“Off-label” (OL) refers to the use of a drug for indications and/or conditions different from those for which it was licensed.1 

However, off-label drug use (OLDU) is not necessarily incorrect. The Food and Drug Administration stated that “Good medical practice and the best interests of the patient require that physicians use legally available drugs ... according to their best knowledge and judgment.”2  Prescribing OL drugs is a common practice. Because of limited pharmacologic research in children, it is more frequent in pediatric care,3  particularly in hospitalized children.4 

Adverse drug reactions (ADRs)5  occur with OLDU at frequencies between 23% and 60%, depending on the type of drug and the group of patients considered6 ; however, information on this topic is limited, particularly in pediatrics, and in many cases the detection of ADRs is based on different definitions and methodologies.7,8 

A standardized procedure for searching ADRs can achieve more accurate results.9 

There is an urgent need to better understand OLDU, particularly in Latin America, where economic, social, and cultural reasons may guide different drug choices from developed countries and possibly tip the balance toward more OL prescribing in pediatrics.

We estimate the prevalence of OLDU and of ADRs in hospitalized children.

This was a cross-sectional study that included patients aged <18 years, hospitalized at a pediatric tertiary care hospital, during 2017. We include one whole year to avoid epidemiological bias related to different cause of hospitalization in children across the year (ie, respiratory infection in winter). Data were collected from clinical charts selected by simple random sampling. Because OLDU is higher in ICU population,6  we excluded them focusing on a more homogeneous population of noncritically ill children. When a clinical chart presented >one hospitalization during 2017, the last 1 was considered.

Each chart was independently evaluated by two pediatricians. In cases of disagreement, a third researcher resolved discrepancies. Age, reason for admission, length of stay, and all prescriptions (and their indications) were analyzed. The presence of OL drug prescriptions and the number of OL drugs were determined. To identify OL drugs, the Argentine national drug handbook was used.10 

ADRs were systematically investigated by using a trigger tool designed to detect them.9  Upon the identification of 1 trigger, the clinical chart was searched for the presence and magnitude of ADR. Then, the Liverpool Adverse Drug Reaction Causality Assessment Tool (LCAT) was used, which includes an algorithm for recognizing the association between an ADR and a particular drug.11 

Outcome variables were as follows:

  • OLDU: a drug used for indications and/or in conditions different from those authorized by the regulatory agency (eg, different indication, patient age, dose, and/or route of administration);2  and

  • ADR: any response to a drug that is noxious, unintended, and occurs at the usual doses prescribed for prophylaxis, diagnosis, or treatment.5 

For an expected ADR rate of 1.6% ± 1.2%, ≥403 clinical records were required (confidence level, 95%).12  This number exceeds what is needed to assess the prevalence of OLDU, usually >20%.13 

Descriptive analysis included percentages (95% confidence interval [CI]), and means (SD) or medians (interquartile range) (according to distribution, assessed by Kolmogorov–Smirnov). Differences in age and days of hospitalization according to OLDU were assessed (Mann–Whitney). Interobserver agreement was evaluated by the κ coefficient. Difference in the prevalence of ADRs between patients with OLDU and without was evaluated by χ2, and odds ratios were calculated. A significance level of P < .05 was adopted.

The study was approved by the Research Ethics Committee of the institution and registered in the National Registry of Research (IS002156).

A total of 412 clinical charts were randomly selected from the 10 334 hospitalizations in 2017. The most common reason for hospitalization was respiratory or infectious causes (58%) (Table 1).

TABLE 1

Patient Demographic Characteristics, According to OLDU

OL (n = 238; 57.8%)Non-OL (n = 174; 42.2%)TotalP
Age, y, median (IQR) 1.2 (0.4–6.3) 3.9 (1.3–9.7) 2.2 (0.6–7.8) <.001a 
Sex, male (95% CI) 60.2 (53.7–66.3) 39.8 (33.6–46.3) 54.9 (50.3–59.6) NSb 
Length of stay, d, median (IQR) 5 (4–7) 5 (4–8) 5 (4–8) NSa 
Reason for hospitalization, median (IQR)     
 Respiratory, infectious 57.4 (51.1–63.5) 42.5 (36.6–48.8) 58.7 (53.9–63.3) NSb 
(n = 139) (n = 103) 
 Surgical pathology 69.1 (59.9–76.9) 30.9 (23.1–40.1) 26.7 (22.6–31.1) .007b 
(n = 76) (n = 34) 
 Others 38.3 (27.1–50.9) 61.6 (49.1–72.9) 14.6 (11.5–22.4) .001b 
(n = 23) (n = 37) 
OL (n = 238; 57.8%)Non-OL (n = 174; 42.2%)TotalP
Age, y, median (IQR) 1.2 (0.4–6.3) 3.9 (1.3–9.7) 2.2 (0.6–7.8) <.001a 
Sex, male (95% CI) 60.2 (53.7–66.3) 39.8 (33.6–46.3) 54.9 (50.3–59.6) NSb 
Length of stay, d, median (IQR) 5 (4–7) 5 (4–8) 5 (4–8) NSa 
Reason for hospitalization, median (IQR)     
 Respiratory, infectious 57.4 (51.1–63.5) 42.5 (36.6–48.8) 58.7 (53.9–63.3) NSb 
(n = 139) (n = 103) 
 Surgical pathology 69.1 (59.9–76.9) 30.9 (23.1–40.1) 26.7 (22.6–31.1) .007b 
(n = 76) (n = 34) 
 Others 38.3 (27.1–50.9) 61.6 (49.1–72.9) 14.6 (11.5–22.4) .001b 
(n = 23) (n = 37) 

IQR< interquartile range; NS, not significant.

a

Mann–Whitney.

b

χ2.

There were 1353 prescriptions, of which 284 were OL (21%; 95% CI: 19–23); 782 (57.8%; 95% CI: 52.9–62.4) of the patients received ≥1 OL drug.

There were no significant differences between groups (OLDU versus non-OLDU) regarding sex and length of stay. Those with OLDU were significant younger (Table 1).

Use outside the authorized age range was the most common reason for considering a drug OL (159 of 284; 55.9%), followed by use outside of dosage recommendations (105 of 284; 36.9%). The most common drug used OL per dosage was salbutamol and by age was tramadol (Table 2). Use of salbutamol was more frequent (81%) during cold months (April through September).

TABLE 2

OL Drug Prescriptions, by Reason

Reason for OL Usen (%)Drugn (%)
Outside approved age range 159 (55.9) Tramadol 81 (51) 
  Clarithromycin 11 (6.9) 
  Co-trimoxazole 11 (6.9) 
  Other 56 (35.2) 
Outside dosage recommendations (dose, frequency, wt) 105 (36.9) Salbutamol 102 (97.1) 
 — Other 3 (2.9) 
Administration by an alternative route 14 (5) — — 
Formulation not approved for use in children 3 (1.1) — — 
Prescribed for off‐label indication 3 (1.1) — — 
Total 284 — — 
Reason for OL Usen (%)Drugn (%)
Outside approved age range 159 (55.9) Tramadol 81 (51) 
  Clarithromycin 11 (6.9) 
  Co-trimoxazole 11 (6.9) 
  Other 56 (35.2) 
Outside dosage recommendations (dose, frequency, wt) 105 (36.9) Salbutamol 102 (97.1) 
 — Other 3 (2.9) 
Administration by an alternative route 14 (5) — — 
Formulation not approved for use in children 3 (1.1) — — 
Prescribed for off‐label indication 3 (1.1) — — 
Total 284 — — 

—, not applicable.

Using the ADR detection tool, 20 triggers were identified, leading to 5 ADRs. The prevalence of ADRs was 1.2% (95% CI: 0.5–2.8). Only 1 ADR was categorized as “probable” (LCAT) in the OLDU group.

The prevalence of ADRs did not differ significantly between those who received OL drugs and those who did not (0.35% vs 0.37%; odds ratio = 0.9; 95% CI: 0.1–8.3; P = .9).

The interobserver agreement (κ) was 0.88 for OLDU, 0.78 for triggers, and 0.91 for ADR.

In our study, we provide updated information on a subject that must be constantly monitored, presenting data on a region, Latin America, where this information is scarce. We found that 57.8% of the patients received ≥1 OL drug. Our results coincided with information showing that in the European Union, nearly half of the hospitalized patients received an OL drug.14  The use of OL drugs in hospitalized patients reveals a prevalence ranging between 14% and 63% that tends to increase with younger patients.6 

In our study, the most frequent reason for OLDU was age; >50% of the OL conditions were related to age, and patients who received OL drugs were significantly younger than those who did not. Yackey et al15  report that OLDU was 44.8% in infants and decreased to 21.4% in adolescents. Lee et al16  also identified age as the main cause of OLDU (≤73.5%), but they included ICU and emergency department patients.

Regarding OLDU based on age, tramadol was the most frequently OL prescribed drug (51%), mostly as an analgesic in postsurgical patients. The use of this drug in children is controversial because isolated cases of respiratory depression have been described.17,18  None of the patients in our analysis had respiratory or cardiovascular depression. However, the Food and Drug Administration contraindicates the use of tramadol <12 years of age and does not recommend its use in obese children between 12 and 18 years of age.18,19 

Regarding dose related OLDU, almost all prescriptions were for salbutamol because the frequency of administration was every 4 hours, higher than that indicated on the label. In a retrospective study including >6000 prescriptions, 852 doses of salbutamol were observed, all of which were considered OL based on dose frequency; however, no significant ADRs were found.20 

We identified 5 ADRs, only 1 related to OLDU, and all were expected, as detailed on the drugs’ respective labels. Although the low prevalence of ADR may correspond to underreporting by physicians, similar results were observed in a retrospective cohort including 10 years of records, in which the reported incidence of ADR was 1.6%, and almost 90% of cases were reported by pharmacists.12  Similar results were observed in a study (n = 6000) with 26% OLDU; in that study, 40 ADRs were detected, only 5 of which were associated with an OLDU.21 

The high prevalence of OLDU explained by age highlights the need to encourage high-quality pharmacologic research in pediatrics. Both the United States and European Union established specific regulations and lead a global effort to overcome this inequity.22 

As a consequence of the still-present gap in pharmacologic research in pediatrics, lower-quality evidence is frequently used. The particular case of salbutamol is a good example in which a noticeable difference can be observed between what is detailed in the label and the international guidelines for asthma in pediatric patients.23,24  Moreover, in our study, despite OL use, all drugs were used with the support of local guidelines. Research aimed at evaluating the safety and efficacy of drugs used in pediatric populations is essential because there are diseases and conditions specific to this group; children should not be considered as small adults, because unnecessary risks may be incurred.25 

Our work is limited by the weaknesses inherent to studies based on clinical records in terms of the potential for bias. However, the chosen variables correspond to concrete data from clinical records and medical prescriptions.

In contrast, our study shows considerable methodologic strengths. Our study is original in its use of a validated trigger-based tool, which has proven to be superior to reports and simple reviews of medical records for the detection of ADRs.26  We also use a validated tool (LCAT) for recognizing the association between an ADR and a particular drug.11  Furthermore, when only patients hospitalized in a general ward (excluding ICU) are included, the internal validity is increased. Although we found no association between OLDU and ADRs (probably because lack of power for this analysis), the OLDU involves risks beyond ADRs, such as lack of efficacy,27  increased bacterial resistance,28  increased costs, and long-term adverse events.29  It should be remembered that the only way to provide safe and effective medicines for children is through research in this population.30 

We found a high prevalence of OLDU in our population, suggesting that pediatric-specific medications are scarce and that regulatory agencies evaluations of medications suitable for pediatric use are outdated and lag behind actual pediatric clinical practice. Efforts should be increased to cover this knowledge gap that puts sick children at risk.

We thank Dr Facundo Garcia-Bournissen, Head of the Division of Paediatric Clinical Pharmacology, Schulich School of Medicine and Dentistry, Western University (Ontario, Canada), for the critical review of our article.

Drs Ferreira and Torres conceptualized and designed the study and drafted the initial manuscript; Drs Dominguez, Ossorio, and Ferrero collected the data and reviewed and revised the manuscript; Dr Ferrero conducted the analyses and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted.

FUNDING: This work was supported by a grant: “Dr Abraam Sonis,” Ministerio de Salud, Argentina, 2018 (NRU3118).

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflict of interest to disclose

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.