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Pharmacovigilance Analysis of Serious Adverse Events Reported for Biologic Response Modifiers Used as Prophylaxis Against Transplant Rejection: A Real-World Postmarketing Experience from the US FDA Adverse Event Reporting System (FAERS)
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Ali A.K. Pharmacovigilance Analysis of Serious Adverse Events Reported for Biologic Response Modifiers Used as Prophylaxis Against Transplant Rejection: A Real-World Postmarketing Experience from the US FDA Adverse Event Reporting System (FAERS). International Journal of Organ Transplantation Medicine. April 2013;4(2):62-71.
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Ali, Ayad K.
Avicenna Organ Transplantation Institute
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Background: Immunosuppression by biologic response modifiers (BRM) is a crucial component for successful organ transplantation. In addition to their variable effectiveness in the prevention of organ rejection, these medications have safety concerns that complicate therapeutic outcomes in organ transplant patients. Objective: This study aims at identifying and characterizing safety signals of serious adverse events associated with exposure to BRM among organ transplant patients in a real-world environment. Methods: The FDA Adverse Event Reporting System was utilized to apply a pharmacovigilance disproportionality analysis to indentify serious adverse events. Associations between drugs and events were measured by empirical Bayes geometric mean (EBGM) and the corresponding 95% confidence intervals (EB05–EB95). Associations with EBGM≥2 were considered significant safety signals. Results: From 1997 to 2012, a total of 12,151 serious adverse event reports for BRM were reported; 15.6% of them (n=1,711) met the safety signal threshold of EB05>1, and 11.6% of these signals (n=199) were significant (EBGM≥2). Sirolimus and mycophenolate accounted for the majority of all signals; antithymocyte immunoglobulin (ATI) and cyclosporine contributed to the majority of significant signals. The following significant signals were identified for ATI (reduced therapeutic response, pulmonary edema, hypotension, serum sickness, infusion-related reaction, and anaphylactic reaction); for azathioprine (alternaria infection, fungal skin infection, and lymphoproliferative disorder); for cyclosporine (neurotoxicity, graft vs. host disease, and thyroid cancer); for cyclophosphamide (disease progression); for daclizumab (cytomegalovirus infection); and for tacrolimus (coma and tremor). 33.6% of these events contributed to patient death (n=67); 6.5% were life-threatening (n=13); 32.1% lead to hospitalization (n=64); and 27.6% resulted in other serious outcomes (n=55). Conclusion: Utilization of BRM for the prophylaxis against transplant rejection is associated with serious adverse events that could be fatal.
Collected for University of Florida's Institutional Repository by the UFIR Self-Submittal tool. Submitted by Ayad K Ali.
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Suggested Citation: Ali AK. Pharmacovigilance Analysis of Serious Adverse Events Reported for Biologic Response Modifiers Used as Prophylaxis Against Transplant Rejection: A Real-World Postmarketing Experience from the US FDA Adverse Event Reporting System (FAERS). International Journal of Organ Transplantation Medicine. April 2013;4(2):62-71.

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Original Article Ayad K Ali, Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, 101 S Newell Drive, PO Box 100496, Gainesville, FL 32610-0496, USA +1-352-273-6629 +1-352-273-6270 Pharmacovigilance Analysis of Serious Adverse Events Prophylaxis against Transplant Rejection: a Real-World A. K. Ali* Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, USA ABSTRACT vs. KEYWORDS: INTRODUCTION E nd-stage organ failure is a common problem with limited treatment ap proaches beyond organ transplantation [1]. Number of candidates on waiting lists for transplantation continues to rise, while num


63 ber of donors continues to level off. In the United States, there were 11,663 organ donors and 23,360 organ transplants from January to October 2012 [2]. As of January 2013, there were 116,944 candidates on waiting lists with 74,451 (63.6%) being classified as active wait listed who were eligible for organ offer at a given point of time [2]. In 2007, approximately 2.5 million individuals with end-stage organ failure died [3]; nevertheless, pre-transplanta tion mortality rates were reduced among pa tients on waiting lists across all solid organs [4]. From 2010 to 2011, the number of patients on the waiting list for organ transplantation in the United States increased by 0.2% from 54,505 to 54,599; but the number of organ transplantations declined by 0.7% from 17,726 to 17,604 [4]. Organ transplantation improved patients quality of life and overall survival; however, organ rejection by the hosts immune system is a major complication of organ trans plantation [1, 4]. Among adult transplant pa tients, the approximate incidence rates of acute rejection within the first year of transplanta tion are 40% for intestine, 19% for heart, 18% for lung, 15%20% for pancreas, 15% for liver, and 10% for kidney [4]. Immunosuppressive therapy aims to provide minimum suppression to the immune system to prevent transplant rejection while avoiding or minimizing complications of immunodefi ciency. Generally, immunosuppressive medi cations are classified into corticosteroids ( e.g. prednisolone) and biologic response modifiers (BRM) ( e.g. cyclosporine). The introduction of BRM as an alternative to corticosteroids with its associated metabolic adverse reactions, is considered a breakthrough in prophylaxis against transplant rejection. However, these agents are associated with a myriad of safety concerns and not free from serious adverse outcomes that could complicate transplanta tion [5]. Some adverse reactions are well rec ognized for these agents; nonetheless, serious events are not well documented. By utilizing real-world data, this study aims to identify and characterize significant safety signals of seri ous adverse events reported for BRM used for the prophylaxis against transplant rejection. MATERIALS AND METHODS Unduplicated adverse event reports spontane ously submitted to the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) (formerly AERS) from October 1, 1997 to March 31, 2012 were used to apply a pharmacovigilance dispropor tionality analysis for the detection and charac terization of serious adverse events associated with biologic response modifiers indicated for the prophylaxis against organ rejection. The FAERS is a database of spontaneously submit ted adverse event reports for pharmaceutical products that is updated on a quarterly basis by FDA. Reports are submitted from health care professionals, consumers or caregivers, manufacturers, and other sources from the United States and other countries [6]. The FAERS is considered the primary source for the FDA to manage and monitor new adverse events reported for marketed pharmaceutical products [7]. The World Health Organizations Anatomi cal Therapeutic Chemical (ATC, January 2012) classification system was used to iden tify BRM. Table 1 lists individual agents ap proved for marketing in the United States. Adverse event reports that included BRM as primary suspects in the occurrence of the ad verse event, and those with an indication for the prophylaxis against transplant rejection were included in the analysis. Figure 1 shows the applied database restriction criteria. The Preferred Term (PT) hierarchy of the Medical Dictionary for Regulatory Activi ties (MedDRA 15.0, March 2012) was used to identify serious adverse events that resulted in death, life-threatening experience, persis tent or significant disability or incapacity, congenital anomaly or birth defect, initial or prolonged existing inpatient hospitalization, requirement for intervention, or any other im portant medical outcomes [8]. Within these reports, safety signals were evaluated for spe cific adverse events, and event PTs with sig nificant safety signals were discussed in this


64 report. Within FAERS, adverse events, seri ousness outcome, and clinical indication for the reported drug were recorded using the PT hierarchy of MedDRA [6]. Empirica Signal (7.3.341, November 2011, Oracle USA, Inc., Redwood City, CA, USA) was used to generate empirical Bayesian geo metric mean (EBGM) and its corresponding 95% confidence intervals (EB05EB95). An EBGM >1 was interpreted as the reported adverse event for the corresponding drug was higher than that expected compared to other drugs and events in the database. Safety sig nals were identified if the lower limit of the 95% confidence interval (EB05) was >1, and were considered significant safety signals [9, 10]. Signals with both EBGM and EB05 val nals that warrant regulatory action [6]. RESULTS During the study period, a total of 12,151 ad verse event reports was submitted for BRM and were classified as serious events. More than half of these serious events were attrib uted to sirolimus (n=6,749); about 19% were for mycophenolic acid (n=2,317); and about 9%, 7%, and 6% of serious event reports were respectively, for cyclosporine (n=1,067), ta crolimus (n=841), and antithymocyte immu noglobulin (n=725). The rest of BRM collec tively contributed to 4% of the reports (n=452) (Table 2). Table 1: Biologic response modifiers currently available in the United States (Source: Class Agent Brand name example* FDA approval date Alkylating agents Cyclophosphamide Cytoxan Nov. 1959 Antimetabolites Azathioprine Imuran Mar. 1968 Methotrexate Mexate Sept. 1979 Calcineurin inhibitors Cyclosporine Sandimmune Nov. 1983 Tacrolimus Prograf Apr. 1994 IL-2R antibodies Basiliximab Simulect May 1998 Daclizumab Zenapax Dec. 1997 Efalizumab Raptiva Oct. 2003 mTOR inhibitors Everolimus Afinitor Mar. 2009 Pimecrolimus Elidel Dec. 2001 Sirolimus Rapamune Sept. 1999 Temsirolimus Torisel May 2007 Purine synthesis inhibitors Mycophenolic acid Myfortic Feb. 2004 Mycophenolate mofetil Cellcept May 1995 T-cell depletion antibodies Antithymocyte immunoglobulin Thymoglobulin Nov. 1981 A. K. Ali


65 Among the identified serious adverse events, only 14% of the reports (n=1,711) generated safety signals of serious events associated with BRM with EB05 values >1. None of the re ports indicated patient recovery from the seri ous events. Sirolimus and mycophenolic acid, respectively, contributed to 52% (n=896) and 18% (n=304) of the signals. Antithymocyte immunoglobulin, tacrolimus, and cyclospo rine accounted for 10% (n=172), 9% (n=159), and 7% (n=113) of the signals, respectively; the rest of the BRM collectively contributed to 4% (n=67) of the identified signals (Table 2). Figure 2 shows safety signals with EB05 values >1 for reported serious events associ ated with BRM. For antithymocyte immu noglobulin, eight signals were identified the strongest signal was for a MedDRA PT therapeutic response decreased, which could be a proxy for immunosuppression failure (EBGM=3.67; EB05EB95: 1.476.22). Aza thioprine was associated with four signals with the strongest signal for alternaria infec tion (EBGM=4.50; EB05EB95: 1.278.88). Cyclosporine was associated with five sig nals and neurotoxicity was the strongest identified signal (EBGM=4.02; EB05EB95: 2.744.74). Cyclophosphamide and daclizumab each associated with one safety signal; a sig nal of disease progression was identified for cyclophosphamide, which can also be a proxy for immunosuppression failure (EBGM=3.31; EB05EB95: 1.226.03), and a signal of cy tomegalovirus infection was identified for daclizumab (EBGM=2.36; EB05EB95: 1.30 3.53). Among the seven signals identified for mycophenolic acid, cytomegalovirus infec tion was the strongest (EBGM=1.69; EB05 EB95: 1.302.19). Sirolimus was associated with nine signals, which were close in values; however, impaired healing (EBGM=1.26; EB05EB95: 1.011.59) and drug ineffective (EBGM=1.25; EB05EB95: 1.071.44) were the strongest. Tacrolimus was associated with seven safety signals for serious events; the strongest signal was for coma (EBGM=2.40; EB05EB95: 1.084.71). Conversely, safety signals were generated neither for everolimus (EBGM=1.22; EB05EB95: 0.882.40) nor for concomitantly administered sirolimus and tacrolimus (EBGM=1.16; EB05EB95: 0.85 2.04). About 12% of the identified signals were sig nificant (n=199) with a total number of 16 sig nificant signals for six BRM (Tables 2 and 3). The distribution of significant signals in re lation to the identified signals for individual BRM was as follows: about 40% of signals for antithymocyte immunoglobulin (n=68), half the signals for azathioprine (n=18) and cyclosporine (n=58), all the signals for cyclo phosphamide (n=9) and daclizumab (n=22), and 15% of the signals for tacrolimus (Table Figure 1: Database restriction criteria


66 2). Although mycophenolic acid and siroli mus showed safety signals of serious adverse events, none of these signals were significant. Table 3 lists the identified significant sig nals for individual BRM by the decreasing order of signal strength within each agent. The reporting of the following adverse events was significantly higher than that ex pected for the following individual BRM: for antithymocyte immunoglobulin, thera peutic response decreased (EBGM=3.67; EB05EB95: 1.476.22), pulmonary edema (EBGM=2.73; EB05EB95: 1.314.28), hy potension (EBGM=2.64; EB05EB95: 1.25 4.28), serum sickness (EBGM=2.37; EB05 EB95: 1.084.67), infusion related reaction (EBGM=2.26; EB05EB95: 1.074.54), and anaphylactic reaction (EBGM=2.10; EB05 EB95: 1.075.01); for azathioprine, alternaria infection (EBGM=4.50; EB05EB95: 1.27 8.88), fungal skin infection (EBGM=3.06; EB05EB95: 1.037.55), and lymphoprolif erative disorder (EBGM=2.17; EB05EB95: 1.005.14); for cyclosporine, neurotoxic ity (EBGM=4.02; EB05EB95: 2.745.74), graft vs host disease (EBGM=3.00; EB05 EB95: 2.184.06), and thyroid cancer (EBGM=2.92; EB05EB95: 1.205.12); and for tacrolimus, coma (EBGM=2.40; EB05 EB95: 1.084.71), and tremor (EBGM=2.27; EB05EB95: 1.133.99). All the identified signals of disease progression for cyclophos phamide and cytomegalovirus infection for daclizumab were significant. Furthermore, significant signals that necessitate regulatory follow-up were only identified for cyclosporine in association with neurotoxicity and graft versus host disease adverse events (both EBGM and EB05 values exceeded 2). Table 4 shows the characteristics of BRM ad verse event reports in which significant signals were identified. Approximately 34% of these events contributed to patient death (n=67); 6.5% were life-threatening (n=13); 32.1% led to hospitalization or required interventions (n=64); and 27.6% contributed to other seri ous outcomes (n=55). None of the events re sulted in disabilities or congenital anomalies. About 46% of death reports were attributed to cyclosporine (n=31), 15% to antithymocyte immunoglobulin (n=10), 13.4% to cyclophos phamide (n=9), 12% to tacrolimus (n=8), 9% Table 2: Distribution of serious adverse event reports for biologic response modifiers Drug Number of Serious Event Reports (%) All Serious Events (EB05 >0) n=12,151 All Signals (EB05 >1) n=1,711 Significant Signals n=199 Antithymocyte immunoglobulin 725 (5.9) 172 (10.0) 68 (34.1) Azathioprine 99 (0.8) 36 (2.1) 18 (9.0) Cyclosporine 1,067 (8.8) 113 (6.6) 58 (29.1) Cyclophosphamide 60 (0.5) 9 (0.5) 9 (4.5) Daclizumab 267 (2.2) 22 (1.3) 22 (11.0) Everolimus 5 (0.04) 0 (0.0) 0 (0.0) Mycophenolic Acid 2,317 (19.0) 304 (18.0) 0 (0.0) Sirolimus 6,749 (55.0) 896 (52.0) 0 (0.0) Tacrolimus 841 (6.9) 159 (9.3) 24 (12.0) Tacrolimus and Sirolimus 21 (0.2) 0 (0.0) 0 (0.0) EBGM: Empirical Bayes geometric mean n: Number of reports within the corresponding category A. K. Ali


67 to azathioprine (n=6), and 4.4% to daclizumab (n=3). The vast majority of the reported lifethreatening events were for antithymocyte im munoglobulin (n=12); only one report was for tacrolimus. About 42% of the reported hospi talizations or intervention requirements were attributed to antithymocyte immunoglobulin (n=27), 29.6% to daclizumab (n=19), 17.1% to tacrolimus (n=11), 7.8% to cyclosporine (n=5), and 3.1% to azathioprine (n=2). The median age for patients exposed to an tithymocyte and experienced serious events that generated significant safety signals was 47.5 years; it was 64 years for azathioprine us ers, 37 for cyclosporine users, 48 for daclizum ab users, and 54 years for tacrolimus users. About 54% of patients in antithymocyte im munoglobulin reports were males (n=37), 40% were females (n=27), and 6% with unknown sex (n=4). About 78% of reported azathioprine users were males (n=14), 17% were females (n=3), and one patient with unknown sex. Ap proximately 45% of the reported cyclosporine users were males (n=26), 7% were females (n=4), and 48% with unknown sex (n=28). Among reports for daclizumab, about 73% of patients were males (n=16), 18% were females (n=4), and 9% with unknown sex (n=2). Half of the patients in tacrolimus reports were males (n=12), 37.5% were females (n=9), and 12.5% had unknown sex reported (n=3). Patient de Figure 2: Signals of serious adverse events associated with biologic response modifiers


68 mographics were not reported for cyclophos phamide users. The median number of medications concur rently administered with the respective BRM was three for reports of antithymocyte im munoglobulin, two for azathioprine and cy clophosphamide, one for cyclosporine, nine for daclizumab, and six for tacrolimus. Over 17% of antithymocyte immunoglobulin seri ous reports with significant signals did not have concomitantly used medications (n=12), corresponding to almost 57% of anaphylactic reaction, 40% of infusion related reaction, and 13% of each of pulmonary edema and hypotension, events. About 8% of tacrolimus reports did not have additional medications re ported (n=2), corresponding to 10% of coma, and 7.1% of tremor events. Characteristics of individual adverse events for corresponding BRM are described in Table 4. DISCUSSION The United States FAERS database was used to conduct a retrospective pharmacovigilance analysis of serious adverse events reported for BRM immunosuppressive medications that are indicated for the prophylaxis against transplant rejection. The majority of identi fied significant safety signals contributed to patient death; however, these signals should not be interpreted as causal links between exposure to BRM and occurrence of serious adverse events. The identified adverse events were consistent with the known safety profile of individual BRM; however, the seriousness of these events, e.g. death, is not established in the literature. For instance, proliferative disorders, e.g. T-cell lymphoma [11], and op portunistic infections, e.g. cytomegalovirus infection, are common complications of immu nosuppression [12]. Also, transplant recipients Table 3: Significant safety signals of serious adverse events associated with biologic response modifiers (EBGM 2) Drug Adverse event PT No. of reports* EBGM (EB05EB95) Antithymocyte immunoglobulin Therapeutic response decreased 10 3.67 (1.47.22) Pulmonary edema 16 2.73 (1.31.28) Hypotension 15 2.64 (1.25.28) Serum sickness 10 2.37 (1.08.67) Infusion related reaction 10 2.26 (1.07.54) Anaphylactic reaction 7 2.10 (1.00.01) Azathioprine Alternaria infection 6 4.50 (1.27.88) Fungal skin infection 5 3.06 (1.03.55) Lymphoproliferative disorder 7 2.17 (1.00.14) Cyclosporine Neurotoxicity 19 4.02 (2.74.74)** Graft versus host disease 28 3.00 (2.18.06)** Thyroid cancer 11 2.92 (1.20.12) Cyclophosphamide Disease progression 9 3.31 (1.22.03) Daclizumab Cytomegalovirus infection 22 2.36 (1.30.53) Tacrolimus Coma 10 2.40 (1.08.71) Tremor 14 2.27 (1.13.99) EBGM: Empirical Bayes geometric mean PT: Preferred term A. K. Ali


69 Table 4: Drug Adverse event (n) Characteristics of reports Seriousness, n (%) Patients demographics Co-drugs Death LT HI Age, year* Sex** No. of Co-drugs* No. of reports without M F Antithymocyte Ig Therap. response decreased (10) 6 (60) 43 (17) 5 (50) 5 (50) 2 (2) Pulmonary edema (16) 4 (25) 2 (13) 6 (38) 54 (13) 7 (44) 9 (56) 7 (0) 2 Hypotension (15) 2 (13) 6 (40) 5 (33) 52 (13) 11 (73) 3 (20) 4 (0) 2 Serum sickness (10) 7 (70) 37 (24) 6 (60) 4 (40) 6 (3) Infusion related reaction (10) 2 (20) 1 (10) 1 (10) 47 (24) 4 (40) 3 (30) 2 (0) 4 Anaphylactic reaction (7) 2 (29) 3 (43) 2 (29) 48 (15) 4 (57) 3 (43) 0 (0) 4 Azathioprine Alternaria infection (6) 2 (33) 64 (28) 6 (100) 2 (2) Fungal skin infection (5) 2 (40) 65 (48) 5 (100) 2 (2) Lymphoproliferative disorder (7) 2 (29) 2 (39) 21 (5) 3 (43) 3 (43) 2 (1) Cyclosporine Neurotoxicity (19) 14 (74) 1 (5) 36 (17) 9 (47) 10 (53) 1 (1) Graft versus host disease (28) 17 (61) 4 (14) 37 (11) 12 (43) 12 (43) 1 (1) Thyroid cancer (11) 40 (23) 5 (45) 6 (55) 2 Cyclophosphamide Disease progression (9) 9 (100) U U U 2 Daclizumab Cytomegalovirus infection (22) 3 (14) 19 (86) 48 (24) 16 (73) 4 (18) 9 (3) Tacrolimus Coma (10) 7 (70) 2 (20) 59 (46) 4 (40) 3 (30) 2 (0) 1 Tremor (14) 1 (7) 1 (7) 9 (64) 49 (31) 8 (57) 6 (43) 10 (0) 1 *Reported as median (minimummaximum) **Percentages out of total number of reports including unknown sex values. F: Female, M: Male, HI: Initial or prolonged existing inpatient hospitalization and/or requirement for medical intervention Ig: Immunoglobulin, LT: Life-threatening, n: Total number of reports for the adverse event and corresponding drug; total number of reports was 199, U: Unknown


70 are twice more likely to develop cancers than their counterparts without transplantation, and the risk increases greatly by infections with oncogenic viruses, e.g. Epstein-Barr vi rus, Kaposi sarcoma herpes virus, and human papillomavirus [13]; this might be related to the duration and intensity of immunosup pression regardless of specific BRM [14], and therefore, the association of cyclosporine with thyroid cancer should be interpreted with caution. Although daclizumab was associated with significant signal of cytomegalovirus in fection, clinical trials showed fewer incidences among daclizumab users compared to placebo users [15]. In general calcineurin inhibitors, e.g. cyclosporine and tacrolimus, are associ ated with rare neurological and psychiatric adverse events, although coma and delirium have been reported for tacrolimus given at high doses [16]. Serums sickness and infu sion-related reactions have been reported with antithymocyte immunoglobulin [17, 18], but the occurrence of anaphylactic reactions is not well documented. Data repositories of spontaneously submitted adverse events, e.g. FAERS are one of the key tools of routine assessment and management of risks associated with marketed pharmaceu tical products. In addition to other limitations of spontaneously submitted adverse event data, these data are increasingly incomplete ( e.g. missing patient demographic information for cyclophosphamide), variable reporting rates overtime, underreporting, duplicate reports, unverified source of submitted data, inability to adjust for important confounders, and miss ing information about temporality [6]. Since data mining algorithms, e.g. EBGM, are hy pothesis generating techniques, they should not be used in isolation to clinical judgment and available epidemiological or clinical evi dence. Furthermore, the estimated EBGM values should not be interpreted as incidence rates; rather they should be treated as the re spective adverse event for the offending drug has been reported more than that expected compared to other adverse events and other drugs in the database during the specified reporting period. As an example of potential confounding effect by co-medications, system ic corticosteroids were mentioned in most of the reports with concurrent medications, and some reports included more than one class of BRM as secondary suspect in the occurrence of the adverse event. In conclusion, utilization of BRM for the pro phylaxis against transplant rejection is associ ated with serious adverse events that could be fatal and life-threatening. Transplant special ists should exercise caution when prescribing these medications to transplant patients and should monitor patient progress in terms of safety, tolerability and transplant outcomes throughout exposure period. Pharmacoepide miological studies are required to evaluate the identified safety signals to help understand the benefit-risk profile of these medications. REFERENCES 1. Miller BW. Solid Organ Transplant Medicine. In: Green GB, Harris IS, Lin GA, Moylan KC, eds. The 31 st 2004 2. 3. 4. 5. Guidelines on Renal Transplan A. K. Ali


71 6. Therap Clin Risk Manag 7 :337-44. 7. 8. Code of 9. 53 2008 11. 12. 13(Suppl 3) :1-8. 13. et al Curr Mol Med 14. Drugs 67 :1167-98. 15. Group. 68 16. Transplant 13 :313-26. 17. et al Br J Hae 63 :729-36. 18. I. 2 :148-156.