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main
...
llm-extrac
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||||
{
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||||
"folders": {},
|
||||
"connections": {
|
||||
"mariaDB-186c896820e-6ff11b5b802d8b82": {
|
||||
"provider": "mysql",
|
||||
"driver": "mariaDB",
|
||||
"name": "rxnav",
|
||||
"save-password": true,
|
||||
"configuration": {
|
||||
"host": "will-office",
|
||||
"port": "3306",
|
||||
"url": "jdbc:mariadb://will-office:3306/",
|
||||
"configurationType": "MANUAL",
|
||||
"type": "dev",
|
||||
"auth-model": "native"
|
||||
}
|
||||
},
|
||||
"postgres-jdbc-186c896a347-2a3d946d2dea4df7": {
|
||||
"provider": "postgresql",
|
||||
"driver": "postgres-jdbc",
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||||
"name": "aact_db",
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||||
"save-password": true,
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||||
"configuration": {
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||||
"host": "100.95.169.11",
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||||
"port": "5432",
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||||
"database": "aact_db",
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||||
"url": "jdbc:postgresql://100.95.169.11:5432/aact_db",
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||||
"configurationType": "MANUAL",
|
||||
"type": "dev",
|
||||
"provider-properties": {},
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||||
"auth-model": "native"
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||||
},
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||||
"custom-properties": {
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||||
"resultset.maxrows": "500"
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||||
}
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||||
},
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||||
"postgres-jdbc-186cd8f479f-6cc3c10c8adc3359": {
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"provider": "postgresql",
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||||
"driver": "postgres-jdbc",
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||||
"name": "drugcentral",
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"save-password": true,
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"configuration": {
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"host": "localhost",
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||||
"port": "54320",
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||||
"database": "postgres",
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||||
"url": "jdbc:postgresql://localhost:54320/postgres",
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"configurationType": "MANUAL",
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||||
"type": "dev",
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||||
"auth-model": "native"
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||||
}
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||||
}
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||||
},
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||||
"connection-types": {
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||||
"dev": {
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||||
"name": "Development",
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||||
"color": "255,255,255",
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||||
"description": "Regular development database",
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||||
"auto-commit": true,
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||||
"confirm-execute": false,
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"confirm-data-change": false,
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"auto-close-transactions": false
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}
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}
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}
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@ -0,0 +1 @@
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{"resources":{"Scripts/ASSOICATING NCTIDs to NDCs and Marketing dates.sql":{"default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db","default-schema":"public"},"Scripts/Data_summaries.sql":{"default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db","default-schema":"public"},"Scripts/DevelopingLinks.sql":{"default-schema":"public","default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db"},"Scripts/DiseaseBurdens_create_table.sql":{"default-schema":"public","default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db"},"Scripts/GlobalBurdensOfDisease2019Codebook.sql":{"default-schema":"DiseaseBurden","default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db"},"Scripts/GroupingTrials.sql":{"default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db","default-schema":"public"},"Scripts/Script.sql":{"default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db","default-schema":"public"},"Scripts/TablesAndViews_Public.sql":{"default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db","default-schema":"public"},"development_sql/ASSOICATING NCTIDs to NDCs and Marketing dates.sql":{"default-schema":"public","default-datasource":"postgres-jdbc-186c896a347-2a3d946d2dea4df7","default-catalog":"aact_db"}}}
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@ -1,308 +0,0 @@
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select * from formatted_data_with_planned_enrollment fdwpe
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;
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select * from formatted_data_mat fdm
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;
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select count(distinct condition ) from formatted_data_mat fdm
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select nct_id, fdm.current_status , count(*)
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from formatted_data_mat fdm
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group by nct_id , fdm.current_status
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order by nct_id
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;
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select * from formatted_data_mat fdm ;
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-- group with trial split
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with cte as (
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select nct_id
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from formatted_data_mat fdm
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group by nct_id
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having count(distinct current_status) > 1
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order by nct_id
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)
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select
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fdm.nct_id
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, current_status
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, earliest_date_observed
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, elapsed_duration
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, n_brands
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, category_id
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, h_sdi_val
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, h_sdi_u95
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, h_sdi_l95
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, hm_sdi_val
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, hm_sdi_u95
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, hm_sdi_l95
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, m_sdi_val
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, m_sdi_u95
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, m_sdi_l95
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, lm_sdi_val
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, lm_sdi_u95
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, lm_sdi_l95
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, l_sdi_val
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, l_sdi_u95
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, l_sdi_l95
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from formatted_data_mat fdm
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join cte on cte.nct_id = fdm.nct_id
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group by
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fdm.nct_id
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, current_status
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, earliest_date_observed
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, elapsed_duration
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, n_brands
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, category_id
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, h_sdi_val
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, h_sdi_u95
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, h_sdi_l95
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, hm_sdi_val
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, hm_sdi_u95
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, hm_sdi_l95
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, m_sdi_val
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, m_sdi_u95
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, m_sdi_l95
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, lm_sdi_val
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, lm_sdi_u95
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, lm_sdi_l95
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, l_sdi_val
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, l_sdi_u95
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, l_sdi_l95
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order by nct_id , earliest_date_observed
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;
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select count(distinct category_id ) from
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select distinct category_id from formatted_data_mat fdm
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;
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-- group with trial split
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with cte as (
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select nct_id
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from formatted_data_mat fdm
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group by nct_id
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having count(distinct current_status) > 1
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order by nct_id
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)
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select
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fdm.nct_id
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, current_status
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, earliest_date_observed
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, elapsed_duration
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, n_brands
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, category_id
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, h_sdi_val
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, h_sdi_u95
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, h_sdi_l95
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, hm_sdi_val
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, hm_sdi_u95
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, hm_sdi_l95
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, m_sdi_val
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, m_sdi_u95
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, m_sdi_l95
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, lm_sdi_val
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, lm_sdi_u95
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, lm_sdi_l95
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, l_sdi_val
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, l_sdi_u95
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, l_sdi_l95
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from formatted_data_mat fdm
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join cte on cte.nct_id = fdm.nct_id
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group by
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fdm.nct_id
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, current_status
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, earliest_date_observed
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, elapsed_duration
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, n_brands
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, category_id
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, h_sdi_val
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, h_sdi_u95
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, h_sdi_l95
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, hm_sdi_val
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, hm_sdi_u95
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, hm_sdi_l95
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, m_sdi_val
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, m_sdi_u95
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, m_sdi_l95
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, lm_sdi_val
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, lm_sdi_u95
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, lm_sdi_l95
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, l_sdi_val
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, l_sdi_u95
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, l_sdi_l95
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order by nct_id , earliest_date_observed
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; --TODO: join to usp dc dataset
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WITH trialncts AS (
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SELECT DISTINCT ts.nct_id
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FROM history.trial_snapshots ts
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), nct_to_cui AS (
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SELECT bi.nct_id,
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bi.downcase_mesh_term,
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rr.tty2,
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rr.rxcui2 AS approved_drug_rxcui,
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count(*) AS count
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FROM ctgov.browse_interventions bi
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LEFT JOIN rxnorm_migrated.rxnorm_props rp ON bi.downcase_mesh_term::text = rp.propvalue1::text
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LEFT JOIN rxnorm_migrated.rxnorm_relations rr ON rr.rxcui1 = rp.rxcui
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WHERE (bi.nct_id::text IN ( SELECT trialncts.nct_id
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FROM trialncts)) AND bi.mesh_type::text = 'mesh-list'::text AND rp.propname::text = 'Active_ingredient_name'::text AND (rr.tty2::text = ANY (ARRAY['BPCK'::text, 'SCD'::text, 'SBD'::text, 'GPCK'::text]))
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GROUP BY bi.nct_id, bi.downcase_mesh_term, rr.tty2, rr.rxcui2
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)
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SELECT nct_to_cui.nct_id,
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ud."USP Category",
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ud."USP Class"
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FROM nct_to_cui
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JOIN "Formularies".usp_dc ud ON ud.rxcui::bpchar = nct_to_cui.approved_drug_rxcui
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GROUP BY nct_to_cui.nct_id, ud."USP Category", ud."USP Class"
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ORDER BY nct_to_cui.nct_id;
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CREATE MATERIALIZED VIEW "Formularies".nct_to_brands_through_uspdc
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AS
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WITH trialncts AS (
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SELECT DISTINCT ts.nct_id
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FROM history.trial_snapshots ts
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)
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SELECT
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bi.nct_id,
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count( distinct rr2.rxcui2 ) as brand_name_count
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FROM ctgov.browse_interventions bi
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LEFT JOIN rxnorm_migrated.rxnorm_props rp ON bi.downcase_mesh_term::text = rp.propvalue1::text --match mesh terms to rxcui
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LEFT JOIN rxnorm_migrated.rxnorm_relations rr ON rr.rxcui1 = rp.rxcui -- match rxcui to relations between rxcuis
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LEFT JOIN rxnorm_migrated.rxnorm_relations rr2 ON rr.rxcui2 = rr2.rxcui1 -- match rxcui to relations between rxcuis
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WHERE
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(bi.nct_id::text IN (SELECT trialncts.nct_id FROM trialncts)) --check the nct_id is in our list
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AND
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bi.mesh_type::text = 'mesh-list'::text --we are only looking at mesh "list" rxcuis
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AND rp.propname::text = 'Active_ingredient_name'::text --and we only care about active ingredients linked to \/\/\/\/\/
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AND (rr.tty2::text = ANY (ARRAY['BPCK'::text, 'SCD'::text, 'SBD'::text, 'GPCK'::text])) --and we are linking from active ingredients ^^^^ to branded packs
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AND (rr2.tty2::text = 'BN') --and from branded packs back to brand names
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GROUP BY bi.nct_id --remove duplicates
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;
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/*
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*
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*/
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select
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fdqpe.nct_id
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--,fdqpe.start_date
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--,fdqpe.current_enrollment
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--,fdqpe.enrollment_category
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,fdqpe.current_status
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,fdqpe.earliest_date_observed
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,fdqpe.elapsed_duration
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,fdqpe.n_brands as identical_brands
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,ntbtu.brand_name_count
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,fdqpe.category_id
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,fdqpe.final_status
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,fdqpe.h_sdi_val
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--,fdqpe.h_sdi_u95
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--,fdqpe.h_sdi_l95
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,fdqpe.hm_sdi_val
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--,fdqpe.hm_sdi_u95
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--,fdqpe.hm_sdi_l95
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,fdqpe.m_sdi_val
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--,fdqpe.m_sdi_u95
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--,fdqpe.m_sdi_l95
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,fdqpe.lm_sdi_val
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--,fdqpe.lm_sdi_u95
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--,fdqpe.lm_sdi_l95
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,fdqpe.l_sdi_val
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--,fdqpe.l_sdi_u95
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--,fdqpe.l_sdi_l95
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from formatted_data_mat fdqpe
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join "Formularies".nct_to_brands_through_uspdc ntbtu
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on fdqpe.nct_id = ntbtu.nct_id
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;
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--example of multiple reopenings
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select *
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from formatted_data_mat fdm
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where nct_id = 'NCT01239797'
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--attempt to automatically find transition periods
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||||
with cte1 as (
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select nct_id, min(earliest_date_observed) over (partition by nct_id) as earliest_closed_enrollment
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||||
from formatted_data_mat fdm
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||||
where current_status = 'Active, not recruiting'
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||||
), cte2 as (
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select nct_id, max(earliest_date_observed) over (partition by nct_id) latest_open_enrollment
|
||||
from formatted_data_mat fdm
|
||||
where current_status != 'Active, not recruiting'
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||||
)
|
||||
select
|
||||
cte1.nct_id
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||||
,cte1.earliest_closed_enrollment
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||||
,cte2.latest_open_enrollment
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,cte1.earliest_closed_enrollment - cte2.latest_open_enrollment
|
||||
from cte1
|
||||
join cte2 on cte1.nct_id = cte2.nct_id
|
||||
/*group by
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||||
cte1.nct_id
|
||||
,cte1.earliest_closed_enrollment
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||||
,cte2.latest_open_enrollment
|
||||
*/
|
||||
|
||||
|
||||
|
||||
/* So ocassionally a study reopens enrollment.
|
||||
* If that didn't happen, then I could just find the first enrollment matching X and/or last enrollment matching Y
|
||||
* to get the transitions
|
||||
* Instead I need to create shifts of statuses between snapshots, and then remove all of those that did not change.
|
||||
*
|
||||
* Better yet, just get the last shift to ANR.
|
||||
* */
|
||||
|
||||
|
||||
/* Take each entry and get the status from a lagged snapshot
|
||||
* Then select each snapshot moving from previous_state to ANR
|
||||
* and filter out everything except the last one.
|
||||
* */
|
||||
with cte as (
|
||||
select
|
||||
nct_id
|
||||
,lag(current_status, 1) over (partition by nct_id order by earliest_date_observed) as previous_status
|
||||
,current_status
|
||||
,earliest_date_observed as date_current
|
||||
from formatted_data_mat fdm
|
||||
), cte2 as (
|
||||
select
|
||||
nct_id
|
||||
,previous_status
|
||||
,current_status
|
||||
,max(date_current) as date_current_max
|
||||
from cte
|
||||
where
|
||||
previous_status != current_status
|
||||
and
|
||||
current_status = 'Active, not recruiting'
|
||||
group by
|
||||
nct_id
|
||||
,previous_status
|
||||
,current_status
|
||||
,date_current
|
||||
)
|
||||
select *
|
||||
from formatted_data_mat fdm
|
||||
join cte2
|
||||
on cte2.nct_id = fdm.nct_id
|
||||
and cte2.date_current_max = fdm.earliest_date_observed
|
||||
; --join back into
|
||||
|
||||
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@ -1,9 +0,0 @@
|
||||
USP[[:space:]]DC/USP_DC_12_2021_RELEASE_1.0.xlsx filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]DC/usp_dc_pub_2023_release_2.0_updated_final.xlsx filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/Final_Report_and_Summary_of_Methodology_and_Approach_v1.1.pdf filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/MMG_v8.0_Alignment_File.xlsx filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/Summary_of_Changes_between_MMGv7.0_and_MMGv8.0.pdf filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/USP_Medicare_Model_Guidelines_v8.0__All_Excel_Spreadsheets_.xlsx filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/USP_Medicare_Model_Guidelines_v8.0__Categories_and_Classes_.pdf filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/USP_Medicare_Model_Guidelines_v8.0__Showing_changes_from_v7.0_.pdf filter=lfs diff=lfs merge=lfs -text
|
||||
USP[[:space:]]MMG/USP_Medicare_Model_Guidelines_v8.0__With_Example_Part_D_Drugs_.pdf filter=lfs diff=lfs merge=lfs -text
|
||||
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