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1.
Article in English | MEDLINE | ID: mdl-38912790

ABSTRACT

CONTEXT: Predicting the progression of chronic kidney disease (CKD) to end-stage kidney disease (ESKD) is crucial for improving patient outcomes. OBJECTIVE: To reveal the highly predictive activity of serum bilirubin levels for the progression of CKD to ESKD, and to develop and validate a novel ESKD prediction model incorporating serum bilirubin levels. METHODS: We assessed the relative importance of 20 candidate predictors for ESKD, including serum bilirubin levels, in a CKD cohort (15< eGFR <60 mL/min/1.73 m2), and subsequently developed a prediction model using the selected variables. The development cohort comprised 4,103 individuals with CKD who underwent follow-up at Kyushu University Hospital, Japan, from 2008 to 2018. The primary outcome was incident ESKD, defined as an eGFR <15 mL/min/1.73 m2, chronic dialysis, or renal transplantation. RESULTS: The mean follow-up time was 7.0 ± 4.2 years, during which 489 individuals (11.9%) progressed to ESKD. The Cox proportional hazard model selected eGFR, serum bilirubin, proteinuria, age, diabetes, gender, hypertension, serum albumin, and hemoglobin in order of their importance. The predictive performance of the model was optimized by incorporating these 9 variables in discrimination evaluated by time-dependent area under the curve (AUC). This model also demonstrated excellent calibration. Additionally, this model exhibited excellent predictive performance in both discrimination (2-year AUC: 0.943, 5-year AUC: 0.935) and calibration in a validation cohort (n=2,799). CONCLUSION: Serum bilirubin levels were strong predictors for the progression of CKD to ESKD. Our novel model that incorporates serum bilirubin levels could accurately predict ESKD in individuals with CKD.

2.
Hypertens Res ; 45(12): 1869-1881, 2022 12.
Article in English | MEDLINE | ID: mdl-36171325

ABSTRACT

Renin-angiotensin system inhibitors have been shown to prevent cancer metastasis in experimental models, but there are limited data in clinical studies. We aimed to explore whether renin-angiotensin system inhibitors administered during the period of cancer resection can influence the subsequent development of metastasis by analyzing multiple individual types of primary cancers. A total of 4927 patients who had undergone resection of primary cancers at Kyushu University Hospital from 2009 to 2014 were enrolled and categorized into 3 groups based on the use of antihypertensive drugs: renin-angiotensin system inhibitors, other drugs, and none. Cumulative incidence functions of metastasis, treating death as a competing risk, were calculated, and the difference was examined among groups by Gray's test. Fine and Gray's model was employed to evaluate multivariate-adjusted hazards of incidental metastasis. In the multivariate-adjusted analysis, patients with skin and renal cancers showed statistically higher risks of metastasis with the use of renin-angiotensin system inhibitors (hazard ratio [95% confidence interval], 5.81 [1.07-31.57] and 4.24 [1.71-10.53], respectively). Regarding pancreatic cancer, patients treated with antihypertensive drugs other than renin-angiotensin system inhibitors had a significantly increased risk of metastasis (hazard ratio [95% confidence interval], 3.31 [1.43-7.69]). Future larger studies are needed to ascertain whether renin-angiotensin system inhibitors can increase the risk of metastasis in skin and renal cancers, focusing on specific tissue types and potential factors associated with renin-angiotensin system inhibitor use.


Subject(s)
Kidney Neoplasms , Pancreatic Neoplasms , Humans , Antihypertensive Agents/therapeutic use , Angiotensin Receptor Antagonists/therapeutic use , Angiotensin Receptor Antagonists/pharmacology , Angiotensin-Converting Enzyme Inhibitors/pharmacology , Renin-Angiotensin System , Retrospective Studies , Electronic Health Records , Enzyme Inhibitors/pharmacology , Pancreatic Neoplasms/chemically induced , Pancreatic Neoplasms/drug therapy , Kidney Neoplasms/drug therapy
3.
Int J Hematol ; 116(6): 863-870, 2022 Dec.
Article in English | MEDLINE | ID: mdl-35932399

ABSTRACT

Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of chronic myeloid leukemia (CML). However, TKI-related chronic renal toxicity has been reported, particularly in patients with hypertension. We assessed whether incidental use of specific types of antihypertensive drugs, including renin-aldosterone-angiotensin system inhibitors (RAASis), affects the change in estimated glomerular filtration rate (eGFR) during TKI treatment. We retrospectively analyzed all eGFR measurements during TKI treatment for 142 CML patients at Kyushu University Hospital, estimating the rate of eGFR change using a mixed-effects model. Overall, a significant interaction was found between the type of antihypertensive medication used and the yearly change in eGFR (P < 0.01), with RAASi users exhibiting the most rapid decrease in eGFR (- 5.5%/year). The analysis by TKI used showed that the interaction was significant only in imatinib and bosutinib users (P < 0.01 and P = 0.04, respectively). The yearly rate of eGFR decrease was the most notable in RAASi users, at - 5.7 (- 6.6, - 4.9) and - 10.1 (- 12.3, - 7.9) for imatinib and bosutinib users, respectively. Our findings indicate that eGFR should be carefully monitored in patients taking these TKIs.


Subject(s)
Antihypertensive Agents , Leukemia, Myelogenous, Chronic, BCR-ABL Positive , Humans , Imatinib Mesylate/adverse effects , Glomerular Filtration Rate , Antihypertensive Agents/pharmacology , Antihypertensive Agents/therapeutic use , Aldosterone/pharmacology , Aldosterone/therapeutic use , Renin/pharmacology , Renin/therapeutic use , Retrospective Studies , Protein Kinase Inhibitors/adverse effects , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/complications , Enzyme Inhibitors/therapeutic use , Angiotensins/pharmacology , Angiotensins/therapeutic use
4.
Sci Rep ; 12(1): 12482, 2022 07 21.
Article in English | MEDLINE | ID: mdl-35864124

ABSTRACT

This study aimed to develop a simplified model for predicting end-stage kidney disease (ESKD) in patients with diabetes. The cohort included 2549 individuals who were followed up at Kyushu University Hospital (Japan) between January 1, 2008 and December 31, 2018. The outcome was a composite of ESKD, defined as an eGFR < 15 mL min-1 [1.73 m]-2, dialysis, or renal transplantation. The mean follow-up was 5.6 [Formula: see text] 3.7 years, and ESKD occurred in 176 (6.2%) individuals. Both a machine learning random forest model and a Cox proportional hazard model selected eGFR, proteinuria, hemoglobin A1c, serum albumin levels, and serum bilirubin levels in a descending order as the most important predictors among 20 baseline variables. A model using eGFR, proteinuria and hemoglobin A1c showed a relatively good performance in discrimination (C-statistic: 0.842) and calibration (Nam and D'Agostino [Formula: see text]2 statistic: 22.4). Adding serum albumin and bilirubin levels to the model further improved it, and a model using 5 variables showed the best performance in the predictive ability (C-statistic: 0.895, [Formula: see text]2 statistic: 7.7). The accuracy of this model was validated in an external cohort (n = 5153). This novel simplified prediction model may be clinically useful for predicting ESKD in patients with diabetes.


Subject(s)
Diabetes Mellitus , Kidney Failure, Chronic , Renal Insufficiency, Chronic , Bilirubin , Disease Progression , Glomerular Filtration Rate , Glycated Hemoglobin , Humans , Proteinuria , Renal Dialysis , Risk Factors , Serum Albumin
5.
Sci Rep ; 11(1): 13224, 2021 06 24.
Article in English | MEDLINE | ID: mdl-34168201

ABSTRACT

Serum levels of bilirubin, a strong antioxidant, may influence cancer risk. We aimed to assess the association between serum bilirubin levels and cancer risk. Data were retrieved from 10-year electronic medical records at Kyushu University Hospital (Japan) for patients aged 20 to 69 years old. The associations of baseline bilirubin levels with cancer risk (lung, colon, breast, prostate, and cervical) were evaluated using a gradient boosting decision tree (GBDT) model, a machine learning algorithm, and Cox proportional hazard regression model, adjusted for age, smoking, body mass index, and diabetes. The number of study subjects was 29,080. Median follow-up time was 4.7 years. GBDT models illustrated that baseline bilirubin levels were negatively and non-linearly associated with the risk of lung (men), colon, and cervical cancer. In contrast, a U-shaped association was observed for breast and prostate cancer. Cox hazard regression analyses confirmed that baseline bilirubin levels (< 1.2 mg/dL) were negatively associated with lung cancer risk in men (HR = 0.474, 95% CI 0.271-0.828, P = 0.009) and cervical cancer risk (HR = 0.365, 95% CI 0.136-0.977, P = 0.045). Additionally, low bilirubin levels (< 0.6 mg/dL) were associated with total death (HR = 1.744, 95% CI 1.369-2.222, P < 0.001). Serum bilirubin may have a beneficial effect on the risk of some types of cancers.


Subject(s)
Bilirubin/blood , Neoplasms/blood , Neoplasms/etiology , Body Mass Index , Female , Follow-Up Studies , Humans , Japan , Male , Middle Aged , Proportional Hazards Models , Risk Factors , Smoking/adverse effects
6.
BMC Med Inform Decis Mak ; 21(1): 52, 2021 02 11.
Article in English | MEDLINE | ID: mdl-33573645

ABSTRACT

BACKGROUND: No case definition of Type 1 diabetes (T1D) for the claims data has been proposed in Japan yet. This study aimed to evaluate the performance of candidate case definitions for T1D using Electronic health care records (EHR) and claims data in a University Hospital in Japan. METHODS: The EHR and claims data for all the visiting patients in a University Hospital were used. As the candidate case definitions for claims data, we constructed 11 definitions by combinations of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. (ICD 10) code of T1D, the claims code of insulin needles for T1D patients, basal insulin, and syringe pump for continuous subcutaneous insulin infusion (CSII). We constructed a predictive model for T1D patients using disease names, medical practices, and medications as explanatory variables. The predictive model was applied to patients of test group (validation data), and performances of candidate case definitions were evaluated. RESULTS: As a result of performance evaluation, the sensitivity of the confirmed disease name of T1D was 32.9 (95% CI: 28.4, 37.2), and positive predictive value (PPV) was 33.3 (95% CI: 38.0, 38.4). By using the case definition of both the confirmed diagnosis of T1D and either of the claims code of the two insulin treatment methods (i.e., syringe pump for CSII and insulin needles), PPV improved to 90.2 (95% CI: 85.2, 94.4). CONCLUSIONS: We have established a case definition with high PPV, and the case definition can be used for precisely detecting T1D patients from claims data in Japan.


Subject(s)
Diabetes Mellitus, Type 1 , Diabetes Mellitus, Type 1/diagnosis , Diabetes Mellitus, Type 1/drug therapy , Humans , Insulin , Insurance, Health , International Classification of Diseases , Japan
7.
Stud Health Technol Inform ; 264: 1498-1499, 2019 Aug 21.
Article in English | MEDLINE | ID: mdl-31438200

ABSTRACT

We aimed to develop rhabdomyolysis (RB) phenotyping algorithms using machine learning techniques and to create subphenotyping algorithms to identify RB patients who lack RB diagnosis. Two pattern algorithms, one with a focus on improving predictive value and one focused on improving sensitivity, were finally created and had a high area under the curve value of 0.846. Although we were unable to create subphenotyping algorithms, an attempt to detect unknown RB patients is important for epidemiological studies.


Subject(s)
Electronic Health Records , Rhabdomyolysis , Algorithms , Databases, Factual , Humans , Machine Learning
8.
Stud Health Technol Inform ; 264: 1562-1563, 2019 Aug 21.
Article in English | MEDLINE | ID: mdl-31438232

ABSTRACT

Data standardiztion an important aspect to ensure data quality for utilizing large-scale, medical information databases such as the Medical Information Database Network (MID-NET) Project in Japan. We established a governance center to assess the consistency of standard codes across MID-NET-cooperating medical institutions. Moreover, we developed a real-time validation tool and determined its effect in improving data quality in medical institutions by providing a central feedback on the detected differences in standard disease-name codes.


Subject(s)
Databases, Factual , Japan , Medical Informatics , Reference Standards
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