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92 lines
2.7 KiB
SQL
92 lines
2.7 KiB
SQL
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/*get all the ndc codes associated with an rxcui
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* Same as query
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* http://will-office:4000/REST/rxcui/1668240/allhistoricalndcs.json
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* note the different formats of the dates.
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*
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* Based on http://will-office:4000/RxNav/search?searchBy=RXCUI&searchTerm=1668240
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* it appears that this rxcui is a sbd or bpck (branded drug or pack)
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*
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* If I grab every brand, then every branded drug or pack associated with that drug and then attach that to the nsde data I would get the marketing dates required.
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* --get brand names
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* trial -> mesh_term -> IN/MIN (rxcui) -> BN (rxcui)
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* -- associate brand names to marketing dates
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* BN (rxcui) --> SBD/BPCK (RXCUI) --> ndc11 --> nsde
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* */
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/*
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* I do need to figure out a way to change the date types when importing into postgres. In mariadb they ar mmYYYY wheras in the jsonapi they are YYYYmm but I want is YYYY-mm-01
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*/
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---assoicate ingredients, brands, and approved packaging RXCUIs.
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create temp table trial_to_pack_rxcui as
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with trialncts as (
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SELECT DISTINCT nct_id 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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bi.downcase_mesh_term,
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rp.rxcui AS drug_rxcui,
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rn.tty1,
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rn.rxcui1 as ingredient_rxcui, --ingredients
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rn.tty2 ,
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rn.rxcui2 as brand_or_pack_rxcui --brand or pack
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FROM ctgov.browse_interventions bi
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LEFT OUTER JOIN rxnorm_migrated.rxnorm_props AS rp
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on bi.downcase_mesh_term = rp.propvalue1 --Link drug ingredient
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LEFT OUTER JOIN rxnorm_migrated.rxnorm_relations AS rn
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on rp.rxcui = rn.rxcui1 --Grab brand names
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WHERE
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bi.nct_id in (
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SELECT nct_id FROM trialncts
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)
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and
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bi.mesh_type='mesh-list'
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and
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rn.tty1 in ('IN','MIN')
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and
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rn.tty2 = 'BN'
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;
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--link brand names to drug applications (NDA/ANDA etc)
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select rr.rxcui1 as BN, rr.rxcui2 as pack, ah.ndc as pack_ndc11
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from
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rxnorm_migrated.rxnorm_relations rr
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left outer join rxnorm_migrated."ALLNDC_HISTORY" as ah
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on rr.rxcui2 = ah.rxcui
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where
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tty1 = 'BN'
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and
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tty2 in ('SBD', 'BPCK')
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and
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ah.sab='RXNORM'
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;
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---associate NDAs/ANDAs to marketing start dates
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---Get start of coverage periods for NSDE dates grouped by arbitrary grouping.
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SELECT n.application_number_or_citation, count(*), min( marketing_start_date )
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FROM spl.nsde as n
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where product_type = 'HUMAN PRESCRIPTION DRUG'
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group by n.application_number_or_citation ;
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---For a given date, find which NDAs/ANDAs were active were active.
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SELECT n.application_number_or_citation, count(*)
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FROM spl.nsde as n
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where
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product_type = 'HUMAN PRESCRIPTION DRUG'
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and
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marketing_start_date < '2010-05-01'
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and
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marketing_end_date > '2010-05-01'
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group by n.application_number_or_citation ;
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