Trial Review

Registering a new trial?

To achieve prospective registration, we recommend submitting your trial for registration at the same time as ethics submission.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12621000394842
Ethics application status
Approved
Date submitted
16/01/2021
Date registered
9/04/2021
Date last updated
9/04/2021
Date data sharing statement initially provided
9/04/2021
Type of registration
Prospectively registered

Titles & IDs
Public title
Observational study to identify those real-world treatment-seeking women with urinary storage symptoms most likely to benefit from Botulinum A toxin injections into bladder wall..
Scientific title
Development of a prognostic model for Botox effectiveness in the treatment of lower urinary tract symptoms among women from a real-world primarily and secondarily referred treatment-seeking community cohort.
Secondary ID [1] 303448 0
nil knoiwn
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Refractory overactive bladder, 320323 0
Mixed incontinence. 320325 0
Storage lower urinary tract symptoms. 320326 0
Urinary urgency. 320327 0
Bladder pain. 320749 0
Nocturia. 320750 0
Bladder infection. 320751 0
Voiding impairment. 320752 0
Urinary retention. 320753 0
Cystoscopic Bladder wall appearance 320760 0
Condition category
Condition code
Renal and Urogenital 318244 318244 0 0
Other renal and urogenital disorders

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Nil intervention. Creation starting in May 2021 of an observational study dataset by the principal investigator, using as the source the details obtained from the patient files of all women receiving an initial Botulinum A toxin bladder wall injection as part of their standard care and who provided at that time, detailed standardized symptom and demographic as well as general medical and surgical history, and who allowed detailed physical examination including bladder wall visualization, urodynamic studies, imaging, urine culture before and after treatment and who were followed up for a minimum of 12 months post-treatment. The Botulinum A toxin (Botox) was for the treatment of refractory storage lower urinary tract symptoms with an urge component. The treatments started in 2002 and continue. Patients treated from 2002 to April 2021 will be included. They are followed-up at 10 days, 3 months, 12 months post Botox treatment, then further irregularly and indefinitely for as long as individuals return for care. Details of any further treatments and complications were/ will be included and further history and clinical examination details will be collected when available until 2025. The concept for this study originated in January 2016 and the patient information recorded will be influenced by this time point. The study data set will allow the creation of a predictive model for Botox treatment success and explore the specific factors associated with success.
A future observational study collecting similar but only relevant existing data from a geographically separate group will be planned to externally validate the predictive model generated but only if the training model validates adequately internally
Intervention code [1] 319498 0
Not applicable
Comparator / control treatment
No control group.
Control group
Uncontrolled

Outcomes
Primary outcome [1] 326224 0
Botox success measured as a global treatment response. This was assessed using a verbal patient rated symptomatic categorical outcome as a percentage score 0-100%. When patients not infrequently had difficulties allocating percentages (“I’m not good at that”) they were coached. Is it worse? The same? Better? A great deal better? 50% better? Is it 80% better?
Questions about pad use, nocturia, daytime frequency prompt clarification. Many patients struggle to nominate a figure – yet most could confidently report a broad category outcome, ie: ‘’over 50%? - yes definitely”. Percentage outcomes will be recorded as 4 broad categories. for database entry purposes: 4; Unsure, 3; worse, 0; no change, 2; < 70%, 1; >= 70%,
Timepoint [1] 326224 0
10 days post Botox treatment
3 months post botox treatment
12 months post botox treatment
Variably after this depending on the patient's desire to return :
Secondary outcome [1] 390585 0
Recording of patient return for further Botox dosage. Recorded as yes or no at the time of data analysis
Timepoint [1] 390585 0
Return at any time point within 5 years. As this study is observational and uses data from patient treatment records patients will return if and when they wish and there are no fixed time points for a return. All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [2] 390586 0
Response to a further Botox dosage will be measured as a global patient-rated treatment response scored from 0 to 100%. It will be stored as a categorical variable; 0- worse, 1 no change, 2 >50%, 3 >70%.
Timepoint [2] 390586 0
The response is measured at 10 days, 3 months, 12 months.
Secondary outcome [3] 390587 0
Other therapies trialed post initial or subsequent Botox injection entered as: 1. further medication. 2. bladder neck surgery, 3.Bulking agent 4. Sacral nerve stimulation, 4 Posterior tibial nerve stimulation, 5. Contiform device, The global patient-rated outcome. of this treatment is recorded as a categorical measure; success or failure.
Timepoint [3] 390587 0
The outcome of the other therapies trialed, is measured at 10 days and 3 months. Variably also at 12 months after if the patient returns at all as the data set is observational and uses information obtained from patient records. All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [4] 390588 0
Recording of patient return for more than 2 subsequent Botox dosages. Recorded as the number of returns and time period between each return. .Number of repeat injections measured as whole numbers.
Timepoint [4] 390588 0
Time period as whole months between returns for a time period up to 20 years following the initial dose..All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [5] 390589 0
Recording magnitude of Botox doses over time in those who return for 3 or more than 3 doses. Recorded as injection number then Botox brand and units given.
Timepoint [5] 390589 0
Will include as valid any timepoint up to 20 years post initial dose..All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [6] 391821 0
Pre-treatment and post-treatment post-void urine residua in MLS l for every Botox treatment
Timepoint [6] 391821 0
All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [7] 391822 0
Urine culture results using standard culture technique and using Kass's criteria. Urine infection history prior to initial Botox treatment and infection occurring after every treatment will be recorded
Timepoint [7] 391822 0
All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [8] 391823 0
The treatment of urine infection provided after every Botox dose.
Timepoint [8] 391823 0
All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.
Secondary outcome [9] 391824 0
Cystoscopic bladder appearance at the time of Botox injection. Rated as inflamed, oedematous, uninflamed, trabeculated, diverticular pockets, prominent vessels, focal lesion with lesion specified
Timepoint [9] 391824 0
All return data available from patient files will be entered at the time data entry commences, from May 2021. Further data entry will occur as it accrues for 5 years.

Eligibility
Key inclusion criteria
Botox administration is an inclusion criterion
The great majority, of women, do or will have urgency.
If not urgency, they will have other symptoms, history, examination findings, suggesting urge or OAB is present..
All were / will be treatment-refractory or unsuitable to have anticholinergics and some later Mirabegron, before Botox was or is considered.
They are included if they have other failed therapies prior to being considered for Botox; This includes Sacral nerve stimulation, PTNS, Hydrodistension, physiotherapy, bladder neck surgery, prolapse surgery, vaginal pessary device are other treatments applied.
Minimum age
15 Years
Maximum age
No limit
Sex
Females
Can healthy volunteers participate?
No
Key exclusion criteria
Exclusions:
This study uses an existing and future clinical dataset.
There are 2 time points of exclusion.
1. There are study dataset exclusions from the existing and the future growing dataset.
These are as follows:
Those few given Botox where voiding with catheter assistance was already established will be excluded as it is considered the inclusion of this subgroup will bias by confounding the variable ‘retention’ as a valid and useful potential predictor for treatment failure after Botox. For those not already catheterizing, where retention seemed likely, Botox is and will be excluded unless the patient insists and accepts urinary retention risk- here a reduced dose was given in some cases.

2. Some community treatment seeking women were and continue to be excluded from the existing and future dataset and thus will be excluded from the proposed future study dataset.
These are as follows:
2. Women have been or will be excluded from treatment when it is / was deemed clinically inappropriate.
Excluded are and will be those with other discoverable and treatable underlying causes for their urge or LUT symptoms, but only where that treatment had resolved symptoms sufficiently for the patient not to request Botox subsequently. Thus, those responding well enough to other treatments such as pessaries, physiotherapy, bladder training, medications, antibiotics, posterior tibial nerve stimulation (PTNS), prolapse surgery and Sacral nerve stimulation (SNS), were not considered further for Botox treatment.
Women were excluded when they did not feel symptoms were sufficiently troublesome, Botox was refused in some cases due to patient anxiety.
Cost excluded many from treatment prior to 2014 when Botox was not funded and required day surgery admission and in the public system- a long delay;
Prior Botox treatment was an exclusion.

Those with milder urge were often exduded prior to 2014 when there was high cost and no outpatient Botox availability; This would affect the frail and poorly funded. Prior to the mesh debate of 2018 many were excluded as they preferred bladder neck surgery for mixed incontinence
Those with voiding impairment together with recurrent refractory urinary tract infections (UTI) were and are more likely to be excluded over time particularly if better alternatives were available as infection risk became apparent.
Once Botox became PBS listed, treatment selection followed and continues to follow Australian PBS criteria for Botox use which excludes those who do not have ‘’symptoms of urinary incontinence, urgency, and frequency, in adult patients who have an inadequate response to or are intolerant of an anticholinergic medication... (and) treatment of urinary incontinence due to neurogenic detrusor overactivity, as demonstrated by a urodynamic study, in a patient who is not adequately managed by anti-cholinergic therapy. Inadequate management by anti-cholinergic therapy is shown by an insufficient response or if the patient experiences intolerable side effects necessitating permanent withdrawal from treatment.’’
Counselling affects patient treatment choice. Patients were initially warned of a ~ 7% risk of transient voiding impairment requiring temporary catheter use and a 21% risk of bladder infection. This likely caused many to exclude themselves. These exclusions reduced with introduction of PBS funding and a standard 100U Ona-Botulinum toxin A dose,



Study design
Purpose
Natural history
Duration
Longitudinal
Selection
Defined population
Timing
Both
Statistical methods / analysis
Data will be entered into an SPSS database. Unidentified. All likely relevant variables available will be entered but all variables available regardless of likely relevance will be assessed,
Statistical analysis will be performed using SAS v9.4 (SAS Institute, Cary, North Carolina, USA and R (R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/).
Predictive modeling techniques will adhere to the TRIPOD statement guidelines
Modeling will be performed by Hunter Medical Research Institute (HMRI), Newcastle, New South Wales, Australia who have no clinical interest in the research outcome.
Data from the study data set will be used as the training dataset for the model. Internal validation will be performed. Modeling outcome will be used to decide whether to later, externally validate the model. using a geographically separate dataset While criteria for external validation must be somewhat arbitrary, the model will not be considered for later external validation unless it achieves a 0.7 area under ROC and sensitivity of 0.7, and the specificity of 0.7.
Candidate predictors chosen from the training data set will initially be modeled using age stratification and a Random forest-based algorithm approach to see if this achieves the best sensitivity/ specificity. Other modeling techniques will be examined also.
Mixed incontinence pure urge -wet and dry will also be analyzed separately. Most symptoms are likely to be 'mixed'.
Imputation within the random forest-based algorithm will be used for the missing variable data>= 50% of the sample such as BMI. Otherwise, variables where variable data is < 50 % of the total sample will be ignored for the multivariate analysis. This is likely to affect only cystoscopic appearance. Not commonly accessible variables won't be considered. for example, Health utility index scores are reported to be predictive but won't be utilized due to the expense of using this questionnaire. Predictive models need to use variables that are accessible to most.
Any unexpected associations or association directions will not need to be interrogated for selection bias, confounding, or intervention effects when used for predictive model purposes. Different modeling techniques such as multivariate with lasso regression will be considered.
A separate validating study is planned to be performed at a 2nd institution only if the model appears satisfactory. Here additional demographic data will be collected to define the ways in which the validating institution case-mix differs in order to adjust the model if needed.
For this, I plan to collect the relevant predictors. I plan to apply the same primary study exclusion criteria. The 2ndry exclusions will inevitably differ.
Calibration curves will show the “fitting” of the training model; this shows the potential the model has to predict at all levels of risk. Ideally, this will be established in a geographically different sample: This is validation. Calibration compares bundles of the model’s predicted values, usually deciles, from 0- 100% and compares the match with identical bundles of the observed event rates.
The training data set can be used to internally validate the model –using resampling- “bootstrapping”.

Validation is a function of the model fit. An overfit model will match the training data well but not work elsewhere. The more difficult an outcome is to predict; the more noise will exist in the training information that needs to be ignored in future applications. The problem is which fitting variables to ignore and various modeling techniques exist and will be used to optimize this such as Lasso techniques. If the model is overfitted, it picks up the random noise in the data. If it fails to focus on the important constant /persistent themes that will be repeated in any future cohorts and it will predict or validate poorly.
An under fitted model will ignore important persistent themes and lack the important predictive variables
Discrimination will show how often the model makes a prediction in the right direction. It shows how often the model will correctly predict success when there is actually a success. It is a ranking measure so it doesn’t tell us how helpful the prediction will be, how close the risk predicted approaches actual risk. There are many available methods to formulate predictive models and the technique that is most successful will be chosen.
Finally- the model if successful will as a separate study, be tested using a comparative randomized trial design to see if outcomes after using the prediction model are really better than usual care.

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
1/05/2021
Actual
Date of last participant enrolment
Anticipated
1/09/2021
Actual
Date of last data collection
Anticipated
1/05/2025
Actual
Sample size
Target
750
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
NSW

Funding & Sponsors
Funding source category [1] 307596 0
Self funded/Unfunded
Name [1] 307596 0
Jane Manning
Country [1] 307596 0
Australia
Primary sponsor type
Individual
Name
Jane Manning
Address
Dr Jane Manning
Coast Pelvic floor clinic
PO Box 648 The Junction 2291 NSW
Country
Australia
Secondary sponsor category [1] 308288 0
None
Name [1] 308288 0
Address [1] 308288 0
Country [1] 308288 0
Other collaborator category [1] 281591 0
Individual
Name [1] 281591 0
Chris Oldmeadow HMRI (Hunter Medical Research Institute)
Address [1] 281591 0
Christopher Oldmeadow
Associate Director: Research Design and Statistical Services

Lot 1 Kookaburra Circuit
New Lambton Heights, NSW, Australia, 2305
Postal Address
Locked Bag 1000
New Lambton, NSW, Australia, 2305
Country [1] 281591 0
Australia
Other collaborator category [2] 281592 0
Individual
Name [2] 281592 0
Matthjew Clapham (HMRI)
Address [2] 281592 0
Matthew Clapham
Statistician
Lot 1 Kookaburra Circuit
New Lambton Heights, NSW, Australia, 2305
Postal Address
Locked Bag 1000
New Lambton, NSW, Australia, 2305
Country [2] 281592 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 307651 0
university of newcastle Human Research Ethics Committee
Ethics committee address [1] 307651 0
Cnr King and Auckland Streets Newcastle NSW 2300. Australia.
Postal address. University Drive Callaghan NSW 2308. Australia ...
Ethics committee country [1] 307651 0
Australia
Date submitted for ethics approval [1] 307651 0
21/09/2019
Approval date [1] 307651 0
11/12/2019
Ethics approval number [1] 307651 0
H-2019-0371.

Summary
Brief summary

Botulinum A Toxin is currently used to treat refractory urinary urgency. This research uses a part existing retrospective and part (with regard to concept)- prospectively collected dataset that is very detailed, and which documents the care of real-world treatment-seeking women in the community. Existing patient records will be used to compile a large study data set that in turn will be used to create a predictive model for Botox treatment outcome. This will be internally and if promising, externally validated, and finally, clinically trialed for its usefulness as a predictive model to guide initial and also subsequent Botox use. Additionally, any negative effects for those receiving Botox and other treatments over time such as deterioration in bladder function will be tracked. The aim is to achieve more effective, efficient treatment of storage symptoms that is relevant to real-world treatment-seeking women. Such a model does not currently exist.
Trial website
Trial related presentations / publications
Public notes
Urogynaecology Society of Australia (UGSA) meeting 2020. " Predictive Modelling for Overactive Bladder treatment"
This was a description of the proposed study.

Contacts
Principal investigator
Name 108010 0
Dr Jane Manning
Address 108010 0
Dr Jane Manning
Coast Pelvic Floor Clinic
PO Box 648
The Junction 2291 NSW
Country 108010 0
Australia
Phone 108010 0
+61 02 49408069
Fax 108010 0
+61 02 49610599
Email 108010 0
[email protected]
Contact person for public queries
Name 108011 0
Jane MAnning
Address 108011 0
Dr Jane Manning
Coast Pelvic Floor Clinic
PO Box 648
The Junction 2291 NSW
Country 108011 0
Australia
Phone 108011 0
+61 02 49408069
Fax 108011 0
+61 02 49610599
Email 108011 0
[email protected]
Contact person for scientific queries
Name 108012 0
Jane Manning
Address 108012 0
Dr Jane Manning
Coast Pelvic Floor Clinic
PO Box 648
The Junction 2291 NSW
Country 108012 0
Australia
Phone 108012 0
+61 02 49408069
Fax 108012 0
+61 02 49610599
Email 108012 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.