Friday, March 16, 2018

Progress in Prognostic Risk Stratification in Autosomal Dominant Polycystic Kidney Disease

Educating patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD) is unique, as patients typically witness the course of the disease in their affected family members. This is often a parent, but due to the complexities of life including difficult family dynamics, estrangement, or early fatality from other causes (ie. trauma, cancer, cardiovascular disease), it may also be a sibling, parent’s siblings, or a grandparent. At first assessment, they commonly ask “Am I going to end up like them?” Contrarily, up to 15% of patients present with no family history (PMID: 28522688), and the delivery of an ADPKD diagnosis and prognosis can be devastating and seemingly out of the blue.

Relatively recently, many nephrologists felt there was no therapeutic options to offer patients with ADPKD, resulting in therapeutic nihilism until patients reached advanced stages of chronic kidney disease. Following TEMPO (PMID: 23121377) and REPRISE (PMID: 29105594), which reported significant reductions in the rate of GFR decline and kidney growth but with significant cost and side effects, and awaiting an FDA decision projected for April 2018, nephrologists will increasingly need to decide whether “the juice is worth the squeeze”.

Precision medicine aims to identify the best patient for a particular treatment using information from patient history, examination, and bloodwork, as well as incorporating more advanced imaging, genetics, and biomarkers, as well as patient preferences and values. Providing an accurate prognosis to patients is important for selecting the right interventions, but also for life planning for the patient and resource planning for the system.

Diagnosis can be made with ultrasound, especially in those with family history and age over 30, which has allowed time for cysts to grow. Assessment with Magnetic Resonance Imaging (MRI) including calculation of age and height adjusted Total Kidney Volume ( is the best method for ADPKD risk stratification (PMID: 24904092) and has been approved by the FDA as a prognostic enrichment biomarker for clinical trial design ( However, the terms of use include a specific disclaimer against use in clinical care. Furthermore, the economic ramifications of MRI screening of ADPKD patients needs to be considered.

                                                      From: Ekser andRigotti NEJM 2010

Genetic testing is increasingly available, and while costs are falling and our knowledge of the prognostic implications of mutation type is increasing, recommendations remain against widespread testing of all patients (PMID: 25786098). Cases where genetic testing may be of particular importance include: cases with unclear diagnosis (ie. loss of kidney function without enlargement); cases without family history; severe early onset disease; families with intrafamilial discordance; atypical lopsided or unilateral appearance; suspicion of another syndromic presentation (ie. nephronopthosis, autosomal dominant tubulointerstitial kidney disease, tuberous sclerosis) or exclusion of disease in a young patient by checking for a known familial mutation. Nonetheless, it is now recognized that patients with truncating PKD1 mutations (large deletions, nonsense, frameshift, and canonical splice site mutations) have the worst prognosis, followed by PKD1 non-truncating mutations (including inframe insertions/deletions and missense mutations), and PKD2 mutations (PMID: 26453610). After exhaustive screens, those without mutations detected tend to have the mildest disease. However, due to a high degree of allelic heterogeneity, determining if a rare mutation is in fact causal of ADPKD in a specific patient remains far from trivial and interpretation of sequencing results requires specific training and experience.

Future work is required to specifically identify who needs what testing (imaging, genetics, or both), and what the specific benefits are of obtaining either or both types of information. It appears quite likely that those with the greatest risk of disease progression towards kidney failure have the most to gain from disease modifying therapies, especially if they are associated with a therapeutic burden. Future predictive techniques will incorporate imaging and genetics and our growing knowledge of the cyst physiology and polycystin-1 and polycystin-2, and utilize tools such as artificial intelligence, to improve precision medicine care of patients with ADPKD.

Author:  Matthew Lanktree MD, PhD, Heritable Kidney Disease Post Doctoral Fellow, University Health Network, University of Toronto, Toronto, Ontario, Canada.

Wednesday, March 14, 2018

The Uncertainty of Monoclonal Gammopathies

I spend a lot of time discussing patients with renal disease and monoclonal gammopathies with my haematology colleagues, trying to figure out what is of ‘renal significance’ and ‘undetermined significance’. One of those discussions recently was around a normally well 70 year old lady. She presented with several pre-renal insults including a febrile illness, relative hypotension and NSAID use for joint pains. Her renal function rapidly deteriorated and she became oligoanuric requiring haemodialysis.  

Image result for immunotactoid GNAt a routine medical 4 months previously she was normotensive with normal renal function and no proteinuria.  Investigations during this admission revealed nephrotic range proteinuria and an IgG kappa paraprotein at 1g/L with a normal free light chain ratio.  Autoantibodies and cryoglobulins were negative. A renal biopsy showed diffuse endocapillary glomerulonephritis with immunoglobulin pseudo-thrombi in the capillaries and negative Congo Red staining.  Staining was positive for all immunoglobulins and C3. Electron microscopy showed organised sub-endothelial deposits of hollow microtubules of 40-50nm diameter in keeping with immunotactoid glomerulopathy (see image). A bone marrow showed no significant dysplasia, no light chain restriction and no evidence of myeloma. She was treated with high dose steroids and initially plasma exchange whilst results were returned.  Her renal function improved over the following week and she did not require further specific therapy given the absence of overt lymphoproliferative or autoimmune disease.
It is not surprising that we pick up a lot of monoclonal gammopathies in patients with deteriorating renal function or proteinuria as MGUS affects 3% of patients over the age of 50. Recent evidence suggests that MGUS progresses to myeloma or other plasma cell or lymphoproliferative disorders in 10% of patients at 10 years, and higher than this in those with an abnormal serum free light chain ratio or IgM paraprotein.
Monoclonal immunoglobulins or immunoglobulin-derived fragments can be deposited in the kidney in a number of patterns (previous RFN post from Nate):
  • Crystalline deposits: cast nephropathy in myeloma
  • Organised fibrillar deposits: AL amyloidosis (Congo Red stain positive)
  • Organised microtubular pattern: immunotactoid GN or type I cryoglobulinaemia.  Fibrillary GN is from polyclonal IgG deposition (not usually associated with a paraprotein) and on EM has slightly smaller fibrils (approx. 20nm in diameter) than immuntactoid GN.
  • Disorganised granular deposits as in LCDD and HCDD 

Immunotactoid GN usually presents in a more insidious pattern with hypertension, haematuria and proteinuria rather than acutely as in this case.  The straight, hollow tubules are over 30nm in diameter and are usually composed of crystallised monoclonal IgG. The diagnosis can be missed when EM is not performed.  It is usually secondary to lymphoproliferative diseases, typically CLL or B cell non-Hodgkin’s lymphoma but also MGUS. Treatment is based on the underlying disease, and in cases as this vigilance for progression is vital.  

Post by Ailish Nimmo

Tuesday, March 13, 2018

Assessing the risk of CKD progression using Kidney Failure Risk Equations

 “The best way to predict your future is to create it". Abraham Lincoln

Predicting the future is a tenuous concept and at face value is perhaps better suited to popular media and science fiction than medicine. We have an innate preoccupation with the future engendered since childhood and further developed throughout our early adult years. This is not an idle curiosity; at the crux of it is our desire to predict and plan for future challenges. It is this that is at the core of attempts to predict the future in healthcare; identifying risk factors for disease, identifying individuals at risk of disease progression and attempting to enable decision making for treatment in healthcare systems already under considerable service and financial demands.
The pioneering Framingham study was the benchmark study for risk prediction models in healthcare. Chronic kidney disease represents an equally significant health and economic burden, however it has not previously proved amenable to risk prediction models. Current risk stratification in CKD relies on eGFR. Unfortunately, use of eGFR may overestimate the severity of disease in CKD. In addition, eGFR decline may be non-linear and episodes of acute kidney injury may unpredictably shorten the time to ESKD.
CKD has represented a difficult challenge in creation of adequate risk prediction models. CKD is not a uniform entity—for many patients the presence of CKD may have no appreciable impact on their life whereas others will ultimately progress to ESKD. Timely and appropriate specialist referral is imperative to allow interventions and enable planning for renal replacement therapy. Scores that underestimate disease severity may result in inadequate preparation time resulting in patients “crash landing”, missed opportunities regarding slowing progression and multi-disciplinary team input. Overestimation of severity results in increased referrals to Nephrologists with a knock-on effect of increased waiting times, increased demands on the system, unnecessary patient anxiety and a potential delay in identification and treatment of those who will ultimately progress to kidney failure.
Prediction scores to determine which patients with CKD are likely to progress to ESKD would allow us to have patient-specific discussions regarding prognosis and would allow us to collaborate with primary care to select patients who need expedient specialist review. Given the importance of better ESKD risk progression, KDIGO Guidelines on CKD management recommend the use of risk models. The Kidney Failure Risk Equation (KFRE) has been shown to accurately predict the risk of progression in 2 large Canadian and 1 European cohort. 
  • Tangri et al developed multiple models of kidney failure risk in a cohort from Toronto and validated the equations a cohort in Vancouver incorporating clinical and laboratory data of patients with CKD 3-5 referred to nephrologists over a 7 year period. The abbreviated KFRE consists of four variables (age, sex, eGFR and albumin-to-creatinine ratio), and the full eight variable KFRE includes calcium, phosphate, bicarbonate and albumin. The eight variable KFRE showed modest gains compared with the 4-variable model. Unsurprisingly, the ESRD risk was much lower in those who had CKD stage 3 at baseline (3%) compared to those who were already at CKD stage 5 at baseline (60%). About 40% had diabetes and 90% had hypertension. Early criticisms of the KFRE involved missing data in both the derivation and validation cohorts, and the cohort selected were already under the care of the nephrologist.
  • The KFRE was then assessed in a multi-national cohort encompassing 31 cohorts of 721,357 patients with CKD 3-5 in more than 30 countries spanning 4 continents. This meta-analysis showed that original risk equations achieved excellent discrimination, however a calibration factor was required in the non-American cohort.  
  • Peeters et al  applied the KFRE to a cohort in the Netherlands and externally validated the full and abbreviated forms KFRE in an independent CKD population.
  • A further study by Tangri et al. published in AJKD involved use of a version of the 8-variable equation encompassing dynamic values for prediction; this involved longitudinal follow-up of a cohort from a Nephrology clinic over several years. 11% of the study population developed ESKD; unsurprisingly this was predominately those who had CKD 5 at baseline (60%). Change in GFR emerged as a strong factor in predicting those progressing to ESKD emphasizing the importance of monitoring change over time. This study will require further validation in an external cohort as in the previous study, however the dynamic approach is promising as it is able to incorporate information from future events with time dependent covariates throughout the follow-up period.

Obtaining the expected risk progression scores is now as simple as entering data into the QXMD online calculator or application. The possible implications for our future practice is promising, however there are further considerations. The equation could be used to guide referrals to Nephrology services as suggested by Tangri at his recent talk at the KDIGO Controversies Conference on Dialysis Initiation, Modality Choice & Prescription. The equation is yet to be validated in a primary care setting where the vast majority of patients with CKD are not referred for nephrology care. The full KFRE also requires additional data that is unlikely to be available in the primary care setting. ESKD is not the only important clinical outcome in CKD to be considered as there is an additional need to incorporate cardiovascular outcomes and mortality attributed to CKD. An alternative potential application of the KFRE is applying it to new patient referrals to Nephrology clinics. Applying the KFRE at first visit could give Nephrologists added confidence in both discharging patients and identifying those at high risk of progression who need to begin education and planning. The equation is well on the road to being useful in clinical practice and represents a potential game-changer in CKD management. Incorporation of novel biomarkers of CKD into existing scores may represent a future direction for predicting risk of progression. We await further studies testing the KFRE in the broader CKD population with excitement and anticipation.
Post by Laura Slattery, NSMC Intern 2018