Bernard Fischbach M.D.

Posted July 15th 2021

Association between dd-cfDNA levels, de novo donor specific antibodies, and eGFR decline: An analysis of the DART cohort.

Bernard V. Fischbach M.D.

Bernard V. Fischbach M.D.

Sawinski, D., Mehta, S., Alhamad, T., Bromberg, J.S., Fischbach, B., Aeschbacher, T., Ghosh, S., Shekhtman, G., Dholakia, S., Brennan, D.C., Poggio, E., Bloom, R. and Jordan, S.C. (2021). “Association between dd-cfDNA levels, de novo donor specific antibodies, and eGFR decline: An analysis of the DART cohort.” Clin Transplant Jun 28. [Epub ahead of print].

Full text of this article.

Despite advances in immunosuppression, long-term allograft survival remains a challenge and evidence of immune mediated injury can be detected even early in the posttransplant course. The emergence of de novo donor specific antibodies (dnDSA) is a particularly poor prognostic indicator; the detection of DSA is highly correlated with the development of antibody-mediated allograft injury and subsequent graft loss. A study from Wiebe et al. demonstrated that patients with dnDSA had markedly reduced 10-year allograft survival (57% versus 96%). One of the challenges in this population is the lack of consensus regarding therapeutic interventions for dnDSA, complicated by the fact that allograft dysfunction often progresses despite augmented immunosuppression. Particularly problematic is that long-lived plasma cells, the source of dnDSA, are generally resistant to maintenance immunosuppression, and therapies targeted towards them have significant side effects. [No abstract; excerpt from article].


Posted March 15th 2019

A Model for Glomerular Filtration Rate Assessment in Liver Disease (GRAIL) in the Presence of Renal Dysfunction.

Sumeet K. Asrani M.D.

Sumeet K. Asrani M.D.E

Asrani, S. K., L. W. Jennings, J. F. Trotter, J. Levitsky, M. K. Nadim, W. R. Kim, S. A. Gonzalez, B. Fischbach, R. Bahirwani, M. Emmett and G. Klintmalm (2019). “A Model for Glomerular Filtration Rate Assessment in Liver Disease (GRAIL) in the Presence of Renal Dysfunction.” Hepatology 69(3): 1219-1230.

Full text of this article.

Estimation of glomerular filtration rate (eGFR) in patients with liver disease is suboptimal in the presence of renal dysfunction. We developed a model for GFR assessment in liver disease (GRAIL) before and after liver transplantation (LT). GRAIL was derived using objective variables (creatinine, blood urea nitrogen, age, gender, race, and albumin) to estimate GFR based on timing of measurement relative to LT and degree of renal dysfunction (www.bswh.md/grail). The measured GFR (mGFR) by iothalamate clearance (n = 12,122, 1985-2015) at protocol time points before/after LT was used as reference. GRAIL was compared with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD-4, MDRD-6) equations for mGFR < 30 mL/min/1.73 m(2) . Prediction of development of chronic kidney disease (mGFR < 20 mL/min/1.73 m(2) , initiation of chronic dialysis) and listing or receipt of kidney transplantation within 5 years was examined in internal cohort (n = 785) and external validation (n = 68,217, 2001-2015). GRAIL had less bias and was more accurate and precise as compared with CKD-EPI, MDRD-4, and MDRD-6 at time points before/after LT for low GFR. For mGFR < 30 mL/min/1.73 m(2) , the median difference (eGFR-mGFR) was GRAIL: 5.24 (9.65) mL/min/1.73 m(2) as compared with CKD-EPI: 8.70 (18.24) mL/min/1.73 m(2) , MDRD-4: 8.82 (17.38) mL/min/1.73 m(2) , and MDRD-6: 6.53 (14.42) mL/min/1.73 m(2) . Before LT, GRAIL correctly classified 75% as having mGFR < 30 mL/min/1.73 m(2) versus 36.1% (CKD-EPI), 36.1% (MDRD-4), and 52.8% (MDRD-6) (P < 0.01). An eGFR < 30 mL/min/1.73 m(2) by GRAIL predicted development of CKD (26.9% versus 4.6% CKD-EPI, 5.9% MDRD-4, and 10.5% MDRD-6) in center data and needing kidney after LT (48.3% versus 22.0% CKD-EPI versus 23.1% MDRD-4 versus 48.3% MDRD-6, P < 0.01) in national data within 5 years after LT. Conclusion: GRAIL may serve as an alternative model to estimate GFR among patients with liver disease before and after LT at low GFR.


Posted November 15th 2018

A model for Glomerular filtration Rate Assessment In Liver disease (GRAIL) in the presence of renal dysfunction.

Sumeet K. Asrani M.D.

Sumeet K. Asrani M.D.

Asrani, S. K., L. W. Jennings, J. F. Trotter, J. Levitsky, M. K. Nadim, W. R. Kim, S. A. Gonzalez, B. Fischbach, R. Bahirwani, M. Emmett and G. Klintmalm (2018). “A model for Glomerular filtration Rate Assessment In Liver disease (GRAIL) in the presence of renal dysfunction.” Hepatology Oct 19. [Epub ahead of print].

Full text of this article.

Estimation of glomerular filtration rate (eGFR) in patients with liver disease is suboptimal in presence of renal dysfunction. We developed a model for GFR Assessment In Liver disease (GRAIL) before and after liver transplantation (LT). GRAIL was derived using objective variables (creatinine, blood urea nitrogen, age, gender, race, albumin) to estimate GFR based on timing of measurement relative to LT and degree of renal dysfunction. Measured GFR (mGFR) by iothalamate clearance (n=12,122, 1985-2015) at protocol time points before/after LT was used as reference. GRAIL was compared to Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD-4, MDRD-6) equations for mGFR<30ml/min/1.73m(2) . Prediction of development of chronic kidney disease (mGFR < 20ml/min/1.73m(2) , initiation of chronic dialysis) and listing or receipt of kidney transplantation within 5 years was examined in internal cohort (n=785) and external validation (n=68,217, 2001-2015). GRAIL had less bias, was more accurate and precise as compared to CKD-EPI, MDRD-4 and MDRD-6 at time points before/after LT for low GFR. For mGFR<30ml/min/1.73m(2) , the median difference (eGFR-mGFR) was GRAIL: 5.24 [9.65] ml/min/1.73m(2) as compared to CKD-EPI: 8.70 [18.24]ml/min/1.73m(2) , MDRD-4: 8.82 [17.38]ml/min/1.73m(2) , and MDRD-6: 6.53[14.42] ml/min/1.73m(2) . Prior to LT, GRAIL correctly classified 75% as having mGFR<30ml/min/1.73m(2) vs. 36.1% (CKD-EPI), 36.1%(MDRD-4), and 52.8%(MDRD-6).(p<0.01) An eGFR<30ml/min/1.73m(2) by GRAIL predicted development of CKD (26.9% vs. 4.6% CKD-EPI, 5.9% MDRD-4, and 10.5% MDRD-6) in center data and needing kidney after LT (48.3% vs. 22.0% CKD-EPI vs. 23.1% MDRD-4 vs. 48.3% MDRD-6, p<0.01) in national data within 5 years after LT. CONCLUSION: GRAIL may serve as an alternative model to estimate GFR amongst patients with liver disease before and after LT at low GFR.


Posted July 15th 2017

Cell-free DNA and active rejection in kidney allografts.

Bernard Fischbach M.D.

Bernard Fischbach M.D.

Bloom, R. D., J. S. Bromberg, E. D. Poggio, S. Bunnapradist, A. J. Langone, P. Sood, A. J. Matas, S. Mehta, R. B. Mannon, A. Sharfuddin, B. Fischbach, M. Narayanan, S. C. Jordan, D. Cohen, M. R. Weir, D. Hiller, P. Prasad, R. N. Woodward, M. Grskovic, J. J. Sninsky, J. P. Yee and D. C. Brennan (2017). “Cell-free DNA and active rejection in kidney allografts.” J Am Soc Nephrol 28(7): 2221-2232.

Full text of this article.

Histologic analysis of the allograft biopsy specimen is the standard method used to differentiate rejection from other injury in kidney transplants. Donor-derived cell-free DNA (dd-cfDNA) is a noninvasive test of allograft injury that may enable more frequent, quantitative, and safer assessment of allograft rejection and injury status. To investigate this possibility, we prospectively collected blood specimens at scheduled intervals and at the time of clinically indicated biopsies. In 102 kidney recipients, we measured plasma levels of dd-cfDNA and correlated the levels with allograft rejection status ascertained by histology in 107 biopsy specimens. The dd-cfDNA level discriminated between biopsy specimens showing any rejection (T cell-mediated rejection or antibody-mediated rejection [ABMR]) and controls (no rejection histologically), P<0.001 (receiver operating characteristic area under the curve [AUC], 0.74; 95% confidence interval [95% CI], 0.61 to 0.86). Positive and negative predictive values for active rejection at a cutoff of 1.0% dd-cfDNA were 61% and 84%, respectively. The AUC for discriminating ABMR from samples without ABMR was 0.87 (95% CI, 0.75 to 0.97). Positive and negative predictive values for ABMR at a cutoff of 1.0% dd-cfDNA were 44% and 96%, respectively. Median dd-cfDNA was 2.9% (ABMR), 1.2% (T cell-mediated types >/=IB), 0.2% (T cell-mediated type IA), and 0.3% in controls (P=0.05 for T cell-mediated rejection types >/=IB versus controls). Thus, dd-cfDNA may be used to assess allograft rejection and injury; dd-cfDNA levels <1% reflect the absence of active rejection (T cell-mediated type >/=IB or ABMR) and levels >1% indicate a probability of active rejection.


Posted April 15th 2017

Cell-Free DNA and Active Rejection in Kidney Allografts.

Bernard Fischbach M.D.

Bernard Fischbach M.D.

Bloom, R. D., J. S. Bromberg, E. D. Poggio, S. Bunnapradist, A. J. Langone, P. Sood, A. J. Matas, S. Mehta, R. B. Mannon, A. Sharfuddin, B. Fischbach, M. Narayanan, S. C. Jordan, D. Cohen, M. R. Weir, D. Hiller, P. Prasad, R. N. Woodward, M. Grskovic, J. J. Sninsky, J. P. Yee and D. C. Brennan (2017). “Cell-Free DNA and Active Rejection in Kidney Allografts.” J Am Soc Nephrol: 2017 Mar [Epub ahead of print].

Full text of this article.

Histologic analysis of the allograft biopsy specimen is the standard method used to differentiate rejection from other injury in kidney transplants. Donor-derived cell-free DNA (dd-cfDNA) is a noninvasive test of allograft injury that may enable more frequent, quantitative, and safer assessment of allograft rejection and injury status. To investigate this possibility, we prospectively collected blood specimens at scheduled intervals and at the time of clinically indicated biopsies. In 102 kidney recipients, we measured plasma levels of dd-cfDNA and correlated the levels with allograft rejection status ascertained by histology in 107 biopsy specimens. The dd-cfDNA level discriminated between biopsy specimens showing any rejection (T cell-mediated rejection or antibody-mediated rejection [ABMR]) and controls (no rejection histologically), P<0.001 (receiver operating characteristic area under the curve [AUC], 0.74; 95% confidence interval [95% CI], 0.61 to 0.86). Positive and negative predictive values for active rejection at a cutoff of 1.0% dd-cfDNA were 61% and 84%, respectively. The AUC for discriminating ABMR from samples without ABMR was 0.87 (95% CI, 0.75 to 0.97). Positive and negative predictive values for ABMR at a cutoff of 1.0% dd-cfDNA were 44% and 96%, respectively. Median dd-cfDNA was 2.9% (ABMR), 1.2% (T cell-mediated types >/=IB), 0.2% (T cell-mediated type IA), and 0.3% in controls (P=0.05 for T cell-mediated rejection types >/=IB versus controls). Thus, dd-cfDNA may be used to assess allograft rejection and injury; dd-cfDNA levels <1% reflect the absence of active rejection (T cell-mediated type >/=IB or ABMR) and levels >1% indicate a probability of active rejection.