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43 results on '"Liao, Weiqi"'

3. The use of sequence analysis to study primary care pathways : an exploratory study of people at high risk of lung cancer in England

Author

Liao, Weiqi and Brindle, Lucy

Abstract

Research background, gaps, and aim: Lung cancer (LC) is a research priority in the UK, due to its high incidence and mortality, and poor survival. Current population-based studies are focused on investigating 'route to diagnosis', factors associated with late diagnosis and poor survival, and the implications of different intervals (e.g. primary care interval, diagnostic interval, treatment interval) in the cancer care pathway. However, the longitudinal sequence of interdependent patient-GP events over time (patient's help-seeking behaviours and general practitioner (GP) management) preceding cancer diagnosis is a research area less investigated. Therefore, this PhD study proposes a new perspective of studying primary care sequences for early diagnosis research, using a novel statistical method - sequence analysis (SA), to identify meaningful typologies in a less investigated population - patients at high risk but not yet diagnosed with LC. Methodology: A systematic scoping review was conducted to understand how SA has been applied to study disease trajectories and care pathways in health services research, to learn the lessons from published studies and inform the application of SA in the main study. Study design, setting, and participants: 899 community patients at high risk of developing LC (based on patient's smoking history) but not yet diagnosed with LC from eight general practices in the South coast of England consented to participate in this study. Their primary care records from June 2010 to October 2012 (29 months) were reviewed. Information was extracted from GP notes in free text and transcribed manually. Research process: Two study phases, methodological exploration and empirical analysis, were involved to address three research objectives: how to construct primary care sequences from discrete health events, how to use different features of SA to obtain meaningful cluster patterns (the outcome of SA), and how patients' sociodemographic and clinical characteristics can help explain the variation in the cluster patterns and help-seeking behaviours. The primary outcome, covariates, and statistical methods: SA and cluster analysis were used to obtain the primary outcome - typology of clusters. Descriptive statistics were used to characterise patient profiles for each cluster, followed by traditional statistical tests (ANOVA, chi-square test, Kruskal-Wallis test) to compare patients' sociodemographic and clinical features among clusters. Generalised linear models were used to explore the association between patient characteristics and clusters, and to quantify the relative risk ratios. Key findings: The study sample was classified into seven clusters. The subgroups of patients who presented with potential LC symptoms were categorised into four clusters with different GP management: GP ordered tests or prescribed medications for transient symptoms (Cluster 1, n=133/899, 14.8%); GP ordered chest X-ray or referred patients to specialists (Cluster 2, n=65, 7.2%); GP offered health advice to patients (Cluster 3, n=60, 6.7%); and patients presented symptoms multiple times and received repeated prescriptions from GP (Cluster 4, n=37, 4.1%). Cluster 5 was patients without potential LC symptoms but presented in general practice with cardiorespiratory comorbidities and/or other alarm symptoms (n=326, 36.3%). Patients in Cluster 6 only had minor care needs (n=237, 26.4%). Patients in Cluster 7 did not visit GP at all during the whole study period (n=41, 4.6%). For patients who had ≥2 visits with potential LC symptoms, the median interval was 61.5 days, interquartile range [16, 217] days. Age and the number of comorbidities were the two significant variables in different models. Variation of patient management among practices (practice effect) was observed. Conclusions, clinical relevance, and implications: This PhD thesis has made an original contribution by establishing the feasibility and analytical framework of using SA to study complex primary care sequences in the field of early diagnosis research. This study demonstrates the potential of applying SA in a larger scale study with a more representative population, to investigate the complex and heterogeneous primary care sequences leading to LC diagnosis, which has clinical implications for patient care and management, promote early cancer diagnosis from primary care, and eventually improve LC survival in the UK.

Published
2022

4. Predicting the future risk of lung cancer: development, and internal and external validation of the CanPredict (lung) model in 19·67 million people and evaluation of model performance against seven other risk prediction models

Author

Gleeson, Fergus, Baldwin, David, Batchkala, George, Buchanan, James, Burchardt, Judith, Chakraborty, Rohan, Chana, Ravi, Chen, Yan, Coupland, Carol, Crichton, Charles, Davies, Jim, Devaraj, Anand, Fan, Mengran, Hippisley-Cox, Julia, Koleva-Kolarova, Rositsa, Lee, Richard, Liao, Weiqi, Nair, Arjun, Pickup, Lyndsey, Powell, Anne, Rittscher, Jens, Shadmaan, Amied, Shanmugam, Kandavel, Stokes, Elizabeth, Verrill, Clare, Watkins, Johnathan, Wordsworth, Sarah, Coupland, Carol A C, Baldwin, David R, and Gleeson, Fergus V

Published
2023
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5. Disparities in care and outcomes for primary liver cancer in England during 2008–2018: a cohort study of 8.52 million primary care population using the QResearch database

Author

Barnes, Eleanor, Culver, Emma, Fischer, Roman, Hippisley-Cox, Julia, Innes, Hamish, Irving, William L., Jepsen, Peter, Kelly, Matt, Klenerman, Paul, Liao, Weiqi, Mann, Derek, Marshall, Aileen, Matthews, Philippa C., Pavlides, Michael, Peters, Rory J.R., Pickles, Elisabeth, Robineau, James, Schuster-Böckler, Benjamin, Song, Chunxiao, Tomlinson, Jeremy, Welberry, Christopher, Coupland, Carol A.C., and Campbell, Cori

Published
2023
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7. A new species of Bolbelasmus (Coleoptera, Bolboceratidae) from Guangdong Province, China.

Author

Liao, Weiqi and Wu, Zhengwei

Subjects
BEETLES, GEOGRAPHICAL distribution of insects, INFORMATION retrieval
Abstract

Background: Bolbelasmus is a group of small to medium-sized beetles distributed in the Holarctic and Oriental Regions and in Central America. It includes two subgenera (Bolbelasmus and Kolbeus) and 32 species known in the world fauna with seven species recorded from China. New information: The new species, Bolbelasmus guangdongensis sp. nov., is described from south China and compared with B. coreanus, B. meridionalis and B. chifengi. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Predicting the future risk of lung cancer: development, and internal and external validation of the CanPredict (lung) model in 19·67 million people and evaluation of model performance against seven other risk prediction models

Author

Liao, Weiqi, primary, Coupland, Carol A C, additional, Burchardt, Judith, additional, Baldwin, David R, additional, Gleeson, Fergus V, additional, Hippisley-Cox, Julia, additional, Gleeson, Fergus, additional, Baldwin, David, additional, Batchkala, George, additional, Buchanan, James, additional, Chakraborty, Rohan, additional, Chana, Ravi, additional, Chen, Yan, additional, Coupland, Carol, additional, Crichton, Charles, additional, Davies, Jim, additional, Devaraj, Anand, additional, Fan, Mengran, additional, Koleva-Kolarova, Rositsa, additional, Lee, Richard, additional, Liao, Weiqi, additional, Nair, Arjun, additional, Pickup, Lyndsey, additional, Powell, Anne, additional, Rittscher, Jens, additional, Shadmaan, Amied, additional, Shanmugam, Kandavel, additional, Stokes, Elizabeth, additional, Verrill, Clare, additional, Watkins, Johnathan, additional, and Wordsworth, Sarah, additional

Published
2023
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11. Disparities in care and outcomes for primary liver cancer in England during 2008–2018: a cohort study of 8.52 million primary care population using the QResearch database

Author

Liao, Weiqi, primary, Coupland, Carol A.C., additional, Innes, Hamish, additional, Jepsen, Peter, additional, Matthews, Philippa C., additional, Campbell, Cori, additional, Barnes, Eleanor, additional, Hippisley-Cox, Julia, additional, Culver, Emma, additional, Fischer, Roman, additional, Irving, William L., additional, Kelly, Matt, additional, Klenerman, Paul, additional, Liao, Weiqi, additional, Mann, Derek, additional, Marshall, Aileen, additional, Pavlides, Michael, additional, Peters, Rory J.R., additional, Pickles, Elisabeth, additional, Robineau, James, additional, Schuster-Böckler, Benjamin, additional, Song, Chunxiao, additional, Tomlinson, Jeremy, additional, and Welberry, Christopher, additional

Published
2023
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20. The use of sequence analysis to study primary care pathways: an exploratory study of people at high risk of lung cancer in England

Author

Liao, Weiqi. and Liao, Weiqi.

Abstract

Research background, gaps, and aim: Lung cancer (LC) is a research priority in the UK, due to its high incidence and mortality, and poor survival. Current population-based studies are focused on investigating ‘route to diagnosis’, factors associated with late diagnosis and poor survival, and the implications of different intervals (e.g. primary care interval, diagnostic interval, treatment interval) in the cancer care pathway. However, the longitudinal sequence of interdependent patient-GP events over time (patient’s help-seeking behaviours and general practitioner (GP) management) preceding cancer diagnosis is a research area less investigated. Therefore, this PhD study proposes a new perspective of studying primary care sequences for early diagnosis research, using a novel statistical method – sequence analysis (SA), to identify meaningful typologies in a less investigated population – patients at high risk but not yet diagnosed with LC. Methodology: A systematic scoping review was conducted to understand how SA has been applied to study disease trajectories and care pathways in health services research, to learn the lessons from published studies and inform the application of SA in the main study. - Study design, setting, and participants: 899 community patients at high risk of developing LC (based on patient's smoking history) but not yet diagnosed with LC from eight general practices in the South coast of England consented to participate in this study. Their primary care records from June 2010 to October 2012 (29 months) were reviewed. Information was extracted from GP notes in free text and transcribed manually. - Research process: Two study phases, methodological exploration and empirical analysis, were involved to address three research objectives: how to construct primary care sequences from discrete health events, how to use different features of SA to obtain meaningful cluster patterns (the outcome of SA), and how patients’ sociodemographic and

Published
2022

25. Additional file 1 of Development and validation of personalised risk prediction models for early detection and diagnosis of primary liver cancer among the English primary care population using the QResearch® database: research protocol and statistical analysis plan

Author

Liao, Weiqi, Jepsen, Peter, Coupland, Carol, Innes, Hamish, Matthews, Philippa C., Campbell, Cori, Barnes, Eleanor, and Hippisley-Cox, Julia

Abstract

Additional file 1. Co-investigators and members in the DeLIVER consortium.

Published
2022
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29. Predicting risk of pancreatic cancer in individuals with new-onset type-2 diabetes in primary care: protocol for the development and validation of a clinical prediction model (QPancreasD)

Author

Tan, Pui San, primary, Clift, Ashley Kieran, additional, Liao, Weiqi, additional, Patone, Martina, additional, Coupland, Carol, additional, Bashford-Rogers, Rachael, additional, Sivakumar, Shivan, additional, Clifton, David, additional, Pereira, Stephen P, additional, and Hippisley-Cox, Julia, additional

Published
2021
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30. Identification of symptoms associated with the diagnosis of pancreatic exocrine and neuroendocrine neoplasms: a nested case-control study of the UK population

Author

Liao, Weiqi, Clift, Ashley Kieran, Patone, Martina, Coupland, Carol, Pereira, Stephen, and Julia, Hippisley-Cox

Subjects
Family Practice
Abstract

Background: Pancreatic cancer has the worst survival rate among all cancers. Almost 70% of patients were diagnosed at Stage IV. Aim: This study aimed to investigate the symptoms associated with the diagnoses of pancreatic ductal adenocarcinoma (PDAC) and neuroendocrine neoplasms (PNEN), comparatively characterise the symptomatology between the two tumour types to inform earlier diagnosis. Design and Setting: A nested case-control study was conducted using data from the QResearch database. Patients aged ≥25 years and diagnosed with PDAC or PNEN during 2000-2019 were the cases. Up to 10 controls from the same general practice were matched with each case by age, sex, and calendar year using incidence density sampling. Methods: Conditional logistic regression was used to investigate the association between the forty-two shortlisted symptoms and the diagnoses of PDAC/PNEN in different timeframes relative to the index date, adjusting for patients’ sociodemographic characteristics, lifestyle, and relevant comorbidities. Results: There were 23,640 patients diagnosed with PDAC and 596 with PNEN. Twenty-three symptoms were significantly associated with PDAC, and nine symptoms with PNEN. Jaundice and gastrointestinal bleeding were the two alarm symptoms for both tumours. Thirst and dark urine were the two new identified symptoms for PDAC. The risk of unintentional weight loss may be longer than two years before the diagnosis of PNEN. Conclusion: PDAC and PNEN have overlapping symptom profiles. The QCancer (Pancreas) risk prediction model could be updated by including the newly identified symptoms and comorbidities, which could help GP identify high-risk patients for timely investigation in primary care.

Published
2021

32. Temporality of body mass index, blood tests, comorbidities and medication use as early markers for pancreatic ductal adenocarcinoma (PDAC): a nested case–control study

Author

Tan, Pui San, Garriga, Cesar, Clift, Ashley, Liao, Weiqi, Patone, Martina, Coupland, Carol, Bashford-Rogers, Rachael, Sivakumar, Shivan, and Hippisley-Cox, Julia

Abstract

ObjectivePrior studies identified clinical factors associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). However, little is known regarding their time-varying nature, which could inform earlier diagnosis. This study assessed temporality of body mass index (BMI), blood-based markers, comorbidities and medication use with PDAC risk .DesignWe performed a population-based nested case–control study of 28 137 PDAC cases and 261 219 matched-controls in England. We described the associations of biomarkers with risk of PDAC using fractional polynomials and 5-year time trends using joinpoint regression. Associations with comorbidities and medication use were evaluated using conditional logistic regression.ResultsRisk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while following a U-shaped relationship for BMI and haemoglobin. Five-year trends showed biphasic BMI decrease and HbA1c increase prior to PDAC; early-gradual changes 2–3 years prior, followed by late-rapid changes 1–2 years prior. Liver markers and blood counts (white blood cell, platelets) showed monophasic rapid-increase approximately 1 year prior. Recent diagnosis of pancreatic cyst, pancreatitis, type 2 diabetes and initiation of certain glucose-lowering and acid-regulating therapies were associated with highest risk of PDAC.ConclusionRisk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while followed a U-shaped relationship for BMI and haemoglobin. BMI and HbA1c derange biphasically approximately 3 years prior while liver markers and blood counts (white blood cell, platelets) derange monophasically approximately 1 year prior to PDAC. Profiling these in combination with their temporality could inform earlier PDAC diagnosis.

Published
2023
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33. Analysis of severe outcomes associated with the SARS-CoV-2 Variant of Concern 202012/01 in England using ICNARC Case Mix Programme and QResearch databases

Author

Patone, Martina, primary, Thomas, Karen, additional, Hatch, Rob, additional, Tan, Pui San, additional, Coupland, Carol, additional, Liao, Weiqi, additional, Mouncey, Paul, additional, Harrison, David, additional, Rowan, Kathryn, additional, Horby, Peter, additional, Watkinson, Peter, additional, and Hippisley-Cox, Julia, additional

Published
2021
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35. Data Study Group Final Report: Roche

Author

Abdollahyan, Maryam, Bica, Ioana, Buchholz, Alexander, Conde, Susana, Cunningham, Nathan, Dennis, John, DiazOrdaz, Karla, Grimm, Fiona, Ilieva, Snezhana, Kiraly, Franz, Li, Chen, Liao, Weiqi, Mossotto, Enrico, Page, Hector, Parreno-Centeno, Mario, and Swallow, Ben

Abstract

Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges.\ud \ud Roche: Personalised lung cancer treatment modelling using electronic health records and genomics\ud \ud Cancer immunotherapy (CIT) is a promising new type of cancer treatment that uses the patient’s own immune system to fight cancer cells. CIT drugs work to stop the cancer cells from turning off the immune system’s T-cells by inhibiting the PD-L1 produced by the tumour cells (PD-L1 is a protein that binds to PD-1 receptors on T-cells and prevents the immune system from attacking the cancer cells).\ud \ud CIT is currently being used to treat patients with non-small cell lung cancer (NSCLC) for whom chemotherapy or other drugs have failed. CIT is also be-ing used as part of the first-line treatment in patients with advanced NSCLC (aNSCLC - stage III and higher). Theoretically, patients with high PD-L1 ex-pression levels are more likely to respond well to CIT; however, in practice, patient outcomes vary considerably.\ud \ud In this data study group, we investigated different approaches for predicting survival time for patients treated with CIT as first line of treatment, using both electronic health records and tumour genomic data. We also investigated the causal effects of CIT vs other oncology treatments, and studied treatment heterogeneity. The results contribute to identifying patients who are most likely to benefit from CIT.

Published
2020

38. Cluster-randomized controlled trial of the effects of free glasses on purchase of children's glasses in China: The PRICE (Potentiating Rural Investment in Children's Eyecare) study

Author

Wang, Xiuqin, primary, Congdon, Nathan, additional, Ma, Yue, additional, Hu, Min, additional, Zhou, Yuan, additional, Liao, Weiqi, additional, Jin, Ling, additional, Xiao, Baixiang, additional, Wu, Xiaoyi, additional, Ni, Ming, additional, Yi, Hongmei, additional, Huang, Yiwen, additional, Varga, Beatrice, additional, Zhang, Hong, additional, Cun, Yongkang, additional, Li, Xianshun, additional, Yang, Luhua, additional, Liang, Chaoguang, additional, Huang, Wan, additional, Rozelle, Scott, additional, and Ma, Xiaochen, additional

Published
2017
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39. A profile of The Clinical Course of Cognition and Comorbidity in Mild Cognitive Impairment and Dementia Study (The 4C study): two complementary longitudinal, clinical cohorts in the Netherlands

Author

Liao, Weiqi, primary, Hamel, Renske E. G., additional, Olde Rikkert, Marcel G. M., additional, Oosterveld, Saskia M., additional, Aalten, Pauline, additional, Verhey, Frans R. J., additional, Scheltens, Philip, additional, Sistermans, Nicole, additional, Pijnenburg, Yolande A. L., additional, van der Flier, Wiesje M., additional, Ramakers, Inez H. G. B., additional, and Melis, René J. F., additional

Published
2016
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40. Distinct laterality alterations distinguish mild cognitive impairment and Alzheimer's disease from healthy aging: Statistical parametric mapping with high resolution MRI

Author

Long, Xiaojing, Zhang, Lijuan, Liao, Weiqi, Jiang, Chunxiang, and Qiu, Bensheng

Subjects
Adult, Aged, 80 and over, Male, Aging, Brain Mapping, Age Factors, Middle Aged, Magnetic Resonance Imaging, Functional Laterality, Young Adult, Alzheimer Disease, Image Processing, Computer-Assisted, Humans, Cognitive Dysfunction, Female, Mental Status Schedule, Research Articles, Aged
Abstract

Laterality of human brain varies under healthy aging and diseased conditions. The alterations in hemispheric asymmetry may embed distinct biomarkers linked to the disease dynamics. Statistical parametric mapping based on high‐resolution magnetic resonance imaging (MRI) and image processing techniques have allowed automated characterization of morphological features across the entire brain. In this study, 149 subjects grouped in healthy young, healthy elderly, mild cognitive impairment (MCI), and Alzheimer's disease (AD) were investigated using multivariate analysis for regional cerebral laterality indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume measured on high‐resolution MR images. Asymmetry alteration of MCI and AD were characterized by marked region‐specific reduction, while healthy elderly featured a distinct laterality shift in the limbic system in addition to regional asymmetry loss. Lack of the laterality shift in limbic system and early loss of asymmetry in entorhinal cortex may be biomarkers to identify preclinical AD among other dementia. Multivariate analysis of hemispheric asymmetry may provide information helpful for monitoring the disease progress and improving the management of MCI and AD. Hum Brain Mapp 34:3400–3410, 2013. © 2012 Wiley Periodicals, Inc.

Published
2012

43. Healthy Aging

Author

Long, Xiaojing, primary, Liao, Weiqi, additional, Jiang, Chunxiang, additional, Liang, Dong, additional, Qiu, Bensheng, additional, and Zhang, Lijuan, additional

Published
2012
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