DISEASE

The invention provides a method and device making it possible to identify the activity of an autoinflammatory disease in a patient.

The hereditary recurrent fever syndromes (HRFs) are rare Mendelian autoinflammatory diseases (AID) characterized by flares of fevers associated with acute inflammation affecting various tissues without evidence of an underlying cause. With the exception of familial Mediterranean fever (FMF) these diseases are very rare with estimated prevalence of less than two per million.

These autoinflammatory diseases (AIDs) are caused by primary dysfunction of the innate immune system. Proteins that are mutated in AIDs mediate the regulation of NFkappaB activation, cell apoptosis, and IL-1 beta secretion through cross-regulated and sometimes common signaling pathways. These conditions are characterized by recurrent attacks of fever, abdominal pain, arthritis, and cutaneous signs; these symptoms sometimes overlap, obscuring diagnosis. The

The four main diseases by date of description and frequency are: FMF, mevalonate kinase deficiency (MKD), tumor necrosis factor receptor (TNF)- associated periodic syndrome (TRAPS), and cryopyrin-associated periodic syndromes (CAPS). Recent advances in the molecular pathogenesis of HRFs have led to a better understanding of the common pathways and mediators of apoptosis, inflammation and cytokine signaling involved in their pathogenesis and have radically improved diagnosis and therapies (Touitou et Kone-Paut, Autoinflammatory diseases. Best Pract Res Clin Rheumatol 2008;22(5):81 1 -29; Hashkes et ai, Ann Intern Med 2012;157(8):533-41 )..

With the increasing potential for targeted therapies in AID, there is the need for validated assessment tools which can be used to evaluate the level of disease activity and response to therapy and thus to assess drug efficacy in standardize assessments across trials (Singh et al., Arthritis Rheum 2006;55(3):348-52; Hoffman et al., Arthritis Rheum 2008;58(8):2443-52; Lachmann et al., N Engl J Med 2009;360(23):2416-25; Gillespie et ai, J Inflamm Res 2010;3:1 -8)

The lack of such standardized and validated measures for assessing disease activity for either adults or children with AID, has seriously hampered assessment of current treatments and comparison of treatment responses in the different HRFs.

It is therefore important to design a method that would help the physician to determine whether the AID is active in the patient or whether it is controlled by the drugs that are being taken.

An international collaboration, initiated by Assistance Publique-Hopitaux de Paris (APHP) in association with the Paediatric Rheumatology International Trials Organization (PRINTO at www.printo.it) and supported by the EUROFEVER and EUROTRAPS networks has already designed the content and preliminary scoring of this Auto-Inflammatory Disease Activity Index (AIDAI) using a single format disease adapted patient diary for the four major HRFs (Piram et al., Ann Rheum Dis 201 1 ;70(2):309-14).

Piram et al. {op. cit) thus described the design of various Indexes that are each specific for one of the four main diseases as indicated above. For each index, the patients had to daily give a note for some items associated to their disease (See Table 1 ). Fever was noted as 0 (absent) or 1 (present) whereas the other disease-specific variables were to be scored from 0 to 3 according to their severity (0=absent, 1 =minor, 2=mild, 3=severe).

CAPS, cryopyrin-associated periodic syndromes; FMF, familial Mediterranean fever; MKD, mevalonate kinase deficiency; TRAPS, TNF receptor-1 -associated periodic syndrome.

Table 1 : Variables selected in Piram et al. (op. cit.) to assess disease activity A final score was generated by calculating the sum of the scores for all variables divided by the number of days over which the diary was completed. Scores could vary from 0 to 16 (0-13 in CAPS). Piram et al clearly indicated that the scoring system is a preliminary system which measures disease activity for each of the four hereditary autoinflammatory disorders. Furthermore, a validation phase was to be made (in order to determine the threshold above which each disease is considered to be active).

The purpose of the present invention is to provide a validated score that could be generic to detect activity for all AIDs, and would be easier to obtain. Indeed, it may be difficult for the patient to grade the different variables associated to the disease from 0 to 3, in particular for children to discriminate between a mild and a severe item. This score has been validated through expertise of the physicians having assessed the disease activity of the patients.

A new score and method for detecting activity of an AID is thus provided, where some items are scored every day by the patient and a total score is then obtained. Depending on the amount of this score, said AID is then considered as active or not. This test and method is thus useful, in particular, to adapt the patient's treatment if it proves not effective enough.

In particular, the new AIDAI score uses a simplified scoring system. The patient is requested to score multiple items associated to the AID disease, but each item is dichotomized (i.e. is scored 0 (absence of the sign) or 1 (presence of the sign)) rather than from 0 to 3 as in the previously described index. Surprisingly, reducing the granularity of the scoring didn't lower the performance of the test, as determined by statistical analysis, while allowing for greater simplicity in the AIDAI completion. The invention thus relates to a method for determining the activity of an auto-inflammatory disease in a patient, comprising the steps of:

a) Having said patient daily report, during a one-month period, the status of at least 5 dichotomous items, wherein each item corresponds to a physiological observation

b) Recovering said reports from said patient c) Allocating the value "1 " to each item which has received a positive completion by said patient (presence of the item) and the value "0" to each item which has received a negative completion by said patient (absence of the item)

d) Combining, in a mathematical function, all the values obtained in step c) for each days of a consecutive period of one month in order to obtain an end value.

This method is preferably performed by the physician/clinician. The method may also comprise the step of analyzing said end value of said mathematical function in order to determine the presence of active AID in said patient. In particular, it is possible to determine that said auto-inflammatory disease is active in said patient if said end-value is higher than a predetermined cut-off.

In a preferred embodiment, said auto-inflammatory disease is a major hereditary recurrent fever syndrome.

In another embodiment, the invention relates to a method for determining the activity of an auto-inflammatory disease in a patient, comprising the steps of: a) Providing a one-month diary to said patient, wherein said diary comprises an emplacement for each day of the month and wherein each daily emplacement of said diary comprises a [the same] list of at least 5 dichotomous items, wherein each item corresponds to a physiological observation

b) Recovering said diary from said patient, wherein said diary has been completed daily by said patient for a consecutive period of one month c) Allocating the value "1 " to each item which has received a positive completion by said patient (presence of the item) and the value "0" to each item which has received a negative completion by said patient (absence of the item)

d) Combining all values obtained in step c) in a mathematical function in order to obtain an end value

e) Determining that said auto-inflammatory disease is active in said patient if said end-value is higher than a predetermined cut-off, wherein said auto-inflammatory disease is a major hereditary recurrent fever syndrome. As used herein, an autoinflammatory disease is intended to mean a disease in which the innate immune system causes inflammation. These diseases are relatively new diseases, which are characterized by intense episodes of inflammation that result in such symptoms as fever, rash, or joint swelling.

One can cite major hereditary recurrent fever syndromes (FMF, TRAPS,

MKD, CAPS) as described above, as well as Neonatal Onset Multisystem Inflammatory Disease (NOMID or CINCA), Deficiency of the lnterleukin-1 Receptor Antagonist (DIRA) or Behget's Disease. Autoinflammatory diseases also encompass Blau, Majeed, and PFAPA syndromes. A review of these diseases can be found in Grateau (Acta Clin Belg. 2006 Sep-Oct; 61 (5):264-9).

By "daily reporting the status of a dichotomous item, wherein said item corresponds to a physiological observation", one intends to indicate that the patient will note whether or not said physiological condition has been present or absent on that specific day of report. This can be performed, for instance, by checking a box corresponding to both said item and said specific day. Such box crossing would then amount to a positive completion.

Step b) of the method consists in recovering the daily reports from said patient. In a specific embodiment, said recovery is made directly by said patient to said physician/clinician.

In another embodiment, step a) is performed by the patient filling out an electronic form, in particular on a patient's device, and the recovery of step b) consists in sending the filled form to a server that can be consulted by the physician/clinician. In this embodiment, an "electronic form" relates to a form that can be completed electronically by the patient (form user) and for which the data is transmitted into a database or another application after completion.

Said electronic form can be accessed through a dedicated website to which the patient connects, preferably with an identifier and password. Step b) (transmission of the data) is then performed when the patient validates the form. In this embodiment, one can design the website such as to provide a blank electronic form to said patient each day, until it is validated. In this embodiment, it is possible and known in the art to automatically remind the patient to fill the electronic form every day (such as by sending a daily automatic email, or a Short Message on the device of the patient (SMS)). It is also possible to send such reminders when the patient has not logged in or validated the form for one day. The server at the receiving end can perform a daily check for completion of the form for the patient and send a reminder in case the form has not been completed during a specified period of time.

In another embodiment, said electronic form is presented to the patient on a phone (smartphone) through a specifically designed application present on said phone. Said application may also contain other features such as opening a pop-up window every day or being linked to the calendar of said phone's user in order to remind the patient to fill-out the form. The application may also present the items one at a time to the user (one item is presented after the previous one has been completed) and send the data once (perform step b)) after the last item has been completed, and the patient has validated the data entry, and when network (such as wireless network, GSM, 3G or wifi) is available.

When an electronic form is used, said entered data is sent to a distant server, according to method known in the art. It is preferred when communication between the distant server and the patient's device (either computer or phone) is encrypted.

"Combining, in a mathematical function, all the values obtained in step c) for each days of a consecutive period of one month in order to obtain an end value" is intended to mean that, after all values (1 or 0) have been generated for all items for all days of the one-month period, these values are then introduced in a mathematical function. In a preferred embodiment, said mathematical function is the algebraic sum of the values obtained in c). In this embodiment, all values are given the same weight in said function.

In another embodiment, one or more values are given a greater or lesser weight in the mathematical function. One could use some coefficient between some values linked to a particular item (for instance, fever could be given a higher (or lower) weight, which would be translated by allocating a coefficient higher than 1 (or lower than 1 ) for all values obtained for the fever item before adding these values to the other ones). In this embodiment, the modified weight given to some values is not necessarily identical (i.e. some values may be given more weight than others, or some values may be given an increased weight, whereas other values may be given a decreased weight). Statistical analysis could help determine the proper weight for each value. In the preferred embodiment, though, all values are given the same weight (i.e. the mathematical function is the algebraic sum of all values).

When the reporting of step b) is performed through electronic/network means (either when the patient uses a computer or a smartphone to enter the data), the data is then received on a remote server (remote from the source). Allocation of the 0/1 value of step c) and calculation of the end value in step d) can thus be performed automatically, and said end value (calculated daily on a one month rolling) can be sent to the physician (by any method known in the art such as by email). The physician can thus determine daily the status of the activity of the disease for said patient.

In a preferred embodiment, said items reported by the patient are chosen in the group consisting of a) Fever >38°C, b) Overall symptoms of the disease, c) Abdominal pain, d) Nausea/vomiting, e) Diarrhea, f) Headaches, g) Chest pain, h) Painful nodes, i) Arthralgia or Myalgia, j) Swelling of the joints, k) Eyes manifestations, I) Skin rash.

Overall symptoms of the disease are symptoms that are not listed apart in the group specified above. In these kinds of diseases, the patient can recognize a burst of the disease (such as an increased fatigue, irritability and the like). The patient can thus indicate whether he/she feels that there was such a disease burst on that specific day (this is particularly true for TRAPS). In a specific embodiment, said patient shall daily report, during a one-month period, the status of exactly 5 dichotomous items.

In this embodiment, said group of five items shall preferably be (fever > 38°C / headaches / arthralgia or myalgia / eyes manifestations / skin rash). In another specific embodiment, said patient shall daily report, during a one- month period, the status of exactly 6 dichotomous items.

In this embodiment, said group of five items shall preferably be chosen in the group consisting of (fever >38°C / abdominal pain / chest pain / arthralgia or myalgia / swelling of the joints / skin rash), (fever >38°C / abdominal pain / nausea- vomiting / diarrhea / painful nodes / arthralgia or myalgia) and (fever >38°C / overall symptoms / abdominal pain / arthralgia or myalgia / eyes manifestations / skin rash).

In another embodiment, said patient shall daily report, during a one-month period, the status of exactly 7, 8, 9, 10 or 1 1 items.

In the preferred embodiment, said patient shall daily report, during a one- month period, the status of exactly the twelve dichotomous items as indicated above as a) to I).

In another embodiment, said patient may also report other information, such as the intake of pain killers, the number of days out of school or work, any disturbance of the social life and the like.

The patient may also report any information related to an item, which may also help to discard the report of said item on a particular day, or a period of time. For instance, in case the patient has had the flu, the fever item during this period may be discarded. Any nausea/vomiting episodes may also be discarded if the patient has had gastrointestinal disease. Generally, the patient can recognize when a symptom is linked to activity of the disease or when it is linked to another disease. Preferably, the patient shall thus report only the symptoms linked to the AID. In practice, and in order to be sure not to miss any symptom, the patient is requested to report all information, and indicate, in an open box, any information that would help to discard or not the reported symptom (such as presence of another punctual disease).

In a preferred embodiment, said auto-inflammatory disease is a hereditary recurrent fever syndrome (HRFs), in particular chosen in the group consisting of familial Mediterranean fever (FMF), mevalonate kinase deficiency (MKD), tumor necrosis factor receptor-associated periodic syndrome (TRAPS), and cryopyrin- associated periodic syndromes (CAPS). In a preferred embodiment, said mathematical function is the algebraic sum of the values of step c) and the predetermined cut-off is 9. This means that when the sum of said values of step c) is above or equal to 9, said AID is active; when the sum of said values of step c) is lower than 9, said AID is not active.

The invention also covers a form to be filled by a patient, which comprises a list of at least 5 dichotomous items, wherein each item corresponds to a physiological condition that can be experienced by said patient, and a box to be checked by said patient for each item when said patient experiences said physiological condition.

In a specific embodiment, said form is an electronic form. In another embodiment, said form is a physical form, such as a paper sheet on which are printed the elements as mentioned above.

In another embodiment, said form also presents a list of days and wherein each of said at least 5 dichotomous items is to be reported on each day. This describes in particular a diary that would be given to a patient for filling for a one- month period, wherein said patient would have a box (to check or not) for each item for each day of this one-month period.

In a preferred embodiment, said form comprises five items. In another embodiment, said form comprises six items. In another embodiment, said form comprises exactly 7, 8, 9, 10 or 1 1 items. In a preferred embodiment, said form contains 12 items.

In a preferred embodiment, said items are chosen in the group consisting of a) Fever >38°C, b) Overall symptoms of the disease, c) Abdominal pain, d) Nausea/vomiting, e) Diarrhea, f) Headaches, g) Chest pain, h) Painful nodes, i) Arthralgia or Myalgia, j) Swelling of the joints, k) Eyes manifestations, I) Skin rash.

In an embodiment, said form comprises an open box that can be filled by the patient with free text in order to report any element of interest for the physician/clinician.

Description of the Figures

Figure 1 : Table 3: Scores of the AIDAI tool with items dichotomized as 0/1 applied in 98 patients with a HRF diagnosis. Data refer to a diary completed by the patients/parents in the month preceding the visit. Data are means ± standard deviation. FMF: familial Mediterranean fever; MKD: mevalonate kinase deficiency; TRAPS: tumor necrosis factor receptor-associated periodic syndrome; CAPS; and cryopyrin-associated periodic syndromes

Figure 2: Distribution of the AIDAI total score for 98 patients with a HRF diagnosis (0/1 scoring).

Figure 3: ROC curve with binary items of disease activity (0/1 scoring) showing an area under curve of 0.98(95% CI 0.96-1 ) in 98 patients with an HRF

Examples

Patients and Methods

The overall methodology of this project phase was based on the following framework:

Patients were asked to fill a survey (diary) for at least one month prior to assessment.

In a first step, physicians made a blinded evaluation of patient's disease activity level, through analysis of the results of the survey

For patients for which consensus was not reached, a NGT consensus conference was conducted, leading to assessment of the disease activity level for some of these patients.

Finally, the score was finalized, and the threshold above which activity is present was determined. Sensitivity and specificity could then be calculated.

This process was followed as there is no golden standard to determine the activity of the diseases, and the state of activity of the patients thus needs to be determined by the experience of various physicians, specialists of these diseases.

Study design.

A convenience sample of patients (children and adults) with a genetically confirmed diagnosis of FMF, MKD, TRAPS or CAPS, and in varying states of disease activity, ranging from active to inactive disease, was enrolled consecutively.

Patients were evaluated by at least one physician with expertise in the care of AID. All patients (or their parents for minors as appropriate) were asked to complete a one month prospective diary prior to the scheduled clinical appointment. Content and scoring of the AIDAI tool.

The AIDAI diary contains 13 items as follows: a) fever >38°C (100.4 ); b) overall symptoms; c) abdominal pain; d) nausea/vomiting; e) diarrhea; f) headaches; g) chest pain; h) painful nodes; i) arthralgia or myalgia; j) swelling of the joints; k) eyes manifestations; I) skin rash; m) pain relief taken.

The items of patient/parent's diary were dichotomized as no (0) =absence of symptom or yes (1 ) =presence of symptom (either minor, mild or severe), yielding a total score in a single day of 0-12. In a month of 31 days the cumulative score thus ranges from 0 to 372.

Indeed, although the diary also noted the use of rescue (pain killers) treatment, this item was not used in the score calculation.

In addition to the diary completed by the patient and/or parents, physicians and patients completed together, during the visit, a questionnaire retrospectively assessing disease activity during the preceding 30 days: this documented: 1 ) the numbers of days with each symptoms; 2) all the treatments taken 3) the number of days of pain relief drugs; 4) the regularity of disease modifying anti-rheumatic drugs (DMARDs) taken (colchicine or biologies); 5) the number of days out of school or work; 6) patient's social life disturbance by the disease with a three level categorical scale (none; a little; a lot); 7) patient's assessment of fatigue on a 21 circle visual analogue scale (VAS) (where 0= no fatigue and 100=maximum fatigue); 8) patient's global assessment of overall well-being and physician's global assessment of disease activity on two separate 21 circle VAS ( Filocamo et al., J Rheumatol 2010;37(7):1534-41 ; Pincus et ai, J Rheumatol 2008;35(8):1550-8.); 9) the need to consult an external doctor; 10) the feasibility of the activity score (patient's opinion and comments). Validation procedures

Data from patients/parents and physicians' assessment were validated through a three step validation process:

Step 1 Physician's blinded web evaluation of patient's disease activity level: Seven physicians with expertise in AID evaluated the level of activity for each patient in the database as: no activity (0), low activity (1 ), moderate activity (2), severe activity (3). These physicians had access to the completed diary as well as to the questionnaire filled by the patients.

Patients were anonymized, total AIDAI score was not provided and the physicians were blinded to the diagnosis so that they could not recognize the patients followed in their own hospital.

The physicians worked independently from each other. At each session a minimum consensus of 6/7 (85%) for the inactive/active (low, moderate, and severe activity combined) was required to consider a patient as having reached a final consensus. When consensus was not achieved a new session was held for a total of three iterative independent evaluation sessions; at each subsequent session physicians were provided with their previous score as well as with the blinded evaluation of the other participants.

Step 2 NGT consensus conference of patient's disease activity level:

Eight physicians were asked to re-evaluate individually the level of disease activity for the patients in whom consensus was not achieved in the previous step. For all patients, each physician was asked to provide a verbal explanation as to why he/she has given a certain level of disease activity to that particular patient. The individual evaluation of each physician was shown on a screen to all participants. Then a web-based electronic vote was taken and consensus was achieved if a minimum of 6/8 (75%) participants provided the same level of disease activity. Patients for which consensus could not be achieved after a second vote were discarded from further considerations.

Step 3 Statistical analysis of the AIDAI scoring system:

In the work previously published (Piram et al., op. cit), the score calculation differs according to the specific disease as follows:

FMF could be scored by adding the variables a+c+g+i+j+l,

MKD the variables a+c+d+e+h+i,

TRAPS the variables a+b+c+i+k+l and

CAPS the variables a+f+i+k+l.

For a 31 day month, the cumulative scores of the prior art ranged from 0 to 496 for FMF, MKD and TRAPs and 0 to 403 for CAPS, respectively. In the context of the work hereby carried out, it was determined that the sum of the positive items from the diary as yes/no has the same statistical performance of the disease specific scoring system previously described.

Furthermore, it was determined that it was possible to calculate a simplified score for each subject by summing up all the items of the diary as total score=a+b+c+d+e+f+g+h+i+j+k+l for the simplified items scored 0 to 1 (range 0 to 372).

This was also compared to the total score=a+b+c+d+e+f+g+h+i+j+k+l obtained for the items scored 0 to 3 (range 0 to 1054) in the previous test.

Average values of the score were compared between activity groups (inactive versus the three levels of activity combined). The ability of the score to discriminate active versus inactive patients and the best AIDAI total cut-off score to classify the patients as active/inactive was evaluated by a receiver operating characteristic (ROC) analysis. Sensitivity, specificity and accuracy of the scores were calculated using the best cut-off value of the total AIDAI score.

Data were entered in a web based Access XP database and analyzed with Excel XP (Microsoft), SPSS Inc. v.18 by 2 of the authors (MPS and NR).

It is reminded that:

Sensibility is the probability of obtaining a positive result for the test if the disease is active; Sensitivity = (TP) / (TP + FN). A test that is 100 % sensible has thus no false negative.

Specificity is the probability of obtaining a negative result for the test if the disease is not active; Specificity = (TN) / (TN + FP). A test that is 100 % specific has thus no false positive.

Accuracy = (TP + TN) / (TP + TN + FP + FN)

TP = True Positive (patients with active disease and above or equal to the threshold)

TN = True Negative (patients with disease not active and below the threshold)

FP = False Positive (patients with disease not active and above or equal to the threshold)

FN = False Negative (patients with active disease and below the threshold) It is always important to have a test that is both specific and sensitive. The quality of a test may be determined by drawing a Receiving Operating Characteristic (ROC) curve and measuring the Area Under Receiving Operating Characteristic curve (AUROC).

The ROC curve is drawn by plotting the sensitivity versus (1 -specificity), after classification of the patients, according to the result obtained for the test, for different thresholds (from 0 to 1 ). It is usually acknowledged that a ROC curve the area under which has a value superior to 0.7 is a good predictive curve for diagnosis. The ROC curve has to be acknowledged as a curve allowing prediction of the quality of a diagnosis test.

Results

Data from a total of 1 1 1 patients were collected. Five patients were not eligible for the analysis: four with PFAPA syndrome and one with a diagnosis of CINCA with incomplete information.

A total of 106 patients were available for the analysis: 42 FMF, 39 CAPS,

14 TRAPS and 1 1 MKD.

Step 1 Physician's blinded web evaluation of patient's disease activity level: During the three iterative web based blinded evaluation consensus was achieved on 63/106 cases (59.4%) with 13 patients declared as inactive, 49 active

(26 with low activity, 13 moderate activity, 10 high activity) and one patient not evaluable (wrong diagnosis) by consensus.

For the remaining 43 patients consensus was not achieved and patients were therefore considered for the consensus NGT discussion as per Step 2.

Step 2 NGT consensus conference of patient's disease activity level

During the NGT meeting consensus was achieved for an additional 36 patients for a total of 98/106 cases (92%).

For the remaining eight cases consensus was not achieved and the patients were therefore discarded for further evaluation.

Table 2 reports the disease activity grading for the 4 HRFs diagnosed in 98 patients with consensus and for all patients combined. 26 out of 98 subjects (27%) were declared as inactive while the remaining 72 (63%) were classified as active (33 low, 28 moderate, 1 1 high disease activity). FMF CAPS TRAPS MKD TOTAL

N=39 N=35 N=14 N=10 N=98

Inactive 8 12 6 0 26

Active:

Low activity 13 14 2 4 33

Mild Activity 1 1 8 3 6 28

Severe activity 7 1 3 0 1 1

Table 2: Consensus classification of the 98 patients with four according to the level of disease activity

FMF: familial Mediterranean fever; MKD: mevalonate kinase deficiency;

TRAPS: tumor necrosis factor receptor-associated periodic syndrome; CAPS; and cryopyrin-associated periodic syndromes

The descriptive statistics for each item of the AIDAI tool for the 98 patients is reported in Figure 1.

Step 3 Statistical analysis of the AIDAI scoring system.

Surprisingly, statistical analyses gave the same results when using the 0-3 score and the simplified no (0)/yes (1 ) version, only the latter is reported here.

In the final analytical step, in order to properly calculate sensitivity, specificity and ROC cut-off, the 98 patients were dichotomized as active (low, moderate and high activity combined) or inactive.

Figure 2 shows the distribution of the AIDAI total score with each AIDAI item dichotomized as yes/no: 14 subjects (12%) had a score=0; the score had a mean value of 22.2±26.8) and a median of 14 (range = 0-175); values are skewed toward lower values of the AIDAI total score.

According to the ROC curve (Figure 3) an AIDAI score≥ 9 points identifies active patients while an AIDAI total score < 9 points identifies patients as inactive; sensitivity was 89% (95%CI=80%-94%), specificity 92% (95% CI=76%-98%), area under the curve (AUC) of 98% (95% Cl=96%-100%) and accuracy 90% (95% CI=84%-96%) (Table 3). Activity as defined by consensus

Activity as defined by the

Active Inactive TOTAL

AIDAI total score

≥9 active 64 (89%) 2 (8%) 66

<9 inactive 8 (1 1 %) 24 (92%) 32

TOTAL 72 26 98

Table 3. Accuracy measures of the AIDAI total score (0/1 scoring) for 98 patients with a HRF diagnosis. A total AIDAI score <9 separates inactive from active patients (total score≥9).

Similar performances were obtained when the original 0-3 score for each item of the AIDAI was applied as follows: sensitivity was 92% (95% CI=86%-98%), specificity 96% (95% Cl=88%-100%), area under the curve (AUC) of 99% (95% Cl=97%-100%) and accuracy 93% (95% CI=87%-98%) (cut-off at 10, data not shown).

Accurate and reproducible evaluation of disease activity is of major importance in the assessment of treatment efficacy, in appreciation of the effect of disease activity on quality of life, and, although this is currently unproven, may predict the development of serious long-term complications.

AIDAI is the first validated instrument designed to standardize assessment of AID activity across trials, and to facilitate comparison and meta-analysis of clinical trials in the future. AIDAI will also allow patient's self-reported disease activity evaluation in daily practice.

AIDAI proved to be a valid and reliable tool for the assessment of presence or absence of disease activity in the four main HRFs. In its current form, the AIDAI score is very easy to use. A unique patient/parents diary gathering all variables for the four main auto-inflammatory diseases is convenient for routine clinical use. The statistical analyses showed that a simple sum of the positive items from the diary with binary value (yes/no) has the same statistical performance as a disease-specific scoring system with graded values reported in the prior art (Piram et al., op. cit).

Both patients and physicians will benefit from this simplified scoring system, as binary values are easier for patients and the single format with a straightforward sum of all positive items simplifies its use by physicians.

In this validation phase, patients were asked to complete a one month prospective diary prior to their scheduled clinical appointment. However the diary could be completed for periods of other lengths as clinically appropriate. A three month period survey is probably more suitable for episodic diseases such as FMF and MKD but the period could be longer in TRAPS and shorter in CAPS.

For use in a period greater than one month, the calculation of the score is straightforward consisting of the sum of all 12 variables as indicated above, divided by the number of months over which the diary was completed.

An AIDAI cut-off score of nine accurately differentiated patients with active versus inactive disease with an area under the ROC curve of 0.98 with sensitivity and specificity exceeding 0.8. This cut-off will help physicians in daily practice to decide if a patient has active or inactive disease. This is moreover important for clinical trials in which an index discriminating patients achieving remission from those who did not, might increase the power of the statistical comparisons, thus permitting smaller sample size (Turner et al., Gastroenterology 2007;133(2):423- 32) a crucial factor in orphan and ultra-orphan diseases such as HRFs. Although the number of patients followed made is possible to design the

AIDAI score, the limited number of patients did not allow for separate analyses of the different diseases or discrimination with sufficient power of the different levels of disease activity (low, moderate and high). The AIDAI score was validated for the four main AIDs, but could also be applied to other AID which shares some of their clinical features such as PFAPA (Periodic Fever Aphtous stomatitis Pharyngitis Adenitis) and Schnitzler's syndrome. Furthermore, once could develop disease-specific scores by not taking into account the variables that are not associated with some diseases. In particular, on could sum the following variables for a period of one month:

FMF: fever >38°C / abdominal pain / chest pain / arthralgia or myalgia / swelling of the joints / skin rash

MKD: fever >38°C / abdominal pain / nausea/vomiting / diarrhea / painful nodes / arthralgia or myalgia

TRAPS: fever >38°C / overall symptoms / abdominal pain / arthralgia or myalgia / eyes manifestations / skin rash

CAPS: fever >38°C / headaches / arthralgia or myalgia / eyes manifestations / skin rash

The threshold for determining activity for these diseases should also be close to 9 and could be easily determined according to the method as described above.

This tool can be useful in clinical practice as well as clinical trials, in the assessment of activity of these rare diseases, thus permitting more reliable analysis of the efficacy of new treatments.