Evidence map›Paper›PMID 29773701›Full record

ArticleBMJ open2018

Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study.

Alessandro Montedori, Ettore Bidoli, Diego Serraino, Mario Fusco, Gianni Giovannini, Paola Casucci, David Franchini, Annalisa Granata, Valerio Ciullo, Maria Francesca Vitale and 7 more

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Alessandro MontedoriHealth Planning Service, Regional Health Authority of Umbria, Perugia, Italy.
Ettore BidoliCancer Epidemiology Unit, Centro di Riferimento Oncologico Aviano, Aviano, Italy.
Diego SerrainoCancer Epidemiology Unit, Centro di Riferimento Oncologico Aviano, Aviano, Italy.
Mario FuscoRegistro Tumori Regione Campania, ASL Napoli 3 Sud, Brusciano, Italy.
Gianni GiovanniniHealth Planning Service, Regional Health Authority of Umbria, Perugia, Italy.
Paola CasucciHealth ICT Service, Regional Health Authority of Umbria, Perugia, Italy.
David FranchiniHealth ICT Service, Regional Health Authority of Umbria, Perugia, Italy.
Annalisa GranataRegistro Tumori Regione Campania, ASL Napoli 3 Sud, Brusciano, Italy.
Valerio CiulloRegistro Tumori Regione Campania, ASL Napoli 3 Sud, Brusciano, Italy.
Maria Francesca VitaleRegistro Tumori Regione Campania, ASL Napoli 3 Sud, Brusciano, Italy.
Michele GobbatoSOC Epidemiologia Oncologica, Centro di Riferimento Oncologico Aviano, Aviano, Italy.
Rita ChiariDipartimento di Oncologia, Azienda Ospedaliera Perugia, Perugia, Italy.
Francesco CozzolinoHealth Planning Service, Regional Health Authority of Umbria, Perugia, Italy.
Massimiliano OrsoHealth Planning Service, Regional Health Authority of Umbria, Perugia, Italy.
Walter OrlandiDirezione salute, Regional Health Authority of Umbria, Perugia, Italy.
Iosief AbrahaHealth Planning Service, Regional Health Authority of Umbria, Perugia, Italy.ORCID 0000-0002-5440-775X
D.I.V.O. Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the accuracy of International Classification of Diseases 9th Revision-Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer.

designA cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical chart (reference standard). Case ascertainment was based on the presence of a primary nodular lesion in the lung and cytological or histological documentation of cancer from a primary or metastatic site.

settingThree operative units: administrative databases from Umbria Region (890 000 residents), ASL Napoli 3 Sud (NA) (1 170 000 residents) and Friuli Venezia Giulia (FVG) Region (1 227 000 residents).

participantsIncident subjects with lung cancer (n=386) diagnosed in primary position between 2012 and 2014 and a population of non-cases (n=280). OUTCOME MEASURES: Sensitivity, specificity and positive predictive value (PPV) for 162.x code.

results130 cases and 94 non-cases were randomly selected from each database and the corresponding medical charts were reviewed. Most of the diagnoses for lung cancer were performed in medical departments.True positive rates were high for all the three units. Sensitivity was 99% (95% CI 95% to 100%) for Umbria, 97% (95% CI 91% to 100%) for NA, and 99% (95% CI 95% to 100%) for FVG. The false positive rates were 24%, 37% and 23% for Umbria, NA and FVG, respectively. PPVs were 79% (73% to 83%)%) for Umbria, 58% (53% to 63%)%) for NA and 79% (73% to 84%)%) for FVG.

conclusionsCase ascertainment for lung cancer based on imaging or endoscopy associated with histological examination yielded an excellent sensitivity in all the three administrative databases. PPV was moderate for Umbria and FVG but lower for NA.

Indexed as

Databases, FactualInternational Classification of DiseasesAdultAgedClinical CodingCross-Sectional StudiesFemaleHumansItalyLung NeoplasmsMaleMiddle AgedSensitivity and Specificityadministrative databaseIcd-9-cmlung cancerpositive predictive valuesensitivity and specificityvalidity

Identifiers

PMID29773701
PMCPMC5961589

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.