Intervention Protocol

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Interventions for infected cysts in people with autosomal dominant polycystic kidney disease

  1. Nuria Montero1,*,
  2. Laia Sans1,
  3. Angela C Webster2,3,4,
  4. Julio Pascual1

Editorial Group: Cochrane Renal Group

Published Online: 29 JAN 2014

DOI: 10.1002/14651858.CD010946


How to Cite

Montero N, Sans L, Webster AC, Pascual J. Interventions for infected cysts in people with autosomal dominant polycystic kidney disease (Protocol). Cochrane Database of Systematic Reviews 2014, Issue 1. Art. No.: CD010946. DOI: 10.1002/14651858.CD010946.

Author Information

  1. 1

    Hospital del Mar-IMIM, Department of Nephrology, Barcelona, Spain

  2. 2

    The University of Sydney, Sydney School of Public Health, Sydney, NSW, Australia

  3. 3

    The University of Sydney at Westmead, Centre for Transplant and Renal Research, Westmead Millennium Institute, Westmead, NSW, Australia

  4. 4

    The Children's Hospital at Westmead, Cochrane Renal Group, Centre for Kidney Research, Westmead, NSW, Australia

*Nuria Montero, Department of Nephrology, Hospital del Mar-IMIM, Passeig Marítim 25-29, Barcelona, 08003, Spain. nuriamonteroperez@gmail.com.

Publication History

  1. Publication Status: New
  2. Published Online: 29 JAN 2014

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Background

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
 

Description of the condition

Polycystic kidney disease (PKD) is a genetic disorder where faulty genes result in the growth of multiple fluid-filled cysts in the kidney. These cysts grow in size as they accumulate fluid. There are different types of PKD: they may be congenital or acquired, inherited, some may not be clinically relevant, while others may lead to severe complications. The most common cause of PKD is the autosomal dominant form (ADPKD) and is the most common hereditary kidney disease. It affects 1/400 to 1/1000 live births and is a leading cause of ESKD, and a common indication for dialysis or kidney transplantation. It accounts for between 2.4% to 12% of all people starting renal replacement therapy (RRT) (ANZDATA 2011; ERA-EDTA 2009; RMRC 2010; Tahvanainen 2005; USRDS 2011). Kidney failure requiring RRT occurs in approximately 50% of patients and typically develops in the fourth to sixth decade of life (Torres 2008). In ADPKD, in addition to the presence of hundreds to thousands of kidney cysts, cysts are also common in the liver, pancreas and intestine. As a consequence of the structural deformities, kidney complications of this disease arise. Some of these are: hypertension, haematuria, polyuria, flank pain and tendency to recurrent urinary tract infections and kidney stones. These fluid-filled cysts may collect blood after mild or severe trauma, may be the site of pyogenic infection or, in rare cases, could develop a malignant neoplasm (Grantham 2008; Wilson 2004). In ADPKD liver cysts develop later than kidney cysts, with a steady increase in frequency with advancing age, and are more common in women (Chauveau 2000). The majority of these patients report no liver symptoms, although no accurate assessment on the prevalence of liver symptoms has been published. A single centre reported 21% of polycystic patients on dialysis experienced kidney complications: mainly cyst infection, intracystic haemorrhage, post-traumatic rupture or cyst carcinoma (Chauveau 2000; Telenti 1990).

It has been estimated that 30% to 50% of patients with ADPKD will have some sort of kidney infection during their lifetime (Alam 2009). In the particular case of transplant recipients, urinary tract infections are among the leading complication in recipients with ADPKD, and septicaemia the most frequent cause of death (Stiasny 2002), and cyst infections responsible for hospitalisation occurs in 9% of ADPKD patients. An infected cyst and acute pyelonephritis are the most common kidney infections, while complications such as a perinephric abscess and bacteraemia can also occur. Diagnosing infected cysts is a challenge despite improvements in clinical, biological and imagining advances because of the lack of non-specific clinical symptoms, the limitations of current imaging procedures, and no radiologic gold standard for diagnosing infected cysts (Jouret 2012). It has been estimated that cyst infection rates are approximately 0.01 episodes/patient/year (Gibson 1998; Sallee 2009; Sklar 1987).

 

Description of the intervention

Cyst infections are serious problems often requiring hospitalisation and aggressive antimicrobial therapy. Despite the fact that cyst infection is one of the most frequent complications of ADPKD, published data are scant (Sallee 2009). The treatment of this complication is hampered by the difficultly in identifying the infective organism and the infected cyst itself, the fact that some of these patients are oliguric or anuric, and the poor penetration of the antibiotics into the kidney cysts.

Treatment of cysts infections can be difficult and significant morbidity, mortality and complications, notably the development of abscesses, have been described (Gibson 1998). The optimal duration of therapy for infected cysts is unclear and in some cases, such as in large (diameter > 5 cm) infected cysts, antibiotics alone are not sufficient to successfully treat the infection, and cyst drainage may be indicated (Akinci 2008; Bennett 1987; Rosenfeld 2002).

 

How the intervention might work

There are two groups of antibacterial drugs: bacteriostatic and bactericidal. Bacteriostatic drugs slow the growth or reproduction of micro-organisms and require the aid of host's defences to clear the infecting micro-organism. If the host's defences are impaired locally at the site of infection, as it happens inside the cysts, the residual pathogen resumes growth after the bacteriostatic drug has been stopped and the infection reoccurs. Bacterial infection in these circumstances requires use of bactericidal drugs (which kill the bacteria). Antibiotic concentrations at the centre of the infected cysts are much lower than in serum, which confers an inherent resistance to antimicrobial agents. Drugs that are bind strongly to serum protein may have reduced antibacterial activity in serum and not penetrate tissues as well as drugs that are less protein bound (Levison 2004). In these cases, the results of the minimal inhibitory concentration and minimal bactericidal concentration may not predict the in vivo effect. Liphophilic compounds, such as ciprofloxacin, new quinolones, trimethoprim-sulphamethoxazole, and chloramphenicol, which can accumulate in the kidney cysts, do not achieve satisfactory therapeutic levels inside the infected cyst even with high dosing (Bennett 1985: Chow 2005; Elzinga 1987; Elzinga 1988; Hiyama 2006; Muther 1981; Rossi 1993; Schwab 1983; Schwab 1985; Schwab 1986). It is also important to consider the peak serum level of free drug after a particular dose regimen and serum half-life of the drug, to predict efficacy. Moreover, some interventional approaches have been implemented such as ultrasonography-guided intracystic injection of antibiotics (Saedi 2009), percutaneous puncture or surgical decompression (Akinci 2008; Bennett 1987; Chehval 1995; Elzinga 1992b; Elzinga 1992a; Elzinga 1993; Waters 1979), drainage with alcohol sclerosis or laparoscopic unroofing (Lee 2003).

 

Why it is important to do this review

Recent research has been focused on the genetics and pathophysiology of ADPKD and on promising therapies aimed at slowing cyst initiation or expansion. Cyst infection involves the use of important hospital resources, morbidity is high and it affects the quality of life of the patients. Although infection of a single cyst within a polycystic kidney is one of the most common and potentially serious complication of this disease, and it has been reported that infection is the most common cause of death in ADPKD (Fick 1995), there is no evidence-based strategy for its management.

 

Objectives

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest

This review aims to look at the benefits and harms of the currently available treatment options for infected kidney and liver cysts in patients with ADPKD.

 

Methods

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
 

Criteria for considering studies for this review

 

Types of studies

  • All randomised controlled trials (RCTs) and quasi-RCTs (RCTs in which allocation to treatment was obtained by alternation, use of alternate medical records, date of birth or other predictable methods) looking at interventions directed at treatment of cyst infection in ADPKD will be included.
  • Observational cohort studies looking at interventions directed at treatment of cyst infection in ADPKD will also be included and separately analysed.

 

Types of participants

 

Inclusion criteria

All patients with ADPKD (men, women, any age, with or without chronic kidney disease (CKD), kidney transplant recipients) with a diagnosis of infected kidney or liver cysts (including those with a concomitant infected cyst anywhere else).

The diagnosis of cyst infections in patients with ADPKD is made complex and difficult. Although the review will not be limited by the following criteria and we will accept any definition described in the reports, the following diagnostic criteria have been proposed for cyst infection (Desouza 2009; Jouret 2012; Sallee 2009; Sklar 1987).

  • Presence of a cyst aspiration showing evidence of infection (neutrophil debris or micro-organism or both).
  • Presence of all of the following features: fever (temperature 38.5°C for three days), abdominal pain (particularly a palpable area of kidney or liver tenderness), increased C-reactive protein (CRP > 50 mg/L), and the absence of any significant recent intracystic bleeding (based on the results of an abdominal computed tomography (CT) scan) or other causes of fever.
  • Presence of bacteraemia or fungaemia.
  • Positive kidney ultrasound data detecting debris with a thick wall or a distal acoustic enhancement or both in at least one cyst.
  • Positive kidney CT scan and magnetic resonance imaging (MRI) data detecting enhanced wall thickening or perilesional inflammation or both in at least one cyst.
  • Positive positron emission computed tomography (18FDG-PET/CT) or positron emission (18FDG-PET) scan data detecting focus of increased glucose analogue 18FDG uptake in the kidney.

 

Exclusion criteria

Patients with another abdominal complication such as cyst haemorrhage, pyelonephritis, kidney graft infection in kidney transplant recipients, and non-cystic abdominal infection (e.g. angiocholitis, diverticulitis).

 

Types of interventions

  1. Medical treatments could include:
    • different types of antibiotics (antibiotic versus different antibiotic);
    • different doses;
    • different frequency (once versus twice versus three times a week);
    • different duration (short versus long therapy);
    • different routes of administration (intravenous versus oral therapy); and
    • monotherapy versus dual therapy.
  2. Surgical or radiological drainage (including percutaneous injection and sclerotherapy)
  3. Nephrectomy (open and endoscopic techniques)
  4. Medical treatment plus surgical or radiological drainage of infected cysts versus antibiotic or drainage alone
  5. Antibiotic versus surgical or radiological drainage
  6. Antibiotic versus nephrectomy
  7. Surgical or radiological drainage versus nephrectomy

 

Types of outcome measures

Outcomes will not be considered part of the eligibility criteria.

 

Primary outcomes

  1. Infection resolution: sterile blood or urine cultures, or both (days)
  2. Treatment failure
    • Persistent positive blood or urine cultures, or both, after completion of antibiotics
    • Recurrence of infection after initial eradication of organism (i.e. relapse with the same organism or reinfection with a different one confirmed by bacterial growth in the urine, or blood or both)
    • Microbial resistance: percentage of pathogens resistant to the study drug two to eight weeks after start of treatment and proportion of subjects that developed resistance (detect organism in cultures) during the treatment period up to eight weeks after starting treatment
    • Requirement of change of therapy
    • Requirement of surgical intervention
  3. Mortality related to infection  

 

Secondary outcomes

  1. Clinical outcomes: fever (days to resolution); time of disappearance of symptoms (days); haematogenous infection (positive blood cultures); need for blood transfusion (number of red blood cell concentrates); need for vasoactive drugs (yes or no); kidney perforation (yes or no)
  2. Duration of therapy (weeks) and hospitalisation (days)
  3. Laboratory findings (initial and at the end of the treatment): creatinine, leucocytes, CRP, organism involved
  4. Reduction in cyst size or volume (mm)
  5. Time to resolution: time of normalization of the images obtained by ultrasound (US), CT, PET/CT or MRI and normalization of the CRP.
  6. Quality of life (whatever measure used); pain intensity (location and frequency)
  7. Adverse effects of medication including urticaria, gastrointestinal reaction, discontinuation of treatment
  8. Economic costs of treatment

 

Search methods for identification of studies

 

Electronic searches

We will search the Cochrane Renal Group's Specialised Register through contact with the Trials' Search Co-ordinator using search terms relevant to this review. The Cochrane Renal Group’s Specialised Register contains studies identified from the following resources.

  1. Monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL).
  2. Weekly searches of MEDLINE OVID SP.
  3. Handsearching of kidney-related journals & the proceedings of major kidney conferences.
  4. Searching of the current year of EMBASE OVID SP.
  5. Weekly current awareness alerts for selected kidney journals.
  6. Searches of the International Clinical Trials Register (ICTRP) Search Portal & ClinicalTrials.gov.

Studies contained in the Specialised Register are identified through search strategies for CENTRAL, MEDLINE, and EMBASE based on the scope of the Cochrane Renal Group. Details of these strategies as well as a list of handsearched journals, conference proceedings and current awareness alerts are available in the Specialised Register section of information about the Cochrane Renal Group.

See Appendix 1 for search terms used in strategies for this review.

 

Searching other resources

  1. Reference lists of clinical practice guidelines, review articles and relevant studies.
  2. Letters or emails seeking information about unpublished or incomplete studies to investigators known to be involved in previous studies.

 

Data collection and analysis

 

Selection of studies

The search strategy described will be used to obtain titles and abstracts of studies that may be relevant to the review. The titles and abstracts will be screened independently by two authors, who will discard studies that are not applicable, however studies and reviews that might include relevant data or information on studies will be retained initially. Two authors will independently assess retrieved abstracts and, if necessary the full text, of these studies to determine which studies satisfy the inclusion criteria.

 

Data extraction and management

Data extraction will be carried out independently by two authors using standard data extraction forms. Studies reported in non-English, non-Spanish, non-French, or non-Italian language journals will be translated before assessment. Where more than one publication of one study exists, reports will be grouped together and the publication with the most complete data will be used in the analyses. Where relevant outcomes are only published in earlier versions these data will be used. Any discrepancy between published versions will be highlighted.

 

Assessment of risk of bias in included studies

The following items will be independently assessed by two authors using the risk of bias assessment tool (Higgins 2011) (see Appendix 2).

  • Was there adequate sequence generation (selection bias)?
  • Was allocation adequately concealed (selection bias)?
  • Was knowledge of the allocated interventions adequately prevented during the study (detection bias)?
    • Participants and personnel
    • Outcome assessors
  • Were incomplete outcome data adequately addressed (attrition bias)?
  • Are reports of the study free of suggestion of selective outcome reporting (reporting bias)?
  • Was the study apparently free of other problems that could put it at a risk of bias?

For assessing the quality of non-randomised studies we will use the Newcastle-Ottawa Scale with the following items (Higgins 2011).

  • Cohort studies

    • Was the exposed cohort representative of the population of PKD?
    • Was the selection of the non-exposed cohort adequate?
    • Was valid the ascertainment of exposure and that the outcome of interest was not present at start of study?
    • Were the cohorts comparable on the basis of the design or analysis?
    • Was the outcome correctly assessed?
    • Was follow-up long enough for outcomes to occur considering in this study that it will be sufficient for one month?
    • Was the follow-up of the exposed and non-exposed cohorts adequate to ensure that losses are not related to either the exposure or the outcome?

  • Case control studies:

    • Is the case definition adequate?
    • Are the cases representative?
    • Are the controls selected from the same population? Is there specified the history of outcome?
    • Are cases and controls comparable?
    • Was valid the ascertainment of exposure?
    • Is there specified a non-response rate?

 

Measures of treatment effect

The data will be disaggregated for kidney, liver and other cysts. For dichotomous outcomes (persistent bacteriuria or bacteraemia after completion of antibiotics, recurrence of infection after initial eradication, mortality related to infection, clinical outcomes, adverse effects) results will be expressed as risk ratios (RR) with 95% confidence intervals (CI). Where continuous scales of measurement are used to assess the effects of treatment (microbial resistance, duration of the therapy or the hospitalisation, laboratory finding, reduction cyst volume, quality of life, economic costs of the treatment), the mean difference (MD) will be used, or the standardised mean difference (SMD) if different scales have been used (quality of life or pain intensity). For time to event data (time of disappearance of symptoms, normalization of CRP, days to get sterile urine culture after completion of antibiotics) we will express the intervention effect as an estimated of the log hazard ratio obtained from statistics computed during a log-rank analysis. In case it is necessary to deal with change scores (reduction cyst size or volume), the statistical approach will be to include the baseline outcome measurements as a covariate in a regression model or analysis of covariance (ANCOVA) and will be included in the meta-analysis using the generic inverse-variance method. We will approach time-to-event outcomes as continuous variables (mean days until an event occurs). For counts and rates the results of a study may be expressed as a RR and the (natural) logarithms of the rate ratios may be combined across studies using the generic inverse-variance method (Higgins 2011).

 

Unit of analysis issues

The unit of analysis issues will be people with infected cysts not the cysts themselves. So if the identified studies report the number of infected cysts we will change the measurement to people with infected cysts. Cross-over studies will not be included. Although it is highly unlikely to find other studies with non-standard designs, if a cluster-RCT is included, statistical advice will be asked for determining the most appropriate method to use and if studies with multiple intervention groups are included, they will be analysed combining groups to create a single pair-wise comparison.

 

Dealing with missing data

Any further information required from the original author will be requested by written correspondence (e.g. emailing the corresponding author) and any relevant information obtained in this manner will be included in the review. Evaluation of important numerical data such as screened, randomised patients as well as intention-to-treat (ITT), as-treated and per-protocol (PP) population will be carefully performed. Attrition rates, for example drop-outs, losses to follow-up and withdrawals will be investigated. Issues of missing data and imputation methods (for example, last-observation-carried-forward (LOCF)) will be critically appraised (Higgins 2011).

 

Assessment of heterogeneity

Heterogeneity will be analysed using a Chi² test on N-1 degrees of freedom, with an alpha of 0.05 used for statistical significance and with the I² test (Higgins 2003). I² values of 25%, 50% and 75% correspond to low, medium and high levels of heterogeneity.

 

Assessment of reporting biases

If possible, funnel plots will be used to assess for the potential existence of small study bias (Higgins 2011).

 

Data synthesis

Data will be pooled using the random-effects model.

 

Subgroup analysis and investigation of heterogeneity

Subgroup analysis will be used to explore possible sources of heterogeneity (e.g. participants (stage of CKD, haemodialysis or peritoneal dialysis, kidney transplant recipients, diabetes), interventions, organism involved, diagnostic imaging technique used (CT, MRI, 18FDG-PET, US); localisation of infected cyst, concomitant liver or other cysts infections and haematogenous infection). Heterogeneity among participants could be related to age and renal pathology (e.g. stage of CKD, haemodialysis or peritoneal dialysis patients or kidney transplant recipients, diabetes). Heterogeneity in treatments could be related to prior agent(s) used and the agent, dose, route of administration and duration of therapy. Adverse effects will be tabulated and assessed with descriptive techniques, as they are likely to be different for the various agents used. Where possible, the risk difference with 95% CI will be calculated for each adverse effect, either compared to no treatment or to another agent.

 

Sensitivity analysis

We will perform sensitivity analyses in order to explore the influence of the following factors on effect size.

  • Repeating the analysis excluding unpublished studies.
  • Repeating the analysis taking account of risk of bias, as specified above.
  • Repeating the analysis excluding any very long or large studies to establish how much they dominate the results.
  • Repeating the analysis excluding studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), and country.

 

Acknowledgements

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest

We would like to thank Narelle Willis and Ruth Mitchell for their editorial advice and searching methods help during the preparation of this protocol. We are also grateful to the Spanish Society of Nephrology for its economical support given to NM and to the Cochrane Renal Group and Centre of Kidney Research and people working there (special mention: Jonathan Craig and Pamela A Lopez-Vargas) to provide all the knowledge and resources to carry out this protocol. We would also like to thank the referees for their comments and feedback.

 

Appendices

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
 

Appendix 1. Electronic search strategies


DatabaseSearch terms

CENTRAL
  1. (polycystic next kidney*):ti,ab,kw
  2. (cyst* near/3 kidney*):ti,ab,kw
  3. (ADPKD or PKD or ARPKD or APKD):ti,ab,kw
  4. (#1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8 OR #9)
  5. infect*:ti,ab,kw
  6. bacter*emi*:ti,ab,kw
  7. (UTI or UTIs):ti.ab.kw
  8. #5 or #6 or #7
  9. (complicated next cyst*):ti,ab,kw
  10. (liver near/3 cyst*):ti,ab,kw
  11. #9 or #10
  12. #4 and (#8 or #11)

MEDLINE
  1. exp Kidney Diseases, Cystic/
  2. polycystic kidney$.tw.
  3. (cyst$ adj3 kidney$).tw.
  4. (ADPKD or PKD or ARPKD or APKD).tw.
  5. or/1-6
  6. Infection/
  7. Bacterial Infections/
  8. Bacteremia/
  9. Urinary Tract Infections/
  10. exp Gram-Positive Bacterial Infections/
  11. exp Gram-Negative Bacterial Infections/
  12. infect$.tw.
  13. bacter?emi$.tw.
  14. (UTI or UTIs).tw.
  15. or/6-14
  16. complicated cyst$.tw
  17. (liver adj3 cyst*).tw.
  18. or/16-17
  19. 5 and (15 or 18)

EMBASE
  1. kidney polycystic disease/
  2. polycystic kidney$.tw.
  3. (cyst$ adj3 kidney$).tw.
  4. (ADPKD or PKD or ARPKD or APKD).tw.
  5. or/1-6
  6. infection/
  7. bacterial infection/
  8. bacteremia/
  9. urinary tract infection/
  10. Gram positive infection/
  11. Gram negative infection/
  12. infect$.tw.
  13. bacter?emi$.tw.
  14. (UTI or UTIs).tw.
  15. exp Staphylococcus infection/
  16. or/8-15
  17. complicated cyst$.tw.
  18. (liver adj3 cyst*).tw.
  19. 5 and (16 or 18)



 

Appendix 2. Risk of bias assessment tool


Potential source of biasAssessment criteria

Random sequence generation

Selection bias (biased allocation to interventions) due to inadequate generation of a randomised sequence
Low risk of bias: Random number table; computer random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots; minimization (minimization may be implemented without a random element, and this is considered to be equivalent to being random).

High risk of bias: Sequence generated by odd or even date of birth; date (or day) of admission; sequence generated by hospital or clinic record number; allocation by judgement of the clinician; by preference of the participant; based on the results of a laboratory test or a series of tests; by availability of the intervention.

Unclear: Insufficient information about the sequence generation process to permit judgement.

Allocation concealment

Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment
Low risk of bias: Randomisation method described that would not allow investigator/participant to know or influence intervention group before eligible participant entered in the study (e.g. central allocation, including telephone, web-based, and pharmacy-controlled, randomisation; sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes).

High risk of bias: Using an open random allocation schedule (e.g. a list of random numbers); assignment envelopes were used without appropriate safeguards (e.g. if envelopes were unsealed or non-opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure.

Unclear: Randomisation stated but no information on method used is available.

Blinding of participants and personnel

Performance bias due to knowledge of the allocated interventions by participants and personnel during the study
Low risk of bias: No blinding or incomplete blinding, but the review authors judge that the outcome is not likely to be influenced by lack of blinding; blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken.

High risk of bias: No blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding; blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding.

Unclear: Insufficient information to permit judgement

Blinding of outcome assessment

Detection bias due to knowledge of the allocated interventions by outcome assessors.
Low risk of bias: No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding; blinding of outcome assessment ensured, and unlikely that the blinding could have been broken.

High risk of bias: No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding; blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding.

Unclear: Insufficient information to permit judgement

Incomplete outcome data

Attrition bias due to amount, nature or handling of incomplete outcome data.
Low risk of bias: No missing outcome data; reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias); missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size; missing data have been imputed using appropriate methods.

High risk of bias: Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size; ‘as-treated’ analysis done with substantial departure of the intervention received from that assigned at randomisation; potentially inappropriate application of simple imputation.

Unclear: Insufficient information to permit judgement

Selective reporting

Reporting bias due to selective outcome reporting
Low risk of bias: The study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way; the study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre-specified (convincing text of this nature may be uncommon).

High risk of bias: Not all of the study’s pre-specified primary outcomes have been reported; one or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. subscales) that were not pre-specified; one or more reported primary outcomes were not pre-specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect); one or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis; the study report fails to include results for a key outcome that would be expected to have been reported for such a study.

Unclear: Insufficient information to permit judgement

Other bias

Bias due to problems not covered elsewhere in the table
Low risk of bias: The study appears to be free of other sources of bias.

High risk of bias: Had a potential source of bias related to the specific study design used; stopped early due to some data-dependent process (including a formal-stopping rule); had extreme baseline imbalance; has been claimed to have been fraudulent; had some other problem.

Unclear: Insufficient information to assess whether an important risk of bias exists; insufficient rationale or evidence that an identified problem will introduce bias.



 

Contributions of authors

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest

  1. Draft the protocol: NM, LS, AW, JP
  2. Study selection: NM, LS
  3. Extract data from studies: NM, LS
  4. Enter data into RevMan: NM
  5. Carry out the analysis: NM
  6. Interpret the analysis: NM, LS, AW, JP
  7. Draft the final review: NM
  8. Disagreement resolution: JP
  9. Update the review: NM

 

Declarations of interest

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest

  • NM, LS, AW: none known
  • JP has had advisory board or clinical trial involvement or both with Novartis, Roche, Amgen and Abbott; he has also been an invited speaker at national and international meetings sponsored by Novartis.

References

Additional references

  1. Top of page
  2. Abstract
  3. Background
  4. Objectives
  5. Methods
  6. Acknowledgements
  7. Appendices
  8. Contributions of authors
  9. Declarations of interest
  10. Additional references
Akinci 2008
  • Akinci D, Turkbey B, Yilmaz R, Akpinar E, Ozmen MN, Akhan O. Percutaneous treatment of pyocystis in patients with autosomal dominant polycystic kidney disease. Cardiovascular & Interventional Radiology 2008;31(5):926-30. [MEDLINE: 18196333]
Alam 2009
ANZDATA 2011
  • Grace B, Hurst K, McDonald S. Chapter 2: New patients commencing treatments in 2010. In: ANZDATA Report 2011. http://www.anzdata.org.au/anzdata/AnzdataReport/34thReport/2011c02_newpatients_v1.5.pdf (accessed 28 November 2013).
Bennett 1985
  • Bennett WM, Elzinga L, Pulliam JP, Rashad AL, Barry JM. Cyst fluid antibiotic concentrations in autosomal-dominant polycystic kidney disease. American Journal of Kidney Diseases 1985;6(6):400-4. [MEDLINE: 4073019]
Bennett 1987
  • Bennett WM, Elzinga L, Golper TA, Barry JM. Reduction of cyst volume for symptomatic management of autosomal dominant polycystic kidney disease. Journal of Urology 1987;137(4):620-2. [MEDLINE: 2435925]
Chauveau 2000
  • Chauveau D, Fakhouri F, Grunfeld JP. Liver involvement in autosomal-dominant polycystic kidney disease: therapeutic dilemma. Journal of the American Society of Nephrology 2000;11(9):1767-75. [MEDLINE: 10966503]
Chehval 1995
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