{"entity": "researcher", "timestamp": "2026-09-23T22:18:13.253Z", "family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "affiliations": ["Centre for Pharmacoepidemiology, Department of Medicine Solna, Karolinska Institutet, S-171 76, Stockholm, Sweden. laura.pazzagli@ki.se."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2"}}, "publications": [{"entity": "publication", "iuid": "f24fdfb1c5874337ad8bac7491b2173f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f24fdfb1c5874337ad8bac7491b2173f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f24fdfb1c5874337ad8bac7491b2173f"}}, "title": "Consistency between the National Patient Register and the Swedish Cancer Register.", "authors": [{"family": "Sakakibara", "given": "Sakura", "initials": "S", "orcid": "0009-0009-1695-6879", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a49fc0aec3d2462a922ea52c8a0ca888.json"}}, {"family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}}, {"family": "Linder", "given": "Marie", "initials": "M", "orcid": "0000-0003-2619-2189", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2caaaaa0836e48948cc20734a68c4e22.json"}}], "type": "journal article", "published": "2024-04-00", "journal": {"title": "Pharmacoepidemiol Drug Saf", "issn": "1099-1557", "volume": "33", "issue": "4", "pages": "e5780", "issn-l": null}, "abstract": "The Swedish National Patient Register (NPR) is widely used as a data source in epidemiological studies, but the consistency of all cancer diagnoses compared to the Swedish Cancer Register (SCR) remains unclear. Using NPR supplementary for detecting safety signals is beneficial due to shorter data extraction delays compared to using SCR alone. This study aims to evaluate the consistency of NPR for cancer diagnoses compared to SCR and its potential use in pharmacoepidemiology.\n\nPatients with a cancer diagnosis recorded in SCR during 2018-2020 were included. To measure the consistency of NPR diagnoses with SCR as the gold standard, positive predictive value (PPV), and sensitivity were calculated. As an empirical example showing differences in identification of cancer diagnoses in NPR and SCR, two nested case-control studies for the association between antidiabetic medications and pancreatic cancer were repeated using the two registers. Conditional logistic regression was performed and the 95% confidence intervals (CIs) for the odds ratios (ORs) were checked for overlaps.\n\nFor breast, male genital organs, and oral cancers consistency was high (PPV: 87.5%-97.4%, sensitivity: 82.2%-91.0%), while for female genital organs, thyroid, and ill-defined, secondary, and unspecified sites cancers it was low (PPV: 8.8%-90.0%, sensitivity: 19.9%-32.3%). All the CIs for the ORs from the nested case-control studies overlapped when pancreatic cancer was identified in NPR or SCR.\n\nConsistency of cancer diagnoses in NPR when compared to SCR depends on cancer type with higher consistency for some cancers and lower for others. Differences in diagnostic processes for different cancer types and coding of cancer in the two registers may explain part of the inconsistent results.", "doi": "10.1002/pds.5780", "pmid": "38511251", "labels": [], "xrefs": [], "notes": [], "created": "2026-09-23T13:00:49.051Z", "modified": "2026-09-23T13:00:49.191Z"}, {"entity": "publication", "iuid": "ec54ba7e990b40ed8acb0660c8b48f4c", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ec54ba7e990b40ed8acb0660c8b48f4c.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ec54ba7e990b40ed8acb0660c8b48f4c"}}, "title": "Model misspecification and bias for inverse probability weighting estimators of average causal effects.", "authors": [{"family": "Waernbaum", "given": "Ingeborg", "initials": "I", "orcid": "0000-0002-4457-5311", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d89b77830b8c4e5794907c893fe3db0b.json"}}, {"family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}}], "type": "journal article", "published": "2023-02-00", "journal": {"title": "Biom J", "issn": "1521-4036", "volume": "65", "issue": "2", "pages": "e2100118", "issn-l": null}, "abstract": "Commonly used semiparametric estimators of causal effects specify parametric models for the propensity score (PS) and the conditional outcome. An example is an augmented inverse probability weighting (IPW) estimator, frequently referred to as a doubly robust estimator, because it is consistent if at least one of the two models is correctly specified. However, in many observational studies, the role of the parametric models is often not to provide a representation of the data-generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper, we propose a crude analytical approach to study the large-sample bias of estimators when the models are assumed to be approximations of the data-generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two IPW estimators, using a misspecified PS model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression (OR) and the PS. For the two IPW estimators, we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models is better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecification of the outcome model is moderate, the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations, we include three simulation studies and corresponding approximations of the large-sample biases. In a dataset from the National Health and Nutrition Examination Survey, we estimate the effect of smoking on blood lead levels.", "doi": "10.1002/bimj.202100118", "pmid": "36045099", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10087564"}], "notes": [], "created": "2026-09-23T11:06:11.238Z", "modified": "2026-09-23T11:06:11.357Z"}, {"entity": "publication", "iuid": "31316c274539455692cdc167f9901d19", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/31316c274539455692cdc167f9901d19.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/31316c274539455692cdc167f9901d19"}}, "title": "Rationale and performances of a data-driven method for computing the duration of pharmacological prescriptions using secondary data sources.", "authors": [{"family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}}, {"family": "Liang", "given": "David", "initials": "D"}, {"family": "Andersen", "given": "Morten", "initials": "M"}, {"family": "Linder", "given": "Marie", "initials": "M"}, {"family": "Khan", "given": "Abdul Rauf", "initials": "AR"}, {"family": "Sessa", "given": "Maurizio", "initials": "M"}], "type": "journal article", "published": "2022-04-15", "journal": {"title": "Sci Rep", "issn": "2045-2322", "volume": "12", "issue": "1", "pages": "6245", "issn-l": "2045-2322"}, "abstract": "The assessment of the duration of pharmacological prescriptions is an important phase in pharmacoepidemiologic studies aiming to investigate persistence, effectiveness or safety of treatments. The Sessa Empirical Estimator (SEE) is a new data-driven method which uses k-means algorithm for computing the duration of pharmacological prescriptions in secondary data sources when this information is missing or incomplete. The SEE was used to compute durations of exposure to pharmacological treatments where simulated and real-world data were used to assess its properties comparing the exposure status extrapolated with the method with the \"true\" exposure status available in the simulated and real-world data. Finally, the SEE was also compared to a Researcher-Defined Duration (RDD) method. When using simulated data, the SEE showed accuracy of 96% and sensitivity of 96%, while when using real-world data, the method showed sensitivity ranging from 78.0 (nortriptyline) to 95.1% (propafenone). When compared to the RDD, the method had a lower median sensitivity of 2.29% (interquartile range 1.21-4.11%). The SEE showed good properties and may represent a promising tool to assess exposure status when information on treatment duration is not available.", "doi": "10.1038/s41598-022-10144-9", "pmid": "35428827", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9012860"}, {"db": "pii", "key": "10.1038/s41598-022-10144-9"}], "notes": [], "created": "2026-09-23T12:17:39.993Z", "modified": "2026-09-23T12:17:40.015Z"}, {"entity": "publication", "iuid": "84132b483bd742ef925ba567ab364bc6", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/84132b483bd742ef925ba567ab364bc6.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/84132b483bd742ef925ba567ab364bc6"}}, "title": "The use of uncertain exposure-A method to define switching and add-on in pharmacoepidemiology.", "authors": [{"family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}}, {"family": "Linder", "given": "Marie", "initials": "M", "orcid": "0000-0003-2619-2189", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2caaaaa0836e48948cc20734a68c4e22.json"}}, {"family": "Reutfors", "given": "Johan", "initials": "J", "orcid": "0000-0003-1372-4262", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/dbc162955acf4b2ba0b4dade363d4592.json"}}, {"family": "Brandt", "given": "Lena", "initials": "L"}], "type": "journal article", "published": "2022-01-00", "journal": {"title": "Pharmacoepidemiol Drug Saf", "issn": "1099-1557", "volume": "31", "issue": "1", "pages": "28-36", "issn-l": null}, "abstract": "When defining exposure to pharmacological treatments in pharmacoepidemiology, register data often do not provide information regarding if a pharmacological treatment is a switch or an add-on. This study aims to compare two methods defining switching and add-on therapies and their impact on exposure-outcome associations. Additionally, to guide bias reduction, it aims to describe how the methods relate to immortal time bias and selection bias.\n\nCohort study using Swedish population-based health registers to identify antidepressant (AD) prescriptions as exposures while hospitalizations for psychiatric reasons were used as an empirical outcome example. The first method for exposure definition used conditioning on future exposure (FE), the second used the concept of uncertain exposure (UE). To estimate associations between outcome and exposure categories \"Use of one AD,\" \"Use of two or more ADs\", and \"UE\" compared to \"Unexposed,\" hazard ratios (HRs) and 95% confidence intervals were estimated using Cox regression adjusted for age and sex.\n\nUsing the UE method, 7.2% of time periods were classified as \"UE\" with a notable proportion of psychiatric hospitalizations (7.7%) occurring during this time, while when using the FE method these hospitalizations were distributed over unexposed time and AD use time. The FE method resulted in slightly higher associations than the UE method. The highest HR was found during \"UE\": HR (95% CI) 5.54 (5.06-6.07).\n\nThis study suggests that to reduce the potential immortal time bias, selection bias, and exposure misclassification inherent to the FE method, the UE method could be used for identifying switching and add-on therapies. If not used as a main exposure definition, the UE method may be used to investigate the impact of UE time in a sensitivity analysis.", "doi": "10.1002/pds.5363", "pmid": "34558772", "labels": [], "xrefs": [], "notes": [], "created": "2026-09-23T13:32:42.604Z", "modified": "2026-09-23T13:32:42.634Z"}, {"entity": "publication", "iuid": "3baa9822765d449db7e55de3a73c32d9", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3baa9822765d449db7e55de3a73c32d9.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3baa9822765d449db7e55de3a73c32d9"}}, "title": "Methods for constructing treatment episodes and impact on exposure-outcome associations.", "authors": [{"family": "Pazzagli", "given": "Laura", "initials": "L", "orcid": "0000-0002-1908-6073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1238a7c151343afb5daf301a63b63c2.json"}}, {"family": "Brandt", "given": "Lena", "initials": "L"}, {"family": "Linder", "given": "Marie", "initials": "M"}, {"family": "Myers", "given": "David", "initials": "D"}, {"family": "Mavros", "given": "Panagiotis", "initials": "P"}, {"family": "Andersen", "given": "Morten", "initials": "M"}, {"family": "Bahmanyar", "given": "Shahram", "initials": "S"}], "type": "comparative study", "published": "2020-02-00", "journal": {"title": "European journal of clinical pharmacology", "issn": "1432-1041", "volume": "76", "issue": "2", "pages": "267-275", "issn-l": "0031-6970"}, "abstract": "To assess the impact on exposure time and outcome misclassifications, and consequent impact on exposure-outcome associations from treatment episode construction. We investigated the dosage assumptions of 1 unit per day, and 1 DDD per day, versus actual prescribed dosage under different handling of gaps and overlaps of prescriptions.\n\nData on mirtazapine and citalopram exposure (years 2006-2014) from the Swedish Prescribed Drug register were used. Via a within individuals design we compared method A, based on actual dosage, with methods B and C based on 1 unit of drug per day and 1 DDD per day assumptions, respectively, including consideration of gaps and overlaps. Four outcomes were used, hospitalizations and outpatient visits for all and for psychiatric causes.\n\nRelative to method A, both alternative methods lead to misclassification of exposure time. With regard to outcome misclassifications, method B overestimates the effect of the exposure on the outcome in 77% and 100% of exposure definition comparisons for mirtazapine and citalopram respectively, while 23% of the comparisons for mirtazapine results in underestimation of exposure-outcome associations. Conversely, treatment episodes based on DDD (method C) result in underestimation of the exposure-outcome association in 100% and 87.5% of exposure definition comparisons for mirtazapine and citalopram respectively, while 12.5% of the comparisons for citalopram results in overestimation of the exposure-outcome associations.\n\nThe study provides results that have consistent clinical relevance. We have showed that a non-accurate construction of exposure time may lead to errors on outcome detection during exposed time, and consequently affect conclusions on safety or efficacy profile of a treatment.", "doi": "10.1007/s00228-019-02780-4", "pmid": "31758215", "labels": [], "xrefs": [{"db": "pii", "key": "10.1007/s00228-019-02780-4"}], "notes": [], "created": "2026-09-23T10:07:19.170Z", "modified": "2026-09-23T10:45:22.818Z"}]}