Materials and Methods
Study design and population – A workshop (“AIT prescription
workshop”, AIT-WS) has been organized with 10GP + 11AS at “Ospedale S.
Pertini” (Rome, Italy) and with 18GP + 7AS at “Ospedale S. Maria degli
Angeli” (Pordenone, Italy). The participants were recruited among those
physicians collaborating with each center on a regular base concerning
patients suffering from allergic diseases. Each workshop consisted of
the following three phases: a) educational training; b) decision taking
on clinical cases; and c) feedback survey.
Educational training – During the first part of the AIT-WS,
the target, nature and methodology of the diagnostic tools (i.e.
questionnaires, SPT, CRD, eDiary) were presented in comprehensive
lectures. In detail, three lectures explained the general concepts,
specific methodologies and clinical interpretation of the diagnostic
tools. A fourth lecture was focused on the procedures for the following
workshop module involving clinical cases.
Clinical cases – Among the @IT.2020 pilot study population
(n=200), twenty clinical index cases (10 cases for each center) were
selected in order to reproduce the local epidemiological
scenario6 and to provide the widest spectrum of
allergen(s) among the patients affected by moderate-to-severe SAR[Table E1] . The @IT.2020 pilot study population (n=200) has
been described in detail elsewhere23. Briefly, 101
children (“Ospedale Sandro Pertini”, Rome), and 99 adults (“Ospedale
S.Maria degli Angeli”, Pordenone) underwent a complete diagnostic
allergy work-up, including a detailed assessment of the retrospective
clinical history, skin prick testing (SPT), blood drawing for IgE
determination against allergenic extracts and molecules, a prospective
collection of clinical data via mobile phone application and an
allergen-specific nasal provocation test (NAPT) with the extract of the
AIT-candidate pollen(s) for a subgroup. Among the selected clinical
cases, NAPT data were available for 18 of the 20 patients (90%). During
the second part of AIT-WS, doctors were asked to express their
therapeutic decision concerning their respective 10 clinical index
cases.
Therapeutic Decision Taking - Each participating doctor filled
a questionnaire reporting his/her own hypothetical AIT decisions on the
base of the primary data progressively added. The first decision had to
be taken based on the retrospective clinical history and SPT results. An
independent second decision was then asked involving the clinical
history, SPT and CRD results. Finally, the results of each patient´s
symptom monitoring via eDiary during the past pollen season plus pollen
counts were shown and doctors decided again on the hypothetical
prescription of AIT for every patient.
Feedback survey– Finally, the doctors filled a questionnaire
not only on the impact of each given diagnostic tool and its perceived
benefits, but also on their role in the doctor´s hypothetical AIT
prescription process. In addition, participants were asked to express
their satisfaction level on the entire AIT-WS (tutorial, clinical cases
and feedback survey) in terms of content and general organization[Figure E1] .
Algorithm for a potential clinical decision support system
(CDSS) for pollen allergy– The @IT.2020-DSS tools are based on
clinical data progressively considered in three steps: 1) clinical
history and SPT (and/or serum sIgE) to allergen extracts; 2) IgE assays
to pollen-derived molecular components (component resolved diagnostics,
CRD); 3) electronic clinical diary (eDiary)24. In the
first step, a list of potentially relevant allergens are selected
considering the period of allergic symptoms reported by the patient
(clinical history, seasonality of AR symptoms) and the SPT reactions
(“traditional” diagnosis). In the second step, the list of allergens
previously selected is restricted to those confirmed by IgE
sensitization to their respective major allergenic proteins (Cup a 1 for
cypress, Phl p 1 and/or Phl p 5 for grass, Bet v 1 for birch, Ole e 1
for Olive, Amb a 1 for ragweed, Art v 1 for mugwort, and Alt a 1 for
Alternaria). Finally, the list of allergens considered after the second
step (anamnesis+SPT+CRD) is further restricted to those whose
pollination period, identified by the local aerobiologist, corresponded
to moderate-to-severe and/or persistent allergic rhinoconjunctivitis
symptoms prospectively registered by the patient during the same period.
The three steps of the @IT2020-DSS algorithm can therefore be
represented by a “pyramid” scheme for each allergen [Figure
1a ] generating a precision “target” when combined [Figure
1b ]. However, the algorithm does not exclude any obtained result
based on the described exclusion scheme. In the rare case of positive
test results occurring at an advanced stage (e.g. positive IgE to a
major molecule of an allergenic source which had been previously
excluded on the base of a negative SPT result), the respective allergen
is being considered potentially relevant for the next step of the
algorithm.
Statistics- Data were summarized as numbers (n) and frequencies
(%) if they were categorical and as mean and standard deviation (SD) if
quantitative. Percentages of correct hypothetical AIT prescription at
each step and for each medical category were computed, taking as
comparison reference, for each examined case, the most frequent AIT
hypothetical prescription of allergen immunotherapy among allergy
specialists at the final stage of CDSS (gold standard). Chi squared
test, when conditions were respected or Fisher exact test was used to
evaluate the association of categorical data between AS and GP groups.
McNemar’s test was used to compare difference of frequency within each
group. A p-value < .05 was considered statistically
significant. Statistical analyses were performed with R Core Team
(2014), version 3.2.3.