3.Clinicopathological features of olfactory carcinoma.
C C ZHANG ; H LI ; L Q CHENG ; H B WU
Chinese Journal of Pathology 2023;52(11):1138-1143
<b>Objective:b> To investigate the clinicopathological features and differential diagnosis of olfactory carcinoma (OC). <b>Methods:b> Twenty-one cases of sinonasal tumors, including those initially diagnosed as olfactory neuroblastoma (ONB) and those with uncertain diagnosis, were collected from the Department of Pathology, the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from January 2016 to August 2022, among which 3 cases were reclassified as OC. The clinicopathological features were investigated, and the remaining 18 cases were used as control. <b>Results:b> Of the three OC patients, 2 were male and 1 was female, with an average age of 57 years ranging from 35 to 74 years. Microscopically, the tumor cells were arranged in solid, nested or lobulated patterns with occasional palisading around the solid nests. The stroma was highly vascular with focal neurofibrillary areas. There were prominent rosettes or pseudorosettes formation. The tumor cells were mainly ovoid to spindly with scant to moderate amount of cytoplasm, one or several small nucleoli, and fine chromatin content. Brisk mitotic figures were seen. In all 3 cases of OC, there were scanty atypical glands and some were ciliated. Immunohistochemically, at least one epithelial marker and neuroendocrine marker were diffusely expressed in the tumor. Some of the tumor cells were positive for p40 and p63, and the sustentacular cells showed the expression of S-100 protein. All cases tested were negative for NUT, CD99 and desmin, with intact expression of SMARCA4 (BRG1) and SMARCB1 (INI-1). Ki-67 proliferation index varied from 20% to 80%. Follow-up after 16-18 months showed no mortality with tumor recurrence from 1 patient after 16 months. <b>Conclusion:b> OC is a rare sinonasal tumor with neuroepithelial differentiation, its histomorphology is diverse, and the combination of immunohistochemical markers is essential for appropriate diagnosis.
Humans
;
Male
;
Female
;
Middle Aged
;
Paranasal Sinus Neoplasms/chemistry*
;
Biomarkers, Tumor/metabolism*
;
Carcinoma/chemistry*
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Diagnosis, Differential
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S100 Proteins
;
DNA Helicases/metabolism*
;
Nuclear Proteins/metabolism*
;
Transcription Factors/metabolism*
4.Development and validation of a prognostic prediction model for patients with stage Ⅰ to Ⅲ colon cancer incorporating high-risk pathological features.
K X LI ; Q B WU ; F Q ZHAO ; J L ZHANG ; S L LUO ; S D HU ; B WU ; H L LI ; G L LIN ; H Z QIU ; J Y LU ; L XU ; Z WANG ; X H DU ; L KANG ; X WANG ; Z Q WANG ; Q LIU ; Y XIAO
Chinese Journal of Surgery 2023;61(9):753-759
<b>Objective:b> To examine a predictive model that incorporating high risk pathological factors for the prognosis of stage Ⅰ to Ⅲ colon cancer. <b>Methods:b> This study retrospectively collected clinicopathological information and survival outcomes of stage Ⅰ~Ⅲ colon cancer patients who underwent curative surgery in 7 tertiary hospitals in China from January 1, 2016 to December 31, 2017. A total of 1 650 patients were enrolled, aged (M(IQR)) 62 (18) years (range: 14 to 100). There were 963 males and 687 females. The median follow-up period was 51 months. The Cox proportional hazardous regression model was utilized to select high-risk pathological factors, establish the nomogram and scoring system. The Bootstrap resampling method was utilized for internal validation of the model, the concordance index (C-index) was used to assess discrimination and calibration curves were presented to assess model calibration. The Kaplan-Meier method was used to plot survival curves after risk grouping, and Cox regression was used to compare disease-free survival between subgroups. <b>Results:b> Age (HR=1.020, 95%CI: 1.008 to 1.033, P=0.001), T stage (T3:HR=1.995,95%CI:1.062 to 3.750,P=0.032;T4:HR=4.196, 95%CI: 2.188 to 8.045, P<0.01), N stage (N1: HR=1.834, 95%CI: 1.307 to 2.574, P<0.01; N2: HR=3.970, 95%CI: 2.724 to 5.787, P<0.01) and number of lymph nodes examined (≥36: HR=0.438, 95%CI: 0.242 to 0.790, P=0.006) were independently associated with disease-free survival. The C-index of the scoring model (model 1) based on age, T stage, N stage, and dichotomous variables of the lymph nodes examined (<12 and ≥12) was 0.723, and the C-index of the scoring model (model 2) based on age, T stage, N stage, and multi-categorical variables of the lymph nodes examined (<12, 12 to <24, 24 to <36, and ≥36) was 0.726. A scoring system was established based on age, T stage, N stage, and multi-categorical variables of lymph nodes examined, the 3-year DFS of the low-risk (≤1), middle-risk (2 to 4) and high-risk (≥5) group were 96.3% (n=711), 89.0% (n=626) and 71.4% (n=313), respectively. Statistically significant difference was observed among groups (P<0.01). <b>Conclusions:b> The number of lymph nodes examined was an independent prognostic factor for disease-free survival after curative surgery in patients with stage Ⅰ to Ⅲ colon cancer. Incorporating the number of lymph nodes examined as a multi-categorical variable into the T and N staging system could improve prognostic predictive validity.
Male
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Female
;
Humans
;
Prognosis
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Neoplasm Staging
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Retrospective Studies
;
Nomograms
;
Lymph Nodes/pathology*
;
Risk Factors
;
Colonic Neoplasms/surgery*
5.Predictive value of MRI pelvic measurements for "difficult pelvis" during total mesorectal excision.
Z SUN ; W Y HOU ; J J LIU ; H D XUE ; P R XU ; B WU ; G L LIN ; L XU ; J Y LU ; Y XIAO
Chinese Journal of Gastrointestinal Surgery 2022;25(12):1089-1097
Objective:b> Total mesorectal resection (TME) is difficult to perform for rectal cancer patients with anatomical confines of the pelvis or thick mesorectal fat. This study aimed to evaluate the ability of pelvic dimensions to predict the difficulty of TME, and establish a nomogram for predicting its difficulty. Methods:b> The inclusion criteria for this retrospective study were as follows: (1) tumor within 15 cm of the anal verge; (2) rectal cancer confirmed by preoperative pathological examination; (3) adequate preoperative MRI data; (4) depth of tumor invasion T1-4a; and (5) grade of surgical difficulty available. Patients who had undergone non-TME surgery were excluded. A total of 88 patients with rectal cancer who underwent TME between March 2019 and November 2021 were eligible for this study. The system for scaling difficulty was as follows: Grade I, easy procedure, no difficulties; Grade II, difficult procedure, but no impact on specimen quality (complete TME); Grade III, difficult procedure, with a slight impact on specimen quality (near-complete TME); Grade IV: very difficult procedure, with remarkable impact on specimen quality (incomplete TME). We classified Grades I-II as no surgical difficulty and grades III-IV as surgical difficulty. Pelvic parameters included pelvic inlet length, anteroposterior length of the mid-pelvis, pelvic outlet length, pubic tubercle height, sacral length, sacral depth, distance from the pubis to the pelvic floor, anterior pelvic depth, interspinous distance, and inter-tuberosity distance. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with the difficulty of TME, and a nomogram predicting the difficulty of the procedure was established. Results:b> The study cohort comprised 88 patients, 30 (34.1%) of whom were classified as having undergone difficult procedures and 58 (65.9%) non-difficult procedures. The median age was 64 years (56-70), 51 patients were male and 64 received neoadjuvant therapy. The median pelvic inlet length, anteroposterior length of the mid-pelvis, pelvic outlet length, pubic tubercle height, sacral length, sacral depth, distance from the pubis to the pelvic floor, anterior pelvic depth, interspinous distance, and inter-tuberosity distance were 12.0 cm, 11.0 cm, 8.6 cm, 4.9 cm, 12.6 cm, 3.7 cm, 3.0 cm, 13.3 cm, 10.2 cm, and 12.2 cm, respectively. Multivariable analyses showed that preoperative chemoradiotherapy (OR=4.97,95% CI: 1.25-19.71, P=0.023), distance between the tumor and the anal verge (OR=1.31, 95% CI: 1.02-1.67, P=0.035) and pubic tubercle height (OR=3.36, 95% CI: 1.56-7.25, P=0.002) were associated with surgical difficulty. We then built and validated a predictive nomogram based on the above three variables (AUC = 0.795, 95%CI: 0.696-0.895). Conclusion:b> Our research demonstrated that our system for scaling surgical difficulty of TME is useful and practical. Preoperative chemoradiotherapy, distance between tumor and anal verge, and pubic tubercle height are risk factors for surgical difficulty. These data may aid surgeons in planning appropriate surgical procedures.
Humans
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Male
;
Middle Aged
;
Female
;
Retrospective Studies
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Laparoscopy/methods*
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Pelvis/pathology*
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Rectal Neoplasms/pathology*
;
Magnetic Resonance Imaging
;
Treatment Outcome
6.Global Impact of the COVID-19 Pandemic on Cerebral Venous Thrombosis and Mortality
Thanh N. NGUYEN ; Muhammad M. QURESHI ; Piers KLEIN ; Hiroshi YAMAGAMI ; Mohamad ABDALKADER ; Robert MIKULIK ; Anvitha SATHYA ; Ossama Yassin MANSOUR ; Anna CZLONKOWSKA ; Hannah LO ; Thalia S. FIELD ; Andreas CHARIDIMOU ; Soma BANERJEE ; Shadi YAGHI ; James E. SIEGLER ; Petra SEDOVA ; Joseph KWAN ; Diana Aguiar DE SOUSA ; Jelle DEMEESTERE ; Violiza INOA ; Setareh Salehi OMRAN ; Liqun ZHANG ; Patrik MICHEL ; Davide STRAMBO ; João Pedro MARTO ; Raul G. NOGUEIRA ; ; Espen Saxhaug KRISTOFFERSEN ; Georgios TSIVGOULIS ; Virginia Pujol LEREIS ; Alice MA ; Christian ENZINGER ; Thomas GATTRINGER ; Aminur RAHMAN ; Thomas BONNET ; Noémie LIGOT ; Sylvie DE RAEDT ; Robin LEMMENS ; Peter VANACKER ; Fenne VANDERVORST ; Adriana Bastos CONFORTO ; Raquel C.T. HIDALGO ; Daissy Liliana MORA CUERVO ; Luciana DE OLIVEIRA NEVES ; Isabelle LAMEIRINHAS DA SILVA ; Rodrigo Targa MARTÍNS ; Letícia C. REBELLO ; Igor Bessa SANTIAGO ; Teodora SADELAROVA ; Rosen KALPACHKI ; Filip ALEXIEV ; Elena Adela CORA ; Michael E. KELLY ; Lissa PEELING ; Aleksandra PIKULA ; Hui-Sheng CHEN ; Yimin CHEN ; Shuiquan YANG ; Marina ROJE BEDEKOVIC ; Martin ČABAL ; Dusan TENORA ; Petr FIBRICH ; Pavel DUŠEK ; Helena HLAVÁČOVÁ ; Emanuela HRABANOVSKA ; Lubomír JURÁK ; Jana KADLČÍKOVÁ ; Igor KARPOWICZ ; Lukáš KLEČKA ; Martin KOVÁŘ ; Jiří NEUMANN ; Hana PALOUŠKOVÁ ; Martin REISER ; Vladimir ROHAN ; Libor ŠIMŮNEK ; Ondreij SKODA ; Miroslav ŠKORŇA ; Martin ŠRÁMEK ; Nicolas DRENCK ; Khalid SOBH ; Emilie LESAINE ; Candice SABBEN ; Peggy REINER ; Francois ROUANET ; Daniel STRBIAN ; Stefan BOSKAMP ; Joshua MBROH ; Simon NAGEL ; Michael ROSENKRANZ ; Sven POLI ; Götz THOMALLA ; Theodoros KARAPANAYIOTIDES ; Ioanna KOUTROULOU ; Odysseas KARGIOTIS ; Lina PALAIODIMOU ; José Dominguo BARRIENTOS GUERRA ; Vikram HUDED ; Shashank NAGENDRA ; Chintan PRAJAPATI ; P.N. SYLAJA ; Achmad Firdaus SANI ; Abdoreza GHOREISHI ; Mehdi FARHOUDI ; Elyar SADEGHI HOKMABADI ; Mazyar HASHEMILAR ; Sergiu Ionut SABETAY ; Fadi RAHAL ; Maurizio ACAMPA ; Alessandro ADAMI ; Marco LONGONI ; Raffaele ORNELLO ; Leonardo RENIERI ; Michele ROMOLI ; Simona SACCO ; Andrea SALMAGGI ; Davide SANGALLI ; Andrea ZINI ; Kenichiro SAKAI ; Hiroki FUKUDA ; Kyohei FUJITA ; Hirotoshi IMAMURA ; Miyake KOSUKE ; Manabu SAKAGUCHI ; Kazutaka SONODA ; Yuji MATSUMARU ; Nobuyuki OHARA ; Seigo SHINDO ; Yohei TAKENOBU ; Takeshi YOSHIMOTO ; Kazunori TOYODA ; Takeshi UWATOKO ; Nobuyuki SAKAI ; Nobuaki YAMAMOTO ; Ryoo YAMAMOTO ; Yukako YAZAWA ; Yuri SUGIURA ; Jang-Hyun BAEK ; Si Baek LEE ; Kwon-Duk SEO ; Sung-Il SOHN ; Jin Soo LEE ; Anita Ante ARSOVSKA ; Chan Yong CHIEH ; Wan Asyraf WAN ZAIDI ; Wan Nur Nafisah WAN YAHYA ; Fernando GONGORA-RIVERA ; Manuel MARTINEZ-MARINO ; Adrian INFANTE-VALENZUELA ; Diederik DIPPEL ; Dianne H.K. VAN DAM-NOLEN ; Teddy Y. WU ; Martin PUNTER ; Tajudeen Temitayo ADEBAYO ; Abiodun H. BELLO ; Taofiki Ajao SUNMONU ; Kolawole Wasiu WAHAB ; Antje SUNDSETH ; Amal M. AL HASHMI ; Saima AHMAD ; Umair RASHID ; Liliana RODRIGUEZ-KADOTA ; Miguel Ángel VENCES ; Patrick Matic YALUNG ; Jon Stewart Hao DY ; Waldemar BROLA ; Aleksander DĘBIEC ; Malgorzata DOROBEK ; Michal Adam KARLINSKI ; Beata M. LABUZ-ROSZAK ; Anetta LASEK-BAL ; Halina SIENKIEWICZ-JAROSZ ; Jacek STASZEWSKI ; Piotr SOBOLEWSKI ; Marcin WIĄCEK ; Justyna ZIELINSKA-TUREK ; André Pinho ARAÚJO ; Mariana ROCHA ; Pedro CASTRO ; Patricia FERREIRA ; Ana Paiva NUNES ; Luísa FONSECA ; Teresa PINHO E MELO ; Miguel RODRIGUES ; M Luis SILVA ; Bogdan CIOPLEIAS ; Adela DIMITRIADE ; Cristian FALUP-PECURARIU ; May Adel HAMID ; Narayanaswamy VENKETASUBRAMANIAN ; Georgi KRASTEV ; Jozef HARING ; Oscar AYO-MARTIN ; Francisco HERNANDEZ-FERNANDEZ ; Jordi BLASCO ; Alejandro RODRÍGUEZ-VÁZQUEZ ; Antonio CRUZ-CULEBRAS ; Francisco MONICHE ; Joan MONTANER ; Soledad PEREZ-SANCHEZ ; María Jesús GARCÍA SÁNCHEZ ; Marta GUILLÁN RODRÍGUEZ ; Gianmarco BERNAVA ; Manuel BOLOGNESE ; Emmanuel CARRERA ; Anchalee CHUROJANA ; Ozlem AYKAC ; Atilla Özcan ÖZDEMIR ; Arsida BAJRAMI ; Songul SENADIM ; Syed I. HUSSAIN ; Seby JOHN ; Kailash KRISHNAN ; Robert LENTHALL ; Kaiz S. ASIF ; Kristine BELOW ; Jose BILLER ; Michael CHEN ; Alex CHEBL ; Marco COLASURDO ; Alexandra CZAP ; Adam H. DE HAVENON ; Sushrut DHARMADHIKARI ; Clifford J. ESKEY ; Mudassir FAROOQUI ; Steven K. FESKE ; Nitin GOYAL ; Kasey B. GRIMMETT ; Amy K. GUZIK ; Diogo C. HAUSSEN ; Majesta HOVINGH ; Dinesh JILLELA ; Peter T. KAN ; Rakesh KHATRI ; Naim N. KHOURY ; Nicole L. KILEY ; Murali K. KOLIKONDA ; Stephanie LARA ; Grace LI ; Italo LINFANTE ; Aaron I. LOOCHTAN ; Carlos D. LOPEZ ; Sarah LYCAN ; Shailesh S. MALE ; Fadi NAHAB ; Laith MAALI ; Hesham E. MASOUD ; Jiangyong MIN ; Santiago ORGETA-GUTIERREZ ; Ghada A. MOHAMED ; Mahmoud MOHAMMADEN ; Krishna NALLEBALLE ; Yazan RADAIDEH ; Pankajavalli RAMAKRISHNAN ; Bliss RAYO-TARANTO ; Diana M. ROJAS-SOTO ; Sean RULAND ; Alexis N. SIMPKINS ; Sunil A. SHETH ; Amy K. STAROSCIAK ; Nicholas E. TARLOV ; Robert A. TAYLOR ; Barbara VOETSCH ; Linda ZHANG ; Hai Quang DUONG ; Viet-Phuong DAO ; Huynh Vu LE ; Thong Nhu PHAM ; Mai Duy TON ; Anh Duc TRAN ; Osama O. ZAIDAT ; Paolo MACHI ; Elisabeth DIRREN ; Claudio RODRÍGUEZ FERNÁNDEZ ; Jorge ESCARTÍN LÓPEZ ; Jose Carlos FERNÁNDEZ FERRO ; Niloofar MOHAMMADZADEH ; Neil C. SURYADEVARA, MD ; Beatriz DE LA CRUZ FERNÁNDEZ ; Filipe BESSA ; Nina JANCAR ; Megan BRADY ; Dawn SCOZZARI
Journal of Stroke 2022;24(2):256-265
Background:
and Purpose Recent studies suggested an increased incidence of cerebral venous thrombosis (CVT) during the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the volume of CVT hospitalization and in-hospital mortality during the 1st year of the COVID-19 pandemic compared to the preceding year.
Methods:
We conducted a cross-sectional retrospective study of 171 stroke centers from 49 countries. We recorded COVID-19 admission volumes, CVT hospitalization, and CVT in-hospital mortality from January 1, 2019, to May 31, 2021. CVT diagnoses were identified by International Classification of Disease-10 (ICD-10) codes or stroke databases. We additionally sought to compare the same metrics in the first 5 months of 2021 compared to the corresponding months in 2019 and 2020 (ClinicalTrials.gov Identifier: NCT04934020).
Results:
There were 2,313 CVT admissions across the 1-year pre-pandemic (2019) and pandemic year (2020); no differences in CVT volume or CVT mortality were observed. During the first 5 months of 2021, there was an increase in CVT volumes compared to 2019 (27.5%; 95% confidence interval [CI], 24.2 to 32.0; P<0.0001) and 2020 (41.4%; 95% CI, 37.0 to 46.0; P<0.0001). A COVID-19 diagnosis was present in 7.6% (132/1,738) of CVT hospitalizations. CVT was present in 0.04% (103/292,080) of COVID-19 hospitalizations. During the first pandemic year, CVT mortality was higher in patients who were COVID positive compared to COVID negative patients (8/53 [15.0%] vs. 41/910 [4.5%], P=0.004). There was an increase in CVT mortality during the first 5 months of pandemic years 2020 and 2021 compared to the first 5 months of the pre-pandemic year 2019 (2019 vs. 2020: 2.26% vs. 4.74%, P=0.05; 2019 vs. 2021: 2.26% vs. 4.99%, P=0.03). In the first 5 months of 2021, there were 26 cases of vaccine-induced immune thrombotic thrombocytopenia (VITT), resulting in six deaths.
Conclusions
During the 1st year of the COVID-19 pandemic, CVT hospitalization volume and CVT in-hospital mortality did not change compared to the prior year. COVID-19 diagnosis was associated with higher CVT in-hospital mortality. During the first 5 months of 2021, there was an increase in CVT hospitalization volume and increase in CVT-related mortality, partially attributable to VITT.
8.DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery
Zhu TIANSHENG ; Zhu YI ; Xuan YUE ; Gao HUANHUAN ; Cai XUE ; Piersma R. SANDER ; Pham V. THANG ; Schelfhorst TIM ; Haas R.G.D. RICHARD ; Bijnsdorp V. IRENE ; Sun RUI ; Yue LIANG ; Ruan GUAN ; Zhang QIUSHI ; Hu MO ; Zhou YUE ; Winan J. Van Houdt ; Tessa Y.S. Le Large ; Cloos JACQUELINE ; Wojtuszkiewicz ANNA ; Koppers-Lalic DANIJELA ; B(o)ttger FRANZISKA ; Scheepbouwer CHANTAL ; Brakenhoff H. RUUD ; Geert J.L.H. van Leenders ; Ijzermans N.M. JAN ; Martens W.M. JOHN ; Steenbergen D.M. RENSKE ; Grieken C. NICOLE ; Selvarajan SATHIYAMOORTHY ; Mantoo SANGEETA ; Lee S. SZE ; Yeow J.Y. SERENE ; Alkaff M.F. SYED ; Xiang NAN ; Sun YAOTING ; Yi XIAO ; Dai SHAOZHENG ; Liu WEI ; Lu TIAN ; Wu ZHICHENG ; Liang XIAO ; Wang MAN ; Shao YINGKUAN ; Zheng XI ; Xu KAILUN ; Yang QIN ; Meng YIFAN ; Lu CONG ; Zhu JIANG ; Zheng JIN'E ; Wang BO ; Lou SAI ; Dai YIBEI ; Xu CHAO ; Yu CHENHUAN ; Ying HUAZHONG ; Lim K. TONY ; Wu JIANMIN ; Gao XIAOFEI ; Luan ZHONGZHI ; Teng XIAODONG ; Wu PENG ; Huang SHI'ANG ; Tao ZHIHUA ; Iyer G. NARAYANAN ; Zhou SHUIGENG ; Shao WENGUANG ; Lam HENRY ; Ma DING ; Ji JIAFU ; Kon L. OI ; Zheng SHU ; Aebersold RUEDI ; Jimenez R. CONNIE ; Guo TIANNAN
Genomics, Proteomics & Bioinformatics 2020;18(2):104-119
To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.
9.Cost-effectiveness of lung cancer screening worldwide: a systematic review.
C C LIU ; J F SHI ; G X LIU ; W TANG ; X ZHANG ; F LI ; L WANG ; Y MA ; K SU ; S J ZHAO ; Y B GAO ; N LI ; W Q CHEN ; N WU ; M DAI
Chinese Journal of Epidemiology 2019;40(2):218-226
<b>Objective:b> From the economic point of view, this study was to systematically assess the status quo on lung cancer screening in the world and to provide reference for further research and implementation of the programs, in China. <b>Methods:b> PubMed, EMbase, The Cochrane Library,CNKI and Wanfang Data were searched to gather papers on studies related to economic evaluation regarding lung cancer screening worldwide, from the inception of studies to June 30(th), 2018. Basic characteristics, methods and main results were extracted. Quality of studies was assessed. Cost were converted to Chinese Yuan under the exchange rates from the World Bank. The ratio of incremental cost-effectiveness ratio (ICER) to local GDP per capita were calculated. <b>Results:b> A total of 23 studies (only 1 randomized controlled trial) were included and the overall quality was accepted. 22 studies were from the developed countries. Nearly half of the studies (11 studies) took 55 years old as the starting age of the screening program. Smoking history was widely applied for the selection of criteria on target populations (18). Low-dose computed tomography (LDCT) was involved in every study used to evaluate the economic effectiveness. Annual (17) and once-life time (7) screening were more common frequencies. 22 studies reported ICERs for LDCT screening, compared to no screening, of which 17 were less than 3 times local GDP per capita, and were considered as cost-effectiveness, according to the WHO's recommendation. 15 and 7 studies reported ICERs for annual and once-life time screening, of which 12 and 7 studies were in favor the results of their cost-effectiveness, respectively. Additionally, the cost-effectiveness of once-lifetime screening was likely to be superior to the annual screening. Differences of cost-effectiveness among the subgroups, by starting age or by the smoking history, might exist. <b>Conclusions:b> Based on the studies, evidence from the developed countries demonstrated that LDCT screening programs on lung cancer, implemented among populations selected by age and smoking history, generally appeared more cost-effective. Combined with the local situation of health resource, the findings could provide direction for less developed regions/countries lacking of local evidence. Low frequency of LDCT screening for lung cancer could be adopted when budget was limited. Data on starting ages, smoking history and other important components related to the strategy of screening programs, needs to be precisely evaluated under the situation of local population.
China
;
Cost-Benefit Analysis
;
Early Detection of Cancer/methods*
;
Humans
;
Lung Neoplasms/prevention & control*
;
Middle Aged
;
Quality-Adjusted Life Years
;
Randomized Controlled Trials as Topic
10.Dynamic path analysis on life course epidemiology.
Z W TIAN ; G Y ZENG ; S L WU ; L T HUANG ; B Z WANG ; H Z TAN
Chinese Journal of Epidemiology 2018;39(1):86-89
In the studies of modern epidemiology, exposure in a short term cannot fully elaborate the mechanism of the development of diseases or health-related events. Thus, lights have been shed on to life course epidemiology, which studies the exposures in early life time and their effects related to the development of chronic diseases. When exploring the mechanism leading from one exposure to an outcome and its effects through other factors, due to the existence of time-variant effects, conventional statistic methods could not meet the needs of etiological analysis in life course epidemiology. This paper summarizes the dynamic path analysis model, including the model structure and significance, and its application in life course epidemiology. Meanwhile, the procedure of data processing and etiology analyzing were introduced. In conclusion, dynamic path analysis is a useful tool which can be used to better elucidate the mechanisms that underlie the etiology of chronic diseases.
Chronic Disease/epidemiology*
;
Epidemiologic Studies
;
Humans
;
Models, Theoretical
;
Risk Factors
;
Time

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