li Z, Libra M, Ligade VS, Likaka ATM, Lim LL, Lin RT, Lin S, Lioutas VA, Listl S, Liu J, Liu S, Liu X, Livingstone KM, Llanaj E, Lo CH, Loreche AM, Lorenzovici L, Lotfi M, Lotfizadeh M, Lozano R, Lubinda J, Lucchetti G, Lugo A, Lunevicius R, Ma J, Ma S, Ma ZF, Mabrok M, Machairas N, Machoy M, Madsen C, Magaña Gómez JA, Maghazachi AA, Maharaj SB, Maharjan P, Mahjoub S, Mahmoud MA, Mahmoudi E, Mahmoudi M, Makram OM, Malagón-Rojas JN, Malakan Rad E, Malekzadeh R, Malhotra AK, Malhotra K, Malik AA, Malik I, Malinga LA, Malta DC, Mamun AA, Manla Y, Mannan F, Mansoori Y, Mansour A, Mansouri V, Mansournia MA, Mantovani LG, Marasini BP, Marateb HR, Maravilla JC, Marconi AM, Mardi P, Marino M, Marjani A, Marrugo Arnedo CA, Martinez-Guerra BA, Martinez-Piedra R, Martins CA, Martins-Melo FR, Martorell M, Marx W, Maryam S, Marzo RR, Mate KKV, Matei CN, Mathioudakis AG, Maude RJ, Maugeri A, May EA, Mayeli M, Mazaheri M, Mazidi M, Mazzotti A, McAlinden C, McGrath JJ, McKee M, McKowen ALW, McLaughlin SA, McPhail MA, McPhail SM, Mechili EA, Mediratta RP, Meena JK, Mehari M, Mehlman ML, Mehra R, Mehrabani-Zeinabad K, Mehrabi Nasab E, Mehrotra R, Mekonnen MM, Mendoza W, Menezes RG, Mengesha EW, Mensah GA, Mensah LG, Mentis AFA, Meo SA, Meretoja A, Meretoja TJ, Mersha AM, Mesfin BA, Mestrovic T, Mhlanga A, Mhlanga L, Mi T, Micha G, Michalek IM, Miller TR, Mindlin SN, Minelli G, Minh LHN, Mini GK, Minja NW, Mirdamadi N, Mirghafourvand M, Mirica A, Mirinezhad SK, Mirmosayyeb O, Mirutse MK, Mirza-Aghazadeh-Attari M, Mirzaei M, Misgana T, Misra S, Mitchell PB, Mithra P, Mittal C, Mittal M, Moazen B, Mohamed AI, Mohamed J, Mohamed MFH, Mohamed NS, Mohammad-Alizadeh-Charandabi S, Mohammadi S, Mohammadian-Hafshejani A, Mohammad-pour S, Mohammadshahi M, Mohammed M, Mohammed S, Mohammed S, Mojiri-forushani H, Mokdad AH, Mokhtarzadehazar P, Momenzadeh K, Momtazmanesh S, Monasta L, Moni MA, Montazeri F, Moodi Ghalibaf A, Moradi M, Moradi Y, Moradi-Lakeh M, Moradinazar M, Moradpour F, Moraga P, Morawska L, Moreira RS, Morovatdar N, Morrison SD, Morze J, Mosaddeghi Heris R, Mosser JF, Mossialos E, Mostafavi H, Mostofinejad A, Mougin V, Mouodi S, Mousavi P, Mousavi SE, Mousavi Khaneghah A, Mpundu-Kaambwa C, Mrejen M, Mubarik S, Muccioli L, Mueller UO, Mughal F, Mukherjee S, Mukoro GD, Mulita A, Mulita F, Muniyandi M, Munjal K, Musaigwa F, Musallam KM, Mustafa G, Muthu S, Muthupandian S, Myung W, Nabhan AF, Nafukho FM, Nagarajan AJ, Naghavi M, Naghavi P, Naik GR, Naik G, Naimzada MD, Nair S, Nair TS, Najmuldeen HHR, Naldi L, Nangia V, Nargus S, Nascimento BR, Nascimento GG, Naser AY, Nasiri MJ, Natto ZS, Nauman J, Naveed M, Nayak BP, Nayak VC, Nayyar AK, Nazri-Panjaki A, Negash H, Negero AK, Negoi I, Negoi RI, Negru SM, Nejadghaderi SA, Nejjari C, Nematollahi MH, Nena E, Nepal S, Nesbit OD, Newton CRJ, Ngunjiri JW, Nguyen DH, Nguyen PT, Nguyen PT, Nguyen TT, Nguyen VT, Nigatu YT, Nikolouzakis TK, Nikoobar A, Nikpoor AR, Nizam MA, Nomura S, Noreen M, Noroozi N, Norouzian Baghani A, Norrving B, Noubiap JJ, Novotney A, Nri-Ezedi CA, Ntaios G, Ntsekhe M, Nuñez-Samudio V, Nurrika D, Oancea B, Obamiro KO, Odetokun IA, Ofakunrin AOD, Ogunsakin RE, Oguta JO, Oh IH, Okati-Aliabad H, Okeke SR, Okekunle AP, Okidi L, Okonji OC, Okwute PG, Olagunju AT, Olaiya MT, Olanipekun TO, Olatubi MI, Olivas-Martinez A, Oliveira GMM, Oliver S, Olorukooba AA, Olufadewa II, Olusanya BO, Olusanya JO, Oluwafemi YD, Oluwatunase GO, Omar HA, Omer GL, Ong S, Onwujekwe OE, Onyedibe KI, Opio JN, Ordak M, Orellana ER, Orisakwe OE, Orish VN, Orru H, Ortega-Altamirano DV, Ortiz A, Ortiz-Brizuela E, Ortiz-Prado E, Osuagwu UL, Otoiu A, Otstavnov N, Ouyahia A, Ouyang G, Owolabi MO, Oyeyemi IT, Oyeyemi OT, Ozten Y, P A MP, Padubidri JR, Pahlavikhah Varnosfaderani M, Pal PK, Palicz T, Palladino C, Palladino R, Palma-Alvarez RF, Pana A, Panahi P, Pandey A, Pandi-Perumal SR, Pando-Robles V, Pangaribuan HU, Panos GD, Pantazopoulos I, Papadopoulou P, Pardhan S, Parikh RR, Park S, Parthasarathi A, Pashaei A, Pasupula DK, Patel JR, Patel SK, Pathan AR, Patil A, Patil S, Patoulias D, Patthipati VS, Paudel U, Pawar S, Pazoki Toroudi H, Pease SA, Peden AE, Pedersini P, Peng M, Pensato U, Pepito VCF, Peprah EK, Pereira G, Pereira J, Pereira M, Peres MFP, Perianayagam A, Perico N, Petcu IR, Petermann-Rocha FE, Pezzani R, Pham HT, Phillips MR, Pierannunzio D, Pigeolet M, Pigott DM, Pilgrim T, Pinheiro M, Piradov MA, Plakkal N, Plotnikov E, Poddighe D, Pollner P, Poluru R, Pond CD, Postma MJ, Poudel GR, Poudel L, Pourali G, Pourtaheri N, Prada SI, Pradhan PMS, Prajapati VK, Prakash V, Prasad CP, Prasad M, Prashant A, Prates EJS, Purnobasuki H, Purohit BM, Puvvula J, Qaisar R, Qasim NH, Qattea I, Qian G, Quan NK, Radfar A, Radhakrishnan V, Raee P, Raeisi Shahraki H, Rafiei Alavi SN, Rafique I, Raggi A, Rahim F, Rahman MM, Rahman M, Rahman MA, Rahman T, Rahmani AM, Rahmani S, Rahnavard N, Rai P, Rajaa S, Rajabpour-Sanati A, Rajput P, Ram P, Ramadan H, Ramasamy SK, Ramazanu S, Rana J, Rana K, Ranabhat CL, Rancic N, Rani S, Ranjan S, Rao CR, Rao IR, Rao M, Rao SJ, Rasali DP, Rasella D, Rashedi S, Rashedi V, Rashid AM, Rasouli-Saravani A, Rastogi P, Rasul A, Ravangard R, Ravikumar N, Rawaf DL, Rawaf S, Rawassizadeh R, Razeghian-Jahromi I, Reddy MMRK, Redwan EMM, Rehman FU, Reiner Jr RC, Remuzzi G, Reshmi B, Resnikoff S, Reyes LF, Rezaee M, Rezaei N, Rezaei N, Rezaeian M, Riaz MA, Ribeiro AI, Ribeiro DC, Rickard J, Rios-Blancas MJ, Robinson-Oden HE, Rodrigues M, Rodriguez JAB, Roever L, Rohilla R, Rohloff P, Romadlon DS, Ronfani L, Roshandel G, Roshanzamir S, Rostamian M, Roy B, Roy P, Rubagotti E, Rumisha SF, Rwegerera GM, Rynkiewicz A, S M, S N C, S Sunnerhagen K, Saad AMA, Sabbatucci M, Saber K, Saber-Ayad MM, Sacco S, Saddik B, Saddler A, Sadee BA, Sadeghi E, Sadeghi M, Sadeghian S, Saeed U, Saeedi M, Safi S, Sagar R, Saghazadeh A, Saheb Sharif-Askari N, Sahoo SS, Sahraian MA, Sajedi SA, Sajid MR, Sakshaug JW, Salahi S, Salahi S, Salamati P, Salami AA, Salaroli LB, Saleh MA, Salehi S, Salem MR, Salem MZY, Salimi S, Samadi Kafil H, Samadzadeh S, Samara KA, Samargandy S, Samodra YL, Samuel VP, Samy AM, Sanabria J, Sanadgol N, Sanganyado E, Sanjeev RK, Sanmarchi F, Sanna F, Santri IN, Santric-Milicevic MM, Sarasmita MA, Saravanan A, Saravi B, Sarikhani Y, Sarkar C, Sarmiento-Suárez R, Sarode GS, Sarode SC, Sarveazad A, Sathian B, Sathish T, Sattin D, Saulam J, Sawyer SM, Saxena S, Saya GK, Sayadi Y, Sayeed A, Sayeed MA, Saylan M, Scarmeas N, Schaarschmidt BM, Schlee W, Schmidt MI, Schuermans A, Schwebel DC, Schwendicke F, Šekerija M, Selvaraj S, Semreen MH, Senapati S, Sengupta P, Senthilkumaran S, Sepanlou SG, Serban D, Sertsu A, Sethi Y, SeyedAlinaghi S, Seyedi SA, Shafaat A, Shafaat O, Shafie M, Shafiee A, Shah NS, Shah PA, Shahabi S, Shahbandi A, Shahid I, Shahid S, Shahid W, Shahwan MJ, Shaikh MA, Shakeri A, Shakil H, Sham S, Shamim MA, Shams-Beyranvand M, Shamshad H, Shamshirgaran MA, Shamsi MA, Shanawaz M, Shankar A, Sharfaei S, Sharifan A, Shariff M, Sharifi-Rad J, Sharma M, Sharma R, Sharma S, Sharma V, Shastry RP, Shavandi A, Shaw DH, Shayan AM, Shehabeldine AME, Sheikh A, Sheikhi RA, Shen J, Shenoy MM, Shetty BSK, Shetty RS, Shey RA, Shiani A, Shibuya K, Shiferaw D, Shigematsu M, Shin JI, Shin MJ, Shiri R, Shirkoohi R, Shittu A, Shiue I, Shivakumar KM, Shivarov V, Shool S, Shrestha S, Shuja KH, Shuval K, Si Y, Sibhat MM, Siddig EE, Sigfusdottir ID, Silva JP, Silva LMLR, Silva S, Simões JP, Simpson CR, Singal A, Singh A, Singh A, Singh A, Singh BB, Singh B, Singh M, Singh M, Singh NP, Singh P, Singh S, Siraj MS, Sitas F, Sivakumar S, Skryabin VY, Skryabina AA, Sleet DA, Slepak ELN, Sohrabi H, Soleimani H, Soliman SSM, Solmi M, Solomon Y, Song Y, Sorensen RJD, Soriano JB, Soyiri IN, Spartalis M, Sreeramareddy CT, Starnes JR, Starodubov VI, Starodubova AV, Stefan SC, Stein DJ, Steinbeis F, Steiropoulos P, Stockfelt L, Stokes MA, Stortecky S, Stranges S, Stroumpoulis K, Suleman M, Suliankatchi Abdulkader R, Sultana A, Sun J, Sunkersing D, Susanty S, Swain CK, Sykes BL, Szarpak L, Szeto MD, Szócska M, Tabaee Damavandi P, Tabatabaei Malazy O, Tabatabaeizadeh SA, Tabatabai S, Tabb KM, Tabish M, Taborda-Barata LM, Tabuchi T, Tadesse BT, Taheri A, Taheri Abkenar Y, Taheri Soodejani M, Taherkhani A, Taiba J, Tajbakhsh A, Talaat IM, Talukder A, Tamuzi JL, Tan KK, Tang H, Tang HK, Tat NY, Tat VY, Tavakoli Oliaee R, Tavangar SM, Taveira N, Tebeje TM, Tefera YM, Teimoori M, Temsah MH, Temsah RMH, Teramoto M, Tesfaye SH, Thangaraju P, Thankappan KR, Thapa R, Thapar R, Thomas N, Thrift AG, Thum CCC, Tian J, Tichopad A, Ticoalu JHV, Tiruye TY, Tohidast SA, Tonelli M, Touvier M, Tovani-Palone MR, Tram KH, Tran NM, Trico D, Trihandini I, Tromans SJ, Truong VT, Truyen TTTT, Tsermpini EE, Tumurkhuu M, Tung K, Tyrovolas S, Ubah CS, Udoakang AJ, Udoh A, Ulhaq I, Ullah S, Ullah S, Umair M, Umar TP, Umeokonkwo CD, Umesh A, Unim B, Unnikrishnan B, Upadhyay E, Urso D, Vacante M, Vahdani AM, Vaithinathan AG, Valadan Tahbaz S, Valizadeh R, Van den Eynde J, Varavikova E, Varga O, Varma SA, Vart P, Varthya SB, Vasankari TJ, Veerman LJ, Venketasubramanian N, Venugopal D, Verghese NA, Verma M, Verma P, Veroux M, Verras GI, Vervoort D, Vieira RJ, Villafañe JH, Villani L, Villanueva GI, Villeneuve PJ, Violante FS, Visontay R, Vlassov V, Vo B, Vollset SE, Volovat SR, Volovici V, Vongpradith A, Vos T, Vujcic IS, Vukovic R, Wado YD, Wafa HA, Waheed Y, Wamai RG, Wang C, Wang D, Wang F, Wang S, Wang S, Wang Y, Wang YP, Ward P, Watson S, Weaver MR, Weerakoon KG, Weiss DJ, Weldemariam AH, Wells KM, Wen YF, Werdecker A, Westerman R, Wickramasinghe DP, Wickramasinghe ND, Wijeratne T, Wilson S, Wojewodzic MW, Wool EE, Woolf AD, Wu D, Wulandari RD, Xiao H, Xu B, Xu X, Yadav L, Yaghoubi S, Yang L, Yano Y, Yao Y, Ye P, Yesera GE, Yesodharan R, Yesuf SA, Yiğit A, Yiğit V, Yip P, Yon DK, Yonemoto N, You Y, Younis MZ, Yu C, Zadey S, Zadnik V, Zafari N, Zahedi M, Zahid MN, Zahir M, Zakham F, Zaki N, Zakzuk J, Zamagni G, Zaman BA, Zaman SB, Zamora N, Zand R, Zandi M, Zandieh GGZ, Zanghì A, Zare I, Zastrozhin MS, Zeariya MGM, Zeng Y, Zhai C, Zhang C, Zhang H, Zhang H, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao Y, Zhao Y, Zheng P, Zhong C, Zhou J, Zhu B, Zhu Z, Ziaeefar P, Zielińska M, Zou Z, Zumla A, Zweck E, Zyoud SH, Lim SS, Murray CJL. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:1989-2056. [PMID: 38484753 PMCID: PMC11126395 DOI: 10.1016/s0140-6736(24)00476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/08/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period. METHODS 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING Bill & Melinda Gates Foundation.
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Tagami Y, Horita N, Kaneko M, Muraoka S, Fukuda N, Izawa A, Kaneko A, Somekawa K, Kamimaki C, Matsumoto H, Tanaka K, Murohashi K, Aoki A, Fujii H, Watanabe K, Hara Y, Kobayashi N, Kaneko T. Whole-Genome Sequencing Predicting Phenotypic Antitubercular Drug Resistance: Meta-analysis. J Infect Dis 2024; 229:1481-1492. [PMID: 37946558 DOI: 10.1093/infdis/jiad480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 10/06/2023] [Accepted: 10/27/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND For simultaneous prediction of phenotypic drug susceptibility test (pDST) for multiple antituberculosis drugs, the whole genome sequencing (WGS) data can be analyzed using either a catalog-based approach, wherein 1 causative mutation suggests resistance, (eg, World Health Organization catalog) or noncatalog-based approach using complicated algorithm (eg, TB-profiler, machine learning). The aim was to estimate the predictive ability of WGS-based tests with pDST as the reference, and to compare the 2 approaches. METHODS Following a systematic literature search, the diagnostic test accuracies for 14 drugs were pooled using a random-effect bivariate model. RESULTS Of 779 articles, 44 with 16 821 specimens for meta-analysis and 13 not for meta-analysis were included. The areas under summary receiver operating characteristic curve suggested test accuracy was excellent (0.97-1.00) for 2 drugs (isoniazid 0.975, rifampicin 0.975), very good (0.93-0.97) for 8 drugs (pyrazinamide 0.946, streptomycin 0.952, amikacin 0.968, kanamycin 0.963, capreomycin 0.965, para-aminosalicylic acid 0.959, levofloxacin 0.960, ofloxacin 0.958), and good (0.75-0.93) for 4 drugs (ethambutol 0.926, moxifloxacin 0.896, ethionamide 0.878, prothionamide 0.908). The noncatalog-based and catalog-based approaches had similar ability for all drugs. CONCLUSIONS WGS accurately identifies isoniazid and rifampicin resistance. For most drugs, positive WGS results reliably predict pDST positive. The 2 approaches had similar ability. CLINICAL TRIALS REGISTRATION UMIN-ID UMIN000049276.
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Kawaguchi Y, Kato S, Horita N, Utsunomiya D. Value of Dynamic Computed Tomography Myocardial Perfusion in CAD: A Systematic Review and Meta-analysis. Eur Heart J Cardiovasc Imaging 2024:jeae118. [PMID: 38693883 DOI: 10.1093/ehjci/jeae118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 04/24/2024] [Indexed: 05/03/2024] Open
Abstract
AIMS Dynamic stress computed tomography (CT) perfusion is a non-invasive method for quantifying myocardial ischemia by assessing myocardial blood flow (MBF). In this meta-analysis, we evaluated the diagnostic accuracy of dynamic CT perfusion for the detection of significant coronary artery disease (CAD) across various CT scanners, obese patients, and its prognostic value. METHODS AND RESULTS We systematically searched PubMed, Embase, Web of Science, and Cochrane library for published studies evaluating the accuracy of CT myocardial perfusion in diagnosing functional significant ischemia by invasive fractional flow reserve. The diagnostic performance of dynamic CT perfusion in detecting ischemia was evaluated using a summary receiver operating characteristic (sROC) curve. A total of 23 studies underwent meta- analysis. In myocardial region without ischemia, MBF was measured at 1.44 ml/min/g (95% confidence interval [CI]: 1.13-1.75), while in region with ischemia, it was 0.94 ml/min/g (95% CI: 0.80-1.08) (p<0.001). On the patient-based analysis, the area under the sROC curve of CT-MBF was 0.93, with a sensitivity of 0.84 and specificity of 0.88. Differences in CT type (dual source vs. single source), and body mass index (BMI) did not significantly affect the diagnostic performance. The pooled hazard ratio of dynamic CT perfusion for predicting adverse events was 4.98 (95%CI: 2.08-11.93, p=<0.001, I2=61%, p for heterogeneity = 0.07). CONCLUSIONS Dynamic CT perfusion has high diagnostic performance in the quantitative assessment of ischemia and detection of functional myocardial ischemia as defined by invasive FFR, and may be useful in risk stratification of CAD patients.
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Saito N, Kato S, Azuma M, Horita N, Utsunomiya D. Prognostic impact of MRI-derived feature tracking myocardial strain in patients with non-ischaemic dilated cardiomyopathy: a systematic review and meta-analysis. Clin Radiol 2024; 79:e702-e714. [PMID: 38402086 DOI: 10.1016/j.crad.2023.12.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/15/2023] [Accepted: 12/04/2023] [Indexed: 02/26/2024]
Abstract
AIM To evaluate the clinical utility of feature tracking (FT)-derived myocardial strain in patients with non-ischaemic dilated cardiomyopathy (NIDCM). MATERIALS AND METHODS Electronic database searches of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE were performed. Studies on NIDCM were divided into categories according to left ventricular ejection fraction (LVEF; <30%, 30-40%, >40%), and correlations between strains and prevalence of late gadolinium enhancement (LGE) were evaluated by weighted correlation coefficients. Global longitudinal strain (GLS) hazard ratios were also integrated for prediction of future adverse events. RESULTS The present meta-analysis analysed data from 5,767 patients with NIDCM from 30 eligible studies. GLS and global circumferential strain significantly differed across the three LVEF categories (all p<0.05); however, global radial strain did not. Only GLS showed a strong correlation with the prevalence of LGE (Spearman's correlation coefficient = 0.61). The pooled HR of GLS for predicting adverse events was 1.15 (95% confidence interval [CI]: 1.07-1.23, p<0.001). CONCLUSION In this meta-analysis, FT-derived GLS was strongly correlated with myocardial fibrosis and was an important predictor of future adverse events. These results suggest that FT-derived GLS may be useful in the pathological evaluation and risk stratification of NIDCM.
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Kaneko A, Kobayashi N, Miura K, Matsumoto H, Somekawa K, Hirose T, Kajita Y, Tanaka A, Teranishi S, Sairenji Y, Kawashima H, Yumoto K, Tsukahara T, Fukuda N, Nishihira R, Watanabe K, Horita N, Hara Y, Kudo M, Miyazawa N, Kaneko T. Real-world evidence of efficacy of pembrolizumab plus chemotherapy and nivolumab plus ipilimumab plus chemotherapy as initial treatment for advanced non-small cell lung cancer. Thorac Cancer 2024; 15:1208-1217. [PMID: 38602166 PMCID: PMC11128373 DOI: 10.1111/1759-7714.15304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND For advanced non-small cell lung cancer (NSCLC), combination therapies including a PD-1 inhibitor plus chemotherapy or a PD-1 inhibitor, CTLA-4 inhibitor, and chemotherapy are standard first-line options. However, data directly comparing these regimens are lacking. This study compared the efficacy of pembrolizumab plus chemotherapy (CP) against nivolumab plus ipilimumab and chemotherapy (CNI) in a real-world setting. METHODS In this multicenter retrospective study, we compared the efficacy and safety of CP and CNI as first-line therapies in 182 patients with stage IIIB-IV NSCLC. Primary outcomes were overall survival (OS) and progression-free survival (PFS), while secondary outcomes included the response rate (RR) and safety profiles. Kaplan-Meier survival curves and Cox proportional hazards models were utilized for data analysis, adjusting for confounding factors such as age, gender, and PD-L1 expression. RESULTS In this study, 160 patients received CP, while 22 received CNI. The CP group was associated with significantly better PFS than the CNI group (median 11.7 vs. 6.6 months, HR 0.56, p = 0.03). This PFS advantage persisted after propensity score matching to adjust for imbalances. No significant OS differences were observed. Grade 3-4 adverse events occurred comparably, but immune-related adverse events were numerically more frequent in the CNI group. CONCLUSIONS In real-world practice, CP demonstrated superior PFS compared with CNI. These findings can inform treatment selection in advanced NSCLC.
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Kato S, Misumi Y, Horita N, Yamamoto K, Utsunomiya D. Clinical Utility of Computed Tomography-Derived Myocardial Extracellular Volume Fraction: A Systematic Review and Meta-Analysis. JACC Cardiovasc Imaging 2024; 17:516-528. [PMID: 37999657 DOI: 10.1016/j.jcmg.2023.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 09/06/2023] [Accepted: 10/16/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Computed tomography (CT)-derived extracellular volume fraction (ECV) is a noninvasive method to quantify myocardial fibrosis. Although studies suggest CT is a suitable measure of ECV, clinical use remains limited. OBJECTIVES A meta-analysis was performed to determine the clinical value of CT-derived ECV in cardiovascular diseases. METHODS Electronic database searches of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE were performed. The most pivotal analysis entailed the comparison of ECV ascertained through CT-ECV among the control, aortic stenosis, and cardiac amyloidosis cohorts. The diagnostic test accuracy for detecting cardiac amyloidosis was assessed using summary receiver-operating characteristics curve. RESULTS Pooled CT-derived ECV values were 28.5% (95% CI: 27.3%-29.7%) in the control, 31.9% (95% CI: 30.2%-33.8%) in the aortic stenosis, and 48.9% (95% CI: 44.5%-53.3%) in the cardiac amyloidosis group. ECV was significantly elevated in aortic stenosis (P = 0.002) (vs controls) but further elevated in cardiac amyloidosis (P < 0.001) (vs aortic stenosis). CT-derived ECV had a high diagnostic accuracy for cardiac amyloidosis, with sensitivity of 92.8% (95% CI: 86.7%-96.2%), specificity of 84.8% (95% CI: 68.6%-93.4%), and area under the summary receiver-operating characteristic curve of 0.94 (95% CI: 0.88-1.00). CONCLUSIONS This study is the first comprehensive systematic review and meta-analysis of CT-derived ECV evaluation in cardiac disease. The high diagnostic accuracy of CT-ECV suggests the usefulness of CT-ECV in the diagnosis of cardiac amyloidosis in preoperative CT planning for transcatheter aortic valve replacement.
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Yamada K, Takeuchi M, Fukumoto T, Suzuki M, Kato A, Mizuki Y, Yamada N, Kaneko T, Mizuki N, Horita N. Immune checkpoint inhibitors for metastatic uveal melanoma: a meta-analysis. Sci Rep 2024; 14:7887. [PMID: 38570507 PMCID: PMC10991441 DOI: 10.1038/s41598-024-55675-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 02/26/2024] [Indexed: 04/05/2024] Open
Abstract
Several studies have evaluated immune checkpoint inhibitors (ICIs) for metastatic uveal melanoma; however, the efficacy of ICIs in the previous studies varied greatly. In this systematic review, we searched for prospective or retrospective studies on single or dual-ICIs for metastatic uveal melanoma treatment. A random-effect model meta-analysis with generic inverse-variance was conducted, and 36 articles representing 41 cohorts of 1414 patients with metastatic uveal melanoma were included. The pooled outcomes were as follows: objective response rate (ORR) was 5.6% (95% confidence interval [95%CI] 3.7-7.5%; I2, 36%), disease control rate (DCR) was 32.5% (95% CI 27.2-37.7%; I2, 73%), median progression-free survival was 2.8 months (95% CI 2.7-2.9 months; I2, 26%), and median overall survival (OS) was 11.2 months (95% CI 9.6-13.2 months; I2, 74%). Compared to single-agent ICI, dual ICI led to better ORR (single-agent: 3.4% [95% CI 1.8-5.1]; dual-agent: 12.4% [95% CI 8.0-16.9]; P < 0.001), DCR (single-agent: 29.3%, [95% CI 23.4-35.2]; dual-agent: 44.3% [95% CI 31.7-56.8]; P = 0.03), and OS (single-agent: 9.8 months [95% CI 8.0-12.2]; dual-agent: 16.3 months [95% CI 13.5-19.7]; P < 0.001). Our analysis provided treatment outcomes as described above. Dual-ICIs appear better than single-agent ICIs for the treatment of metastatic uveal melanoma.
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Tanigaki T, Kato S, Azuma M, Nitta M, Horita N, Utsunomiya D. Right ventricular myocardial fibrosis evaluated by extracellular volume fraction by magnetic resonance imaging in patients with repaired tetralogy of Fallot: a meta-analysis. Heart Vessels 2024; 39:349-358. [PMID: 38010418 DOI: 10.1007/s00380-023-02332-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 10/18/2023] [Indexed: 11/29/2023]
Abstract
OBJECTIVE The objective of this meta-analysis was to assess the clinical utility of anomalous discoveries on cardiac magnetic resonance, particularly the right ventricular extracellular volume (RV-ECV), among individuals who underwent surgical repair for Tetralogy of Fallot (rTOF). METHODS We conducted a systematic search of electronic databases including PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE. Our analysis involved a comparison of ECV levels between rTOF patients and controls, as well as an evaluation of the predictive value of ECV for future adverse events. RESULTS We identified 16 eligible studies that encompassed 856 rTOF patients and 283 controls. Our meta-analysis showed a significant increase in LV-ECV among rTOF patients compared to control subjects (MD = 2.63, 95%CI: 1.35 to 3.90, p < 0.0001, I2 = 86%, p for heterogeneity < 0.00001). Moreover, RV-ECV was found to be substantially higher in patients compared to LV-ECV. Our meta-analysis also revealed a significant association between RV-ECV and adverse events (HR = 1.15, 95% CI: 1.04 to 1.27, p = 0.005, I2 = 0%, p for heterogeneity = 0.62), while LV-ECV did not show any significant association with adverse events (HR = 1.12, 95% CI: 0.92 to 1.36, p = 0.16, I2 = 0%, p for heterogeneity = 0.46). CONCLUSION The results of this meta-analysis on RV-ECV confirmed the presence of RV fibrosis as one of the prognostic factors in rTOF patients.
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Steinmetz JD, Seeher KM, Schiess N, Nichols E, Cao B, Servili C, Cavallera V, Cousin E, Hagins H, Moberg ME, Mehlman ML, Abate YH, Abbas J, Abbasi MA, Abbasian M, Abbastabar H, Abdelmasseh M, Abdollahi M, Abdollahi M, Abdollahifar MA, Abd-Rabu R, Abdulah DM, Abdullahi A, Abedi A, Abedi V, Abeldańo Zuńiga RA, Abidi H, Abiodun O, Aboagye RG, Abolhassani H, Aboyans V, Abrha WA, Abualhasan A, Abu-Gharbieh E, Aburuz S, Adamu LH, Addo IY, Adebayo OM, Adekanmbi V, Adekiya TA, Adikusuma W, Adnani QES, Adra S, Afework T, Afolabi AA, Afraz A, Afzal S, Aghamiri S, Agodi A, Agyemang-Duah W, Ahinkorah BO, Ahmad A, Ahmad D, Ahmad S, Ahmadzade AM, Ahmed A, Ahmed A, Ahmed H, Ahmed JQ, Ahmed LA, Ahmed MB, Ahmed SA, Ajami M, Aji B, Ajumobi O, Akade SE, Akbari M, Akbarialiabad H, Akhlaghi S, Akinosoglou K, Akinyemi RO, Akonde M, Al Hasan SM, Alahdab F, AL-Ahdal TMA, Al-amer RM, Albashtawy M, AlBataineh MT, Aldawsari KA, Alemi H, Alemi S, Algammal AM, Al-Gheethi AAS, Alhalaiqa FAN, Alhassan RK, Ali A, Ali EA, Ali L, Ali MU, Ali MM, Ali R, Ali S, Ali SSS, Ali Z, Alif SM, Alimohamadi Y, Aliyi AA, Aljofan M, Aljunid SM, Alladi S, Almazan JU, Almustanyir S, Al-Omari B, Alqahtani JS, Alqasmi I, Alqutaibi AY, Al-Shahi Salman R, Altaany Z, Al-Tawfiq JA, Altirkawi KA, Alvis-Guzman N, Al-Worafi YM, Aly H, Aly S, Alzoubi KH, Amani R, Amindarolzarbi A, Amiri S, Amirzade-Iranaq MH, Amu H, Amugsi DA, Amusa GA, Amzat J, Ancuceanu R, Anderlini D, Anderson DB, Andrei CL, Androudi S, Angappan D, Angesom TW, Anil A, Ansari-Moghaddam A, Anwer R, Arafat M, Aravkin AY, Areda D, Ariffin H, Arifin H, Arkew M, Ärnlöv J, Arooj M, Artamonov AA, Artanti KD, Aruleba RT, Asadi-Pooya AA, Asena TF, Asghari-Jafarabadi M, Ashraf M, Ashraf T, Atalell KA, Athari SS, Atinafu BTT, Atorkey P, Atout MMW, Atreya A, Aujayeb A, Avan A, Ayala Quintanilla BP, Ayatollahi H, Ayinde OO, Ayyoubzadeh SM, Azadnajafabad S, Azizi Z, Azizian K, Azzam AY, Babaei M, Badar M, Badiye AD, Baghdadi S, Bagherieh S, Bai R, Baig AA, Balakrishnan S, Balalla S, Baltatu OC, Banach M, Bandyopadhyay S, Banerjee I, Baran MF, Barboza MA, Barchitta M, Bardhan M, Barker-Collo SL, Bärnighausen TW, Barrow A, Bashash D, Bashiri H, Bashiru HA, Basiru A, Basso JD, Basu S, Batiha AMM, Batra K, Baune BT, Bedi N, Begde A, Begum T, Behnam B, Behnoush AH, Beiranvand M, Béjot Y, Bekele A, Belete MA, Belgaumi UI, Bemanalizadeh M, Bender RG, Benfor B, Bennett DA, Bensenor IM, Berice B, Bettencourt PJG, Beyene KA, Bhadra A, Bhagat DS, Bhangdia K, Bhardwaj N, Bhardwaj P, Bhargava A, Bhaskar S, Bhat AN, Bhat V, Bhatti GK, Bhatti JS, Bhatti R, Bijani A, Bikbov B, Bilalaga MM, Biswas A, Bitaraf S, Bitra VR, Bjørge T, Bodolica V, Bodunrin AO, Boloor A, Braithwaite D, Brayne C, Brenner H, Briko A, Bringas Vega ML, Brown J, Budke CM, Buonsenso D, Burkart K, Burns RA, Bustanji Y, Butt MH, Butt NS, Butt ZA, Cabral LS, Caetano dos Santos FL, Calina D, Campos-Nonato IR, Cao C, Carabin H, Cárdenas R, Carreras G, Carvalho AF, Castańeda-Orjuela CA, Casulli A, Catalá-López F, Catapano AL, Caye A, Cegolon L, Cenderadewi M, Cerin E, Chacón-Uscamaita PR, Chan JSK, Chanie GS, Charan J, Chattu VK, Chekol Abebe E, Chen H, Chen J, Chi G, Chichagi F, Chidambaram SB, Chimoriya R, Ching PR, Chitheer A, Chong YY, Chopra H, Choudhari SG, Chowdhury EK, Chowdhury R, Christensen H, Chu DT, Chukwu IS, Chung E, Coberly K, Columbus A, Comachio J, Conde J, Cortesi PA, Costa VM, Couto RAS, Criqui MH, Cruz-Martins N, Dabbagh Ohadi MA, Dadana S, Dadras O, Dai X, Dai Z, D'Amico E, Danawi HA, Dandona L, Dandona R, Darwish AH, Das S, Das S, Dascalu AM, Dash NR, Dashti M, De la Hoz FP, de la Torre-Luque A, De Leo D, Dean FE, Dehghan A, Dehghan A, Dejene H, Demant D, Demetriades AK, Demissie S, Deng X, Desai HD, Devanbu VGC, Dhama K, Dharmaratne SD, Dhimal M, Dias da Silva D, Diaz D, Dibas M, Ding DD, Dinu M, Dirac MA, Diress M, Do TC, Do THP, Doan KDK, Dodangeh M, Doheim MF, Dokova KG, Dongarwar D, Dsouza HL, Dube J, Duraisamy S, Durojaiye OC, Dutta S, Dziedzic AM, Edinur HA, Eissazade N, Ekholuenetale M, Ekundayo TC, El Nahas N, El Sayed I, Elahi Najafi MA, Elbarazi I, Elemam NM, Elgar FJ, Elgendy IY, Elhabashy HR, Elhadi M, Elilo LT, Ellenbogen RG, Elmeligy OAA, Elmonem MA, Elshaer M, Elsohaby I, Emamverdi M, Emeto TI, Endres M, Esezobor CI, Eskandarieh S, Fadaei A, Fagbamigbe AF, Fahim A, Faramarzi A, Fares J, Farjoud Kouhanjani M, Faro A, Farzadfar F, Fatehizadeh A, Fathi M, Fathi S, Fatima SAF, Feizkhah A, Fereshtehnejad SM, Ferrari AJ, Ferreira N, Fetensa G, Firouraghi N, Fischer F, Fonseca AC, Force LM, Fornari A, Foroutan B, Fukumoto T, Gadanya MA, Gaidhane AM, Galali Y, Galehdar N, Gan Q, Gandhi AP, Ganesan B, Gardner WM, Garg N, Gau SY, Gautam RK, Gebre T, Gebrehiwot M, Gebremeskel GG, Gebreslassie HG, Getacher L, Ghaderi Yazdi B, Ghadirian F, Ghaffarpasand F, Ghanbari R, Ghasemi M, Ghazy RM, Ghimire S, Gholami A, Gholamrezanezhad A, Ghotbi E, Ghozy S, Gialluisi A, Gill PS, Glasstetter LM, Gnedovskaya EV, Golchin A, Golechha M, Goleij P, Golinelli D, Gomes-Neto M, Goulart AC, Goyal A, Gray RJ, Grivna M, Guadie HA, Guan B, Guarducci G, Guicciardi S, Gunawardane DA, Guo H, Gupta B, Gupta R, Gupta S, Gupta VB, Gupta VK, Gutiérrez RA, Habibzadeh F, Hachinski V, Haddadi R, Hadei M, Hadi NR, Haep N, Haile TG, Haj-Mirzaian A, Hall BJ, Halwani R, Hameed S, Hamiduzzaman M, Hammoud A, Han H, Hanifi N, Hankey GJ, Hannan MA, Hao J, Harapan H, Hareru HE, Hargono A, Harlianto NI, Haro JM, Hartman NN, Hasaballah AI, Hasan F, Hasani H, Hasanian M, Hassan A, Hassan S, Hassanipour S, Hassankhani H, Hassen MB, Haubold J, Hay SI, Hayat K, Hegazy MI, Heidari G, Heidari M, Heidari-Soureshjani R, Hesami H, Hezam K, Hiraike Y, Hoffman HJ, Holla R, Hopf KP, Horita N, Hossain MM, Hossain MB, Hossain S, Hosseinzadeh H, Hosseinzadeh M, Hostiuc S, Hu C, Huang J, Huda MN, Hussain J, Hussein NR, Huynh HH, Hwang BF, Ibitoye SE, Ilaghi M, Ilesanmi OS, Ilic IM, Ilic MD, Immurana M, Iravanpour F, Islam SMS, Ismail F, Iso H, Isola G, Iwagami M, Iwu CCD, Iyer M, Jaan A, Jacob L, Jadidi-Niaragh F, Jafari M, Jafarinia M, Jafarzadeh A, Jahankhani K, Jahanmehr N, Jahrami H, Jaiswal A, Jakovljevic M, Jamora RDG, Jana S, Javadi N, Javed S, Javeed S, Jayapal SK, Jayaram S, Jiang H, Johnson CO, Johnson WD, Jokar M, Jonas JB, Joseph A, Joseph N, Joshua CE, Jürisson M, Kabir A, Kabir Z, Kabito GG, Kadashetti V, Kafi F, Kalani R, Kalantar F, Kaliyadan F, Kamath A, Kamath S, Kanchan T, Kandel A, Kandel H, Kanmodi KK, Karajizadeh M, Karami J, Karanth SD, Karaye IM, Karch A, Karimi A, Karimi H, Karimi Behnagh A, Kasraei H, Kassebaum NJ, Kauppila JH, Kaur H, Kaur N, Kayode GA, Kazemi F, Keikavoosi-Arani L, Keller C, Keykhaei M, Khadembashiri MA, Khader YS, Khafaie MA, Khajuria H, Khalaji A, Khamesipour F, Khammarnia M, Khan M, Khan MAB, Khan YH, Khan Suheb MZ, Khanmohammadi S, Khanna T, Khatab K, Khatatbeh H, Khatatbeh MM, Khateri S, Khatib MN, Khayat Kashani HR, Khonji MS, khorashadizadeh F, Khormali M, Khubchandani J, Kian S, Kim G, Kim J, Kim MS, Kim YJ, Kimokoti RW, Kisa A, Kisa S, Kivimäki M, Kochhar S, Kolahi AA, Koly KN, Kompani F, Koroshetz WJ, Kosen S, Kourosh Arami M, Koyanagi A, Kravchenko MA, Krishan K, Krishnamoorthy V, Kuate Defo B, Kuddus MA, Kumar A, Kumar GA, Kumar M, Kumar N, Kumsa NB, Kundu S, Kurniasari MD, Kusuma D, Kuttikkattu A, Kyu HH, La Vecchia C, Ladan MA, Lahariya C, Laksono T, Lal DK, Lallukka T, Lám J, Lami FH, Landires I, Langguth B, Lasrado S, Latief K, Latifinaibin K, Lau KMM, Laurens MB, Lawal BK, Le LKD, Le TTT, Ledda C, Lee M, Lee SW, Lee SW, Lee WC, Lee YH, Leonardi M, Lerango TL, Li MC, Li W, Ligade VS, Lim SS, Linehan C, Liu C, Liu J, Liu W, Lo CH, Lo WD, Lobo SW, Logroscino G, Lopes G, Lopukhov PD, Lorenzovici L, Lorkowski S, Loureiro JA, Lubinda J, Lucchetti G, Lutzky Saute R, Ma ZF, Mabrok M, Machoy M, Madadizadeh F, Magdy Abd El Razek M, Maghazachi AA, Maghbouli N, Mahjoub S, Mahmoudi M, Majeed A, Malagón-Rojas JN, Malakan Rad E, Malhotra K, Malik AA, Malik I, Mallhi TH, Malta DC, Manilal A, Mansouri V, Mansournia MA, Marasini BP, Marateb HR, Maroufi SF, Martinez-Raga J, Martini S, Martins-Melo FR, Martorell M, März W, Marzo RR, Massano J, Mathangasinghe Y, Mathews E, Maude RJ, Maugeri A, Maulik PK, Mayeli M, Mazaheri M, McAlinden C, McGrath JJ, Meena JK, Mehndiratta MM, Mendez-Lopez MAM, Mendoza W, Mendoza-Cano O, Menezes RG, Merati M, Meretoja A, Merkin A, Mersha AM, Mestrovic T, Mi T, Miazgowski T, Michalek IM, Mihretie ET, Minh LHN, Mirfakhraie R, Mirica A, Mirrakhimov EM, Mirzaei M, Misganaw A, Misra S, Mithra P, Mizana BA, Mohamadkhani A, Mohamed NS, Mohammadi E, Mohammadi H, Mohammadi S, Mohammadi S, Mohammadshahi M, Mohammed M, Mohammed S, Mohammed S, Mohan S, Mojiri-forushani H, Moka N, Mokdad AH, Molinaro S, Möller H, Monasta L, Moniruzzaman M, Montazeri F, Moradi M, Moradi Y, Moradi-Lakeh M, Moraga P, Morovatdar N, Morrison SD, Mosapour A, Mosser JF, Mossialos E, Motaghinejad M, Mousavi P, Mousavi SE, Mubarik S, Muccioli L, Mughal F, Mukoro GD, Mulita A, Mulita F, Musaigwa F, Mustafa A, Mustafa G, Muthu S, Nagarajan AJ, Naghavi P, Naik GR, Nainu F, Nair TS, Najmuldeen HHR, Nakhostin Ansari N, Nambi G, Namdar Areshtanab H, Nargus S, Nascimento BR, Naser AY, Nashwan AJJ, Nasoori H, Nasreldein A, Natto ZS, Nauman J, Nayak BP, Nazri-Panjaki A, Negaresh M, Negash H, Negoi I, Negoi RI, Negru SM, Nejadghaderi SA, Nematollahi MH, Nesbit OD, Newton CRJ, Nguyen DH, Nguyen HTH, Nguyen HQ, Nguyen NTT, Nguyen PT, Nguyen VT, Niazi RK, Nikolouzakis TK, Niranjan V, Nnyanzi LA, Noman EA, Noroozi N, Norrving B, Noubiap JJ, Nri-Ezedi CA, Ntaios G, Nuńez-Samudio V, Nurrika D, Oancea B, Odetokun IA, O'Donnell MJ, Ogunsakin RE, Oguta JO, Oh IH, Okati-Aliabad H, Okeke SR, Okekunle AP, Okonji OC, Okwute PG, Olagunju AT, Olaiya MT, Olana MD, Olatubi MI, Oliveira GMM, Olufadewa II, Olusanya BO, Omar Bali A, Ong S, Onwujekwe OE, Ordak M, Orji AU, Ortega-Altamirano DV, Osuagwu UL, Otstavnov N, Otstavnov SS, Ouyahia A, Owolabi MO, P A MP, Pacheco-Barrios K, Padubidri JR, Pal PK, Palange PN, Palladino C, Palladino R, Palma-Alvarez RF, Pan F, Panagiotakos D, Panda-Jonas S, Pandey A, Pandey A, Pandian JD, Pangaribuan HU, Pantazopoulos I, Pardhan S, Parija PP, Parikh RR, Park S, Parthasarathi A, Pashaei A, Patel J, Patil S, Patoulias D, Pawar S, Pedersini P, Pensato U, Pereira DM, Pereira J, Pereira MO, Peres MFP, Perico N, Perna S, Petcu IR, Petermann-Rocha FE, Pham HT, Phillips MR, Pinilla-Monsalve GD, Piradov MA, Plotnikov E, Poddighe D, Polat B, Poluru R, Pond CD, Poudel GR, Pouramini A, Pourbagher-Shahri AM, Pourfridoni M, Pourtaheri N, Prakash PY, Prakash S, Prakash V, Prates EJS, Pritchett N, Purnobasuki H, Qasim NH, Qattea I, Qian G, Radhakrishnan V, Raee P, Raeisi Shahraki H, Rafique I, Raggi A, Raghav PR, Rahati MM, Rahim F, Rahimi Z, Rahimifard M, Rahman MO, Rahman MHU, Rahman M, Rahman MA, Rahmani AM, Rahmani S, Rahmani Youshanlouei H, Rahmati M, Raj Moolambally S, Rajabpour-Sanati A, Ramadan H, Ramasamy SK, Ramasubramani P, Ramazanu S, Rancic N, Rao IR, Rao SJ, Rapaka D, Rashedi V, Rashid AM, Rashidi MM, Rashidi Alavijeh M, Rasouli-Saravani A, Rawaf S, Razo C, Redwan EMM, Rekabi Bana A, Remuzzi G, Rezaei N, Rezaei N, Rezaei N, Rezaeian M, Rhee TG, Riad A, Robinson SR, Rodrigues M, Rodriguez JAB, Roever L, Rogowski ELB, Romoli M, Ronfani L, Roy P, Roy Pramanik K, Rubagotti E, Ruiz MA, Russ TC, S Sunnerhagen K, Saad AMA, Saadatian Z, Saber K, SaberiKamarposhti M, Sacco S, Saddik B, Sadeghi E, Sadeghian S, Saeed U, Saeed U, Safdarian M, Safi SZ, Sagar R, Sagoe D, Saheb Sharif-Askari F, Saheb Sharif-Askari N, Sahebkar A, Sahoo SS, Sahraian MA, Sajedi SA, Sakshaug JW, Saleh MA, Salehi Omran H, Salem MR, Salimi S, Samadi Kafil H, Samadzadeh S, Samargandy S, Samodra YL, Samuel VP, Samy AM, Sanadgol N, Sanjeev RK, Sanmarchi F, Santomauro DF, Santri IN, Santric-Milicevic MM, Saravanan A, Sarveazad A, Satpathy M, Saylan M, Sayyah M, Scarmeas N, Schlaich MP, Schuermans A, Schwarzinger M, Schwebel DC, Selvaraj S, Sendekie AK, Sengupta P, Senthilkumaran S, Serban D, Sergindo MT, Sethi Y, SeyedAlinaghi S, Seylani A, Shabani M, Shabany M, Shafie M, Shahabi S, Shahbandi A, Shahid S, Shahraki-Sanavi F, Shahsavari HR, Shahwan MJ, Shaikh MA, Shaji KS, Sham S, Shama ATT, Shamim MA, Shams-Beyranvand M, Shamsi MA, Shanawaz M, Sharath M, Sharfaei S, Sharifan A, Sharma M, Sharma R, Shashamo BB, Shayan M, Sheikhi RA, Shekhar S, Shen J, Shenoy SM, Shetty PH, Shiferaw DS, Shigematsu M, Shiri R, Shittu A, Shivakumar KM, Shokri F, Shool S, Shorofi SA, Shrestha S, Siankam Tankwanchi AB, Siddig EE, Sigfusdottir ID, Silva JP, Silva LMLR, Sinaei E, Singh BB, Singh G, Singh P, Singh S, Sirota SB, Sivakumar S, Sohag AAM, Solanki R, Soleimani H, Solikhah S, Solomon Y, Solomon Y, Song S, Song Y, Sotoudeh H, Spartalis M, Stark BA, Starnes JR, Starodubova AV, Stein DJ, Steiner TJ, Stovner LJ, Suleman M, Suliankatchi Abdulkader R, Sultana A, Sun J, Sunkersing D, Sunny A, Susianti H, Swain CK, Szeto MD, Tabarés-Seisdedos R, Tabatabaei SM, Tabatabai S, Tabish M, Taheri M, Tahvildari A, Tajbakhsh A, Tampa M, Tamuzi JJLL, Tan KK, Tang H, Tareke M, Tarigan IU, Tat NY, Tat VY, Tavakoli Oliaee R, Tavangar SM, Tavasol A, Tefera YM, Tehrani-Banihashemi A, Temesgen WA, Temsah MH, Teramoto M, Tesfaye AH, Tesfaye EG, Tesler R, Thakali O, Thangaraju P, Thapa R, Thapar R, Thomas NK, Thrift AG, Ticoalu JHV, Tillawi T, Toghroli R, Tonelli M, Tovani-Palone MR, Traini E, Tran NM, Tran NH, Tran PV, Tromans SJ, Truelsen TC, Truyen TTTT, Tsatsakis A, Tsegay GM, Tsermpini EE, Tualeka AR, Tufa DG, Ubah CS, Udoakang AJ, Ulhaq I, Umair M, Umakanthan S, Umapathi KK, Unim B, Unnikrishnan B, Vaithinathan AG, Vakilian A, Valadan Tahbaz S, Valizadeh R, Van den Eynde J, Vart P, Varthya SB, Vasankari TJ, Vaziri S, Vellingiri B, Venketasubramanian N, Verras GI, Vervoort D, Villafańe JH, Villani L, Vinueza Veloz AF, Viskadourou M, Vladimirov SK, Vlassov V, Volovat SR, Vu LT, Vujcic IS, Wagaye B, Waheed Y, Wahood W, Walde MT, Wang F, Wang S, Wang Y, Wang YP, Waqas M, Waris A, Weerakoon KG, Weintraub RG, Weldemariam AH, Westerman R, Whisnant JL, Wickramasinghe DP, Wickramasinghe ND, Willekens B, Wilner LB, Winkler AS, Wolfe CDA, Wu AM, Wulf Hanson S, Xu S, Xu X, Yadollahpour A, Yaghoubi S, Yahya G, Yamagishi K, Yang L, Yano Y, Yao Y, Yehualashet SS, Yeshaneh A, Yesiltepe M, Yi S, Yiğit A, Yiğit V, Yon DK, Yonemoto N, You Y, Younis MZ, Yu C, Yusuf H, Zadey S, Zahedi M, Zakham F, Zaki N, Zali A, Zamagni G, Zand R, Zandieh GGZ, Zangiabadian M, Zarghami A, Zastrozhin MS, Zeariya MGM, Zegeye ZB, Zeukeng F, Zhai C, Zhang C, Zhang H, Zhang Y, Zhang ZJ, Zhao H, Zhao Y, Zheng P, Zhou H, Zhu B, Zhumagaliuly A, Zielińska M, Zikarg YT, Zoladl M, Murray CJL, Ong KL, Feigin VL, Vos T, Dua T. Global, regional, and national burden of disorders affecting the nervous system, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol 2024; 23:344-381. [PMID: 38493795 PMCID: PMC10949203 DOI: 10.1016/s1474-4422(24)00038-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. METHODS We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. FINDINGS Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378-521), affecting 3·40 billion (3·20-3·62) individuals (43·1%, 40·5-45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7-26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6-38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5-32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7-2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. INTERPRETATION As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. FUNDING Bill & Melinda Gates Foundation.
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Izawa A, Hara Y, Horita N, Muraoka S, Kaneko M, Kaneko A, Somekawa K, Hirata M, Otsu Y, Matsumoto H, Nagasawa R, Tanaka K, Kubo S, Murohashi K, Aoki A, Fujii H, Watanabe K, Kobayashi N, Miura K, Nakajima H, Kaneko T. Improved diagnostic accuracy with three lung tumor markers compared to six-marker panel. Transl Lung Cancer Res 2024; 13:503-511. [PMID: 38601457 PMCID: PMC11002512 DOI: 10.21037/tlcr-23-855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 02/29/2024] [Indexed: 04/12/2024]
Abstract
Background Combining multiple tumor markers increases sensitivity for lung cancer diagnosis in the cost of false positive. However, some would like to check as many as tumor markers in the fear of missing cancer. We though to propose a panel of fewer tumor markers for lung cancer diagnosis. Methods Patients with suspected lung cancer who simultaneously underwent all six tests [carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA), squamous cell carcinoma-associated antigen (SCC), neuron-specific enolase (NSE), pro-gastrin-releasing peptide (ProGRP), and sialyl Lewis-X antigen (SLX)] were included. Tumor markers with significant impact on the lung cancer in a logistic regression model were included in our panel. Area under the curve (AUC) was compared between our panel and the panel of all six. Results We included 1,733 [median 72 years, 1,128 men, 605 women, 779 (45%) confirmed lung cancer]. Logistic regression analysis suggested CEA, CYFRA, and NSE were independently associated with the lung cancer diagnosis. The panel of these three tumor markers [AUC =0.656, 95% confidence interval (CI): 0.630-0.682, sensitivity 0.650, specificity 0.662] had better (P<0.001) diagnostic performance than six tumor markers (AUC =0.575, 95% CI: 0.548-0.602, sensitivity 0.829, specificity 0.321). Conclusions Compared to applying all six markers (at least one marker above the upper limit of normal), the panel with three markers (at least one marker above the upper limit of normal) led to a better predictive value by lowering the risk of false positives.
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Fujiwara Y, Horita N, Naqash AR. Accurately addressing double-arm-zero-events studies in meta-analyses - Authors' reply. Lancet Oncol 2024; 25:e93. [PMID: 38423061 DOI: 10.1016/s1470-2045(24)00009-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 03/02/2024]
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Fukuda Y, Horita N, Aga M, Kashizaki F, Hara Y, Obase Y, Niimi A, Kaneko T, Mukae H, Sagara H. Efficacy and safety of macrolide therapy for adult asthma: A systematic review and meta-analysis. Respir Investig 2024; 62:206-215. [PMID: 38211545 DOI: 10.1016/j.resinv.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/29/2023] [Accepted: 12/25/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND The evidence for macrolide therapy in adult asthma is not properly established and remains controversial. We conducted a systematic review and meta-analysis to examine the efficacy and safety of macrolide therapy for adult asthma. METHODS We searched randomized controlled trials from MEDLINE via the PubMed, CENTRAL, and Ichushi Web databases. The primary outcome was asthma exacerbation. The secondary outcomes were serious adverse events (including mortality), asthma-related quality of life (symptom scales, Asthma Control Questionnaire, and Asthma Quality of Life Questionnaire), rescue medication (puffs/day), respiratory function (morning peak expiratory flow, evening peak flow, and forced expiratory volume in 1 s), bronchial hyperresponsiveness, and minimum oral corticosteroid dose. Of the 805 studies, we selected seven studies for the meta-analysis, which was conducted using a random-effects model. SYSTEMATIC REVIEW REGISTRATION University Hospital Medical Information Network Clinical Trials Registry (UMIN000050824). RESULTS No significant difference between macrolide and placebo for asthma exacerbations was observed (risk ratio 0.71, 95 % confidence interval [CI] 0.46-1.09; p = 0.12). Macrolide therapy for adult asthma showed a significant improvement in rescue medication with short-acting beta-agonists (mean difference -0.41, 95 % CI -0.78 to -0.04; p = 0.03). Macrolide therapy did not show more serious adverse events (odd ratio 0.61, 95 % CI 0.34-1.10; p = 0.10) than those with placebo. The other secondary outcomes were not significantly different between the macrolide and placebo groups. CONCLUSIONS Macrolide therapy for adult asthma may be more effective than placebo and could be a treatment option.
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