Nomogram to Diagnose Prostatic Inflammation (PIN) in Men With Lower Urinary Tract Symptoms

Lower Urinary Tract Symptoms (LUTS) are common in men over 45 years of age and have been traditionally attributed to bladder outlet obstruction (BOO) as a result of benign prostatic obstruction (BPO), which is often associated with benign prostatic enlargement (BPE) resulting from the histologic condition of benign prostatic hyperplasia (BPH).

Additionally, more recent research focuses on the role of prostatic inflammation in the development of prostatic enlargement and consequently the severity of LUTS and the natural history of these symptoms. Several models and hypotheses have been suggested for the pathogenesis of this condition. Also, the relationship of the inflammation pattern with the progression of BPH is currently investigated through the molecular and metabolic pathways, which can be responsible for this connection.

For this reason, the present study aims to develop a nomogram based on clinical parameters that will diagnose the presence of prostatic inflammation. Should the nomogram prove valid (that is: it can make reliable estimations of prostatic inflammation presence in men with LUTS), it will allow physicians to use patient characteristics to identify patients with increased risk of prostatic inflammation in order to optimise medical strategies for the management of LUTS

The study has the following objectives:

Primary objective:

To build a predictive nomogram that will estimate the personalised risk of the presence of prostatic inflammation in patients with LUTS

Secondary objectives:

To validate the nomogram

The study is a non-interventional, multicentric, cross-sectional, observational, prospective study. Patients with LUTS/BPH symptoms who have been scheduled for either prostatectomy (Transurethral surgery - open) or Transrectal Ultrasound (TRUS)-biopsy as indicated by the standard care for their condition according to the physician's practice, are eligible for the study.

Patients will be asked to participate in the study. The following parameters will be recorded: Age, Body Mass Index (BMI), Prostate Volume (PV) (either with transrectal or abdominal ultrasound), total IPSS, voiding IPSS, storage IPSS, Maximum flow rate (Qmax), each component of Metabolic Syndrome (MetS) (waist circumference, triglycerides, blood pressure, fasting glucose, HDL cholesterol or any treatment for these components), serum Prostate Specific Antigen (PSA), presence (Yes or No) of calcifications (either with transrectal or abdominal ultrasound), dipstick urine, previous or current medication for LUTS/BPH, and history of confirmed (Yes or No) Urinary Tract Infections (UTIs).

Specimen will be examined for inflammation according to Irani's score (total and histologic inflammation grading and aggressiveness grading subscores).

The study will be conducted by six centers (or more if needed) in five countries.

The duration of the study is estimated to be six months depending on the enrollment pace. As per the design of the study, no additional treatment/intervention related to the objectives of the study will be required and no follow-up visits will be needed.

The end of study is the date of the last patient histology report.

Population (base) The population will be men, age ≥ 40 yrs, with LUTS who will undergo any prostatic surgery for BPH (Open, laparoscopic, robotic, transurethral resection/enucleation, laser prostatectomy) or TRUS-biopsy according to the standard clinical practice of the participating urologists

Sample size calculation A sample size of 375 patients for the development of the nomogram will be needed. It is generally accepted that for the calculation of the sample size required for the development of a nomogram: the minimum value of the frequencies of the two response levels should be greater than 10 times the number of predictors when the outcome is binary (presence of inflammation yes or no).

The plan of the present study is to include the following 15 parameters (predictors): BMI, Age, PV, IPSS, voiding IPSS, storage IPSS, Qmax, each component of MetS, PSA, presence of calcifications, and history of UTIs. Taking into account that the incidence of prostatic inflammation in the biopsies is around 60%. Therefore, the sample size needed is 10 x 15 = 150 patients for the non-inflammation group and 225 patients for the inflammation group

Treatment of Subjects Not applicable. Any treatment will be offered according to the standard treatment practice of the physicians. Treatment will not be influenced by this study, as this is an observational study.

Data Safety Information will be recorded in the Case Report Form (CRF). A code number will be given to each patient in order to prevent patients' identification. Only the local Primary Investigator will have access to all the names of the patients.

All the CRFs will be stored under the responsibility of the participating centers. The CRFs (without any patient's identification info) will be sent to the Project Leader for the analysis.

Study procedures:

Diagnosis of Prostatic Inflammation:

Prostatic inflammation will be determined according to the total Irani's score, histologic inflammation grading and aggressiveness grading subscores.

The Irani's score classifies prostatic inflammation on the basis of the extension of inflammatory cells and their effect on prostate tissue. A 4-point scale is used for inflammation (0-no inflammatory cells, 1-scattered inflammatory cell infiltrate, 2-nonconfluent lymphoid nodules and 3-large inflammatory areas with confluence of infiltrate) and aggressiveness (0 -no contact between inflammatory cells and glandular epithelium; 1-contact between inflammatory cell infiltrate and glandular epithelium; 2-clear but limited, that is less than 25% of the examined material, glandular epithelium disruption, and 3-glandular epithelium disruption on more than 25% of the examined material).

Definition of Metabolic Syndrome (MetS):

The USA National Cholesterol Education Program - Adult Treatment Panel III (NCEP-ATPIII) definition for MetS will be used. It requires at least three of the following five components: central obesity (waist circumference of >102 cm), elevated triglycerides (≥1.7 mmol/L or 150 mg/dL), elevated blood pressure (≥130/85 mmHg), elevated fasting glucose (≥6.1 mmol/L or 110 mg/dL) and reduced HDL cholesterol (<1.03 mmol/L or 40 mg/dL). Patients with known diabetes mellitus and/or hypercholesteremia and/or arterial hypertension under treatment will be considered as positive for the specific component.

Withdrawal and replacement of individual subjects Subjects can leave the study at any time for any reason if they wish to do so without any consequences. The investigator can decide to withdraw a subject if a violation of the protocol occurs.

Subjects will be replaced after the withdrawal.

Safety Reporting The physicians are asked to apply treatment conform their standard practice in medication type and follow-up frequency; therefore the quality of care is equal and there are no additional risks, therefore no safety issues are expected.

Adverse events (AEs) or Serious adverse events (SAEs) This study has no interventional product. Patients will receive established, standard medical treatment, management of AEs will be done according to the national protocols.

[Data Safety Monitoring Board (DSMB) / Safety Committee] As this study is an observational study, and patients are treated according to the physician's standard practice, no safety problems are expected. Therefore no DSMB will be used in this study.

Statistical Analysis Primary study parameter(s) The development of a multivariable diagnostic model generally requires identification of the important predictors out of a set of preselected candidate predictors; assigning the relative weights for each predictor in a combined risk score; estimating the model's predictive performance including its calibration, discrimination and (re)classification properties; assessing its potential for optimism using so-called internal validation techniques.

Selection of predictor will be based on the multivariable analyses. Candidate predictors that will not contribute usefully in the multivariable model will be removed. Backward elimination will be used to examine all candidate predictors in the multivariable model and run a sequence of tests to remove or keep variables in the model based on predefined nominal significance level for variable exclusion, using the log likelihood ratio test for comparing two models.

The multivariable analysis estimates regression coefficients of each predictor included in the final model, which are mutually adjusted for the other predictors in the model. The coefficients thus quantify the contribution of each predictor to the outcome probability or risk estimation.

Secondary study parameter(s) Internal validation will be performed. Bootstrapping is the preferred method for internal validation, certainly when the development sample is relatively small and/or a high number of candidate predictors is studied.

Bootstrapping is a statistical method that aims to mimic this sampling process using only the data at hand by sampling with replacement a study sample of the same size (to preserve the precision) from the original study sample in which the model was developed. With bootstrapping, all data are thus used for model development and it provides insight into the extent to which the developed model (in the original study sample) is overfitted and too optimistic. Drawing with replacement mimics that random component, making bootstrap samples similar but not identical to the original study sample. This may yield a different model developed from each bootstrap sample with corresponding c-index. Subsequently, each boot- strap model is applied to the original study sample (mimicking the source population), yielding a difference in c-index. The average of all these 'c-index differences' indicates the optimism in the apparent c-index of the prediction model that was initially developed in the original study.

Recruitment and consent Eligible subjects will be selected by participating physicians. During consultation, the physician takes the history, examines the patient and reviews his examinations. Based on the findings, the physician discusses with patient and sets the indication for TRUS-biopsy or prostatectomy. If the patient meets the inclusion criteria, the physician informs the patient about the study and the information subject form is given. The patient who agrees to participate in the study, fills the informed consent (IC) form when the participant comes for the scheduled procedure (biopsy or prostatectomy).

Handling and storage of data and documents A code number will be given to each patient in order to prevent patients' identification. Only the local Primary Investigator will have access to all the names of the patients.

Monitoring, Auditing and Quality Assurance Electronic audit will be performed at the end of the study: Database will be closed and centers will be asked to send specific information from randomly selected patient's file (e.g. baseline PSA, prostate volume, etc).

There will be no centralization (a central Pathology Lab) for the examination of the specimen. For consistency reasons across the Pathology Labs and control of Quality, photos of specimen will be randomly sent from one Lab to another to investigate agreement between the Labs in the grading of the inflammation.