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Annals of Internal Medicine | 2016

Comparative Effect of Contrast Media Type on the Incidence of Contrast-Induced Nephropathy: A Systematic Review and Meta-analysis.

John Eng; Renee F Wilson; Rathan M. Subramaniam; Allen Zhang; Catalina Suarez-Cuervo; Sharon Turban; Michael J Choi; Cheryl Sherrod; Susan Hutfless; Emmanuel Iyoha; Eric B Bass

Iodine contrast media are essential to many diagnostic and therapeutic procedures that involve imaging. An important potential side effect is contrast-induced nephropathy (CIN), most commonly defined in past studies as an increase in serum creatinine levels of more than 25% or 44.2 mol/L (0.5 mg/dL) within 3 days of intravascular contrast administration in the absence of an alternative cause (1). The precise mechanism of CIN is not entirely understood. The leading theories are that it results from hypoxic injury to the renal tubules induced by renal vasoconstriction or by direct cytotoxic effects of contrast media (2, 3); alternatively, some experts have arguedand recent evidence suggeststhat acute kidney injury occurring after intravascular contrast administration is caused by coexisting risk factors and is only coincidentally related to the contrast media, especially when administered intravenously (4, 5). Regardless of the cause, acute kidney injury after intravascular contrast administration remains a major concern for referring clinicians. Osmolality of contrast media is a key factor determining its tolerability (6). Since the 1990s, low-osmolar contrast media (LOCM) (2 to 3 times plasma osmolality) have been the standard of care for intravascular injection. A newer class of intravascular contrast, iso-osmolar contrast media (IOCM), is isotonic to plasma. Iodixanol is the only IOCM available for intravascular injection. The literature contains conflicting reports about whether iodixanol is associated with less risk for CIN than LOCM (7, 8). International guidelines from the Kidney Disease: Improving Global Outcomes Acute Kidney Injury Work Group mention IOCM and LOCM, but they do not make recommendations about selection between them (9). We did a systematic review of randomized, controlled trials (RCTs) to determine the comparative effects of different types of intravascular contrast media on CIN risk in patients having diagnostic imaging studies or image-guided procedures. We hypothesized that updating past reviews with more recent RCTs may help us understand conflicting reports about CIN risk. Some reports suggest that intra-arterial administration may be associated with greater risk than intravenous administration (4, 10, 11), so we also investigated whether the comparative effects vary according to the route of administration. Methods We developed and followed a review protocol, which is included in the full technical report on which this article is based (12). Data Sources and Searches We searched (without date or language restrictions) PubMed, EMBASE, and the Cochrane Library for RCTs published through 30 June 2015, as well as the Scopus database for conference proceedings and other reports (Appendix Table 1). We also reviewed the reference lists of relevant articles and related systematic reviews, searched ClinicalTrials.gov to identify ongoing studies, and asked an external expert panel to identify trials missing from our final list of eligible articles. Appendix Table 1. Search Strategy Study Selection We selected all RCTs that compared 1 or more contrast media types (LOCM or IOCM) with CIN incidence as the main outcome in patients having diagnostic imaging or image-based therapeutic procedures. Studies had to report the incidence of CIN based on serum creatinine levels or glomerular filtration rates at baseline and within 72 hours of contrast injection. Studies could involve patients of any age and preprocedure risk for CIN. There were no restrictions on how the contrast classes were compared, so studies comparing different types of LOCM and those comparing LOCM with IOCM were included. Two reviewers independently screened titles and abstracts to identify articles for inclusion. If necessary, the full text of articles was reviewed. Articles in a language other than English were excluded at the full-text level. Discrepancies between the 2 reviewers that remained after full-text review were resolved by consensus. At random intervals during screening, quality checks were done to ensure that eligibility criteria were applied consistently. Data Extraction and Quality Assessment For each eligible study, 1 investigator extracted pertinent data about study characteristics, patient population, imaging procedure type, comparisons, results, and statistical analysis. A second investigator reviewed the extracted data for accuracy. Discrepancies between the 2 investigators were resolved by consensus. Article and data management were done within the DistillerSR Web service (Evidence Partners). Two reviewers independently assessed each studys risk of bias using the following 5 items from the Cochrane Risk of Bias Tool for randomized studies: allocation sequence generation, allocation concealment, investigator blinding, incomplete outcomes, and selective outcome reporting (13). Discrepancies were resolved by consensus. Data Synthesis and Analysis When evaluating changes in CIN risk, we followed published guidelines for selecting a minimally important clinical difference based on the overall observed event rate in the studies (14). Taking into consideration the potential effect of CIN on a patients overall health and well-being, the clinical experts on our team decided that a 25% reduction in the relative risk for CIN would be clinically important, which is consistent with the published guidance suggesting a range of reduction in relative risk of 20% to 30% in determining optimal information size (14). For each comparison in our review, the study team assigned a grade (high, moderate, low, or insufficient) for the strength of evidence (SOE) associated with the entire group of studies that represented the particular comparison. Grades for SOE were assigned by consensus of the senior study team members (J.E., R.W., R.S., and E.B.). This grading scheme considered all of the following domains in the Agency for Healthcare Research and Quality guidelines for comparative effectiveness reviews: study limitations, precision, directness, consistency, reporting bias, and magnitude of effect (15). The study limitations domain was assessed by examining the risk-of-bias items for each study involved in the comparison. Study limitations were considered high if more than half of the studies in a group scored negatively in at least 1 of the risk-of-bias items, low if more than half of the studies in the group scored positively in all 5 risk-of-bias items, or medium if neither the high nor the low criteria were met. The precision domain was assessed by following guidance from the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group (14). We rated a group of studies as precise if the total number of patients exceeded the optimum information size (14) and the 95% CI excluded a pooled relative risk of 1.0. If the total number of patients exceeded the optimum information size but the CI did not exclude a relative risk of 1.0, we only rated the evidence as precise if the CI excluded the possibility of a 25% minimally important clinical difference as defined previously (relative risk <0.75 or >1.25). For the main outcome of interest, CIN, we calculated an optimum information size of 2000 patients based on an expected 0.1 probability of CIN and a minimally important relative risk of less than 0.75 or greater than 1.25. The SOE of a group of studies was graded high if the study limitations domain was considered low and all other SOE domains were scored positively. The SOE was downgraded for each domain that was scored negatively. If the magnitude of effect was very large, the SOE was upgraded. We did de novo meta-analyses of all studies on a given comparison if study heterogeneity was not important by clinical, qualitative, and statistical criteria (16). We calculated pooled risks by using a random-effects model and the DerSimonianLaird method (17). We used a funnel plot and the Harbord modified test for small study effects (18) to look for asymmetry in the reporting of results, which can be seen when publication bias exists. Analyses were done in Stata, version 13 (StataCorp). Role of the Funding Source The Agency for Healthcare Research and Quality selected the review topic and funded this research under a contract. A representative from the Agency provided technical assistance during creation of the full evidence report on which this article is based and provided comments on draft versions of that report (12). The Agency did not directly participate in the literature search; determination of study eligibility criteria; data collection, analysis, or interpretation; or preparation, review, or approval of the manuscript for publication. Results The literature search revealed 29 RCTs for summary and analysis (Figure 1). Five RCTs compared 2 or more types of LOCM in 826 patients (Appendix Table 2) (1923). Twenty-five RCTs compared the IOCM iodixanol with 1 or more types of LOCM in 5053 patients (Appendix Table 2) (19, 2447). One RCT reported data on both types of comparisons (19). In the 5 RCTs that compared LOCM, 4 studies scored negatively in 1 or more of the 5 risk-of-bias items (Appendix Table 3). In the 25 RCTs comparing iodixanol and LOCM, all studies scored negatively in 1 or more of the 5 risk-of-bias items (Appendix Table 4). Of the 29 RCTs included in our review, 14 (48%) studies (19, 20, 29, 3338, 4043, 45) received funding support from industry sources, all of which were contrast media manufacturers. Figure 1. Summary of evidence search and selection. * Sum of reasons for exclusion exceeds 443 because reviewers were not required to agree on the reason. Appendix Table 2. Study Characteristics Appendix Table 3. Risk of Bias for RCTs Comparing LOCMs* Appendix Table 4. Risk of Bias for RCTs Comparing Iodixanol and LOCMs* No study comparing 2 LOCM reported a statistically significant or clinically important difference between study groups in the incidence of CIN or a related measure of renal func


Clinical Journal of The American Society of Nephrology | 2017

Renal functional outcomes after surgery, ablation, and active surveillance of localized renal tumors: A systematic review and meta-analysis

Hiten D. Patel; Phillip M. Pierorazio; Michael H. Johnson; Ritu Sharma; Emmanuel Iyoha; Mohamad E. Allaf; Eric B Bass; Stephen M. Sozio

BACKGROUND AND OBJECTIVES Management strategies for localized renal masses suspicious for renal cell carcinoma include radical nephrectomy, partial nephrectomy, thermal ablation, and active surveillance. Given favorable survival outcomes across strategies, renal preservation is often of paramount concern. To inform clinical decision making, we performed a systematic review and meta-analysis of studies comparing renal functional outcomes for radical nephrectomy, partial nephrectomy, thermal ablation, and active surveillance. DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS We searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 1997 to May 1, 2015 to identify comparative studies reporting renal functional outcomes. Meta-analyses were performed for change in eGFR, incidence of CKD, and AKI. RESULTS We found 58 articles reporting on relevant renal functional outcomes. Meta-analyses showed that final eGFR fell 10.5 ml/min per 1.73 m2 lower for radical nephrectomy compared with partial nephrectomy and indicated higher risk of CKD stage 3 or worse (relative risk, 2.56; 95% confidence interval, 1.97 to 3.32) and ESRD for radical nephrectomy compared with partial nephrectomy. Overall risk of AKI was similar for radical nephrectomy and partial nephrectomy, but studies suggested higher risk for radical nephrectomy among T1a tumors (relative risk, 1.37; 95% confidence interval, 1.13 to 1.66). In general, similar findings of worse renal function for radical nephrectomy compared with thermal ablation and active surveillance were observed. No differences in renal functional outcomes were observed for partial nephrectomy versus thermal ablation. The overall rate of ESRD was low among all management strategies (0.4%-2.8%). CONCLUSIONS Renal functional implications varied across management strategies for localized renal masses, with worse postoperative renal function for patients undergoing radical nephrectomy compared with other strategies and similar outcomes for partial nephrectomy and thermal ablation. Further attention is needed to quantify the changes in renal function associated with active surveillance and nephron-sparing approaches for patients with preexisting CKD.


Series:AHRQ Comparative Effectiveness Reviews | 2016

Diabetes Medications for Adults With Type 2 Diabetes: An Update

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur


Archive | 2016

Management of Renal Masses and Localized Renal Cancer

Phillip M. Pierorazio; Michael H. Johnson; Hiten D. Patel; Stephen M. Sozio; Ritu Sharma; Emmanuel Iyoha; Eric B Bass; Mohamad E. Allaf


Series:AHRQ Technology Assessments | 2015

Use of Cardiac Resynchronization Therapy in the Medicare Population

John Rickard; Henry J. Michtalik; Ritu Sharma; Zackary Berger; Emmanuel Iyoha; Ariel R. Green; Nowreen Haq; Karen A. Robinson


Archive | 2016

Addendum and Errata

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur


Archive | 2016

Table 1, Characteristics of medications included in this report

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur


Archive | 2016

Table 127, Evidence gaps and future research needs for the comparative effectiveness and safety of diabetes medications for adults with type 2 diabetes

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur


Archive | 2016

Figure 3, Duration of followup for randomized controlled trials comparing the effects of diabetes medications among adults with type 2 diabetes (N = 177)

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur


Archive | 2016

Table A, Priority medication comparisons included for each Key Question

Shari Bolen; Eva Tseng; Susan Hutfless; Jodi B. Segal; Catalina Suarez-Cuervo; Zackary Berger; Lisa M. Wilson; Yue Chu; Emmanuel Iyoha; Nisa M. Maruthur

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Zackary Berger

Johns Hopkins University School of Medicine

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Susan Hutfless

Johns Hopkins University

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Shari Bolen

Johns Hopkins University School of Medicine

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Eva Tseng

Johns Hopkins University

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Jodi B. Segal

Johns Hopkins University

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Lisa M. Wilson

Johns Hopkins University

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Yue Chu

Johns Hopkins University

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Ritu Sharma

Johns Hopkins University

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