Evidence map›Paper›PMID 11735651›Full record

ReviewDrug safety2001

Therapeutic drug monitoring databases for postmarketing surveillance of drug-drug interactions.

M Gex-Fabry, A E Balant-Gorgia, L P Balant

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drug safety, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 35% of its field
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

5 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
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

3 authors at 1 institution in 2 countries.

M Gex-FabryClinical Research Unit, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland. gexfabry@cmu.unige.ch
A E Balant-Gorgia
L P Balant
Geneva College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-drug interactions can be associated with patient morbidity due to either increased toxicity or a potentially ineffective concentration. Because interactions cannot always be anticipated during drug development and actual patients receiving a drug for therapeutic use often differ from those included in clinical trials, postmarketing surveillance is essential. Therapeutic drug monitoring (TDM) databases offer a unique opportunity in this respect. Prerequisites for TDM databases to provide valid information in a pharmacoepidemiological perspective include the following: precise description of exposure to the potentially interacting drugs; measurement of parent compound and active metabolites through accurate and precise analytical techniques; documentation of relevant patient characteristics that may act as confounding factors (e.g. gender, age, smoking habits); repeated assessments over time if possible; and sound pharmacokinetic framework for data selection, analysis and interpretation. The contribution of TDM to the documentation of drug-drug interactions takes advantage of different possible study designs, discussed on the basis of recently published studies. The single case report plays an important role as an alert signal. It is illustrated for a patient on long-term treatment, who displayed an unexpectedly high clozapine concentration after the introduction of ciprofloxacin comedication. The prospective on and off comedication panel study shows advantages in terms of carefully selected inclusion criteria and control of treatment modalities. A study of the thioridazine-fluvoxamine interaction is presented, with patients followed on thioridazine monotherapy, after introduction of fluvoxamine and after its discontinuation. The main advantage of the retrospective large-scale TDM database screen is representativeness of patients actually treated, whereas drawbacks are related to quality of data and suitability for valid interpretation. Such an approach is illustrated by a review of data collected over 10 years of routine TDM that allowed documenting induction of nortriptyline metabolism by carbamazepine and inhibition by several phenothiazines. Finally, population pharmacokinetics is well suited to observational data collected for TDM purpose, provided quality is ascertained. Focus is placed on interindividual variability and relationship between pharmacokinetic parameters and patient characteristics, including comedication. The population approach is discussed with respect to a study that documented a 32% increase of haloperidol clearance associated with anticonvulsant comedication, in addition to effects of age and bodyweight. Among factors to consider for improved effectiveness in the use of TDM databases for postmarketing surveillance of drug-drug interactions, integration of efficacy and safety data in future studies and communication of expert recommendations to prescribing physicians are essential.

Indexed as

Databases, FactualDrug InteractionsProduct Surveillance, PostmarketingHumansPharmacokinetics

Identifiers

PMID11735651
OpenAlexW2077147953

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.