Endpoint definition ↥ FinnGen phenotype data 321302 individuals Apply sex-specific rule None 321302 Check conditions None 321302 Filter registries Hospital Discharge: ICD-10 R90 Cause of death: ICD-10 R90 741 Check pre-conditions, main-only, mode, ICD version Look only at ICD versions H.D: 10 ; C.O.D: 10 741 Check minimum number of events None 741 Include endpoints None 741 R18_ABNORMAL_FINDI_DIAGNOST_IMAGI_CENTRAL_NERVOUS_SYSTEM Extra metadata Level in the ICD hierarchy 3 First used in FinnGen datafreeze DF4 Parent code in ICD-10 R9[0-4] Name in latin Reperta abnormia ex imagine diagnostica systematis nervosi centralis
FinnGen phenotype data 321302 individuals Apply sex-specific rule None 321302 Check conditions None 321302 Filter registries Hospital Discharge: ICD-10 R90 Cause of death: ICD-10 R90 741 Check pre-conditions, main-only, mode, ICD version Look only at ICD versions H.D: 10 ; C.O.D: 10 741 Check minimum number of events None 741 Include endpoints None 741 R18_ABNORMAL_FINDI_DIAGNOST_IMAGI_CENTRAL_NERVOUS_SYSTEM Extra metadata Level in the ICD hierarchy 3 First used in FinnGen datafreeze DF4 Parent code in ICD-10 R9[0-4] Name in latin Reperta abnormia ex imagine diagnostica systematis nervosi centralis
Similar endpoints ↥ List of similar endpoints to Abnormal findings on diagnostic imaging of central nervous system based on the number of shared cases. Broader endpoints: Abnormal findings on diagnostic imaging and in function studies, without diagnosis Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified Any event in hilmo or specialist outpatient Any ICDMAIN event in hilmo or causes of death Narrower endpoints: None Show all endpoint correlations
List of similar endpoints to Abnormal findings on diagnostic imaging of central nervous system based on the number of shared cases. Broader endpoints: Abnormal findings on diagnostic imaging and in function studies, without diagnosis Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified Any event in hilmo or specialist outpatient Any ICDMAIN event in hilmo or causes of death Narrower endpoints: None Show all endpoint correlations
Summary Statistics ↥ Key figures All Female Male ? X Number of individuals Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the number of individuals is 2, since only 2 unique individuals (FG1 and FG2) have EXAMPLE_ENDPOINT events. Number of individuals 714 449 265 ? X Unadjusted prevalence Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the unadjusted prevalence is 66 %. The unadjusted prevalence is the number of individuals having an endpoint divided by the total number of individuals. Here: 2 unique individuals (FG1 and FG2) have EXAMPLE_ENDPOINT events 1 individual (FG3) has no EXAMPLE_ENDPOINT event So the unadjusted prevalence is 2 / 3 = 66 %. Unadjusted prevalence (%) 0.23 0.26 0.20 ? X Mean age at first event Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the mean age at first event is 37.5. The mean age at first event for EXAMPLE_ENDPOINT is computed by: selecting individuals having EXAMPLE_ENDPOINT: FG1 and FG2 for these individuals, taking the age of their first event of EXAMPLE_ENDPOINT: 45 for FG1 and 30 for FG2 computing the mean of these values So the mean age at first event is Mean(45, 30) = 37.5. Mean age at first event (years) 52.78 50.99 55.82 ? X Follow-up Amount of time to look for the endpoint since entering the study. This is either either 1, 5, 15 years or the full study time from 1998 to 2019. Absolute risk Estimates the probability of dying from the current endpoint. Check the Documentation page for Mortality: absolute risk to get more details. Hazard Ratio (HR) and 95% Confidence Interval (CI) Measures how much the risk of dying increases (HR > 1) or decreases (HR < 1). Number of individuals (N) Number of individuals having the current endpoint and died during the follow-up time. Mortality Follow-up Absolute risk HR [95% CI] p N 1998–2019 0.06 4.73 [1.75, 12.78] 2.2e-3 58 15 years 0.01 0.96 [0.31, 3.01] 9.5e-1 11 5 years 0.00 4.05 [1.38, 11.89] 1.1e-2 24 1 year - - - - Age distribution of first events Year distribution of first events Cumulative Incidence
Key figures All Female Male ? X Number of individuals Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the number of individuals is 2, since only 2 unique individuals (FG1 and FG2) have EXAMPLE_ENDPOINT events. Number of individuals 714 449 265 ? X Unadjusted prevalence Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the unadjusted prevalence is 66 %. The unadjusted prevalence is the number of individuals having an endpoint divided by the total number of individuals. Here: 2 unique individuals (FG1 and FG2) have EXAMPLE_ENDPOINT events 1 individual (FG3) has no EXAMPLE_ENDPOINT event So the unadjusted prevalence is 2 / 3 = 66 %. Unadjusted prevalence (%) 0.23 0.26 0.20 ? X Mean age at first event Using example data: ID phenocode age FG1 EXAMPLE_ENDPOINT 45 FG1 ENDPOINT_XYZ 46 FG1 DEATH 47 FG2 EXAMPLE_ENDPOINT 30 FG2 EXAMPLE_ENDPOINT 30.1 FG3 ENDPOINT_XYZ 50 In this example the mean age at first event is 37.5. The mean age at first event for EXAMPLE_ENDPOINT is computed by: selecting individuals having EXAMPLE_ENDPOINT: FG1 and FG2 for these individuals, taking the age of their first event of EXAMPLE_ENDPOINT: 45 for FG1 and 30 for FG2 computing the mean of these values So the mean age at first event is Mean(45, 30) = 37.5. Mean age at first event (years) 52.78 50.99 55.82
? X Follow-up Amount of time to look for the endpoint since entering the study. This is either either 1, 5, 15 years or the full study time from 1998 to 2019. Absolute risk Estimates the probability of dying from the current endpoint. Check the Documentation page for Mortality: absolute risk to get more details. Hazard Ratio (HR) and 95% Confidence Interval (CI) Measures how much the risk of dying increases (HR > 1) or decreases (HR < 1). Number of individuals (N) Number of individuals having the current endpoint and died during the follow-up time. Mortality Follow-up Absolute risk HR [95% CI] p N 1998–2019 0.06 4.73 [1.75, 12.78] 2.2e-3 58 15 years 0.01 0.96 [0.31, 3.01] 9.5e-1 11 5 years 0.00 4.05 [1.38, 11.89] 1.1e-2 24 1 year - - - -
Follow-up Amount of time to look for the endpoint since entering the study. This is either either 1, 5, 15 years or the full study time from 1998 to 2019.
Absolute risk Estimates the probability of dying from the current endpoint. Check the Documentation page for Mortality: absolute risk to get more details.
Hazard Ratio (HR) and 95% Confidence Interval (CI) Measures how much the risk of dying increases (HR > 1) or decreases (HR < 1).
Number of individuals (N) Number of individuals having the current endpoint and died during the follow-up time.
Correlations ↥ Index endpoint: R18_ABNORMAL_FINDI_DIAGNOST_IMAGI_CENTRAL_NERVOUS_SYSTEM – Abnormal findings on diagnostic imaging of central nervous system GWS hits: 0
Survival analyses between endpoints ↥ Plot before Abnormal findings on diagnostic imaging of central nervous system after Abnormal findings on diagnostic imaging of central nervous system Loading survival analyses plot Table Loading survival analyses table Download CSV
Plot before Abnormal findings on diagnostic imaging of central nervous system after Abnormal findings on diagnostic imaging of central nervous system Loading survival analyses plot
Drugs most likely to be purchased after Abnormal findings on diagnostic imaging of central nervous system ↥ Download CSV