Time trends in recurrence of juvenile nasopharyngeal angiofibroma: Experience of the past 4 decades




Abstract


Background


An analysis of time distribution of juvenile nasopharyngeal angiofibroma (JNA) from the last 4 decades is presented.


Methods


Sixty recurrences were analyzed as per actuarial survival. SPSS software was used to generate Kaplan–Meier (KM) curves and time distributions were compared by Log-rank, Breslow and Tarone–Ware test.


Results


The overall recurrence rate was 17.59%. Majority underwent open transpalatal approach(es) without embolization. The probability of detecting a recurrence was 95% in first 24 months and comparison of KM curves of 4 different time periods was not significant.


Conclusion


This is the first and largest series to address the time-distribution. The required follow up period is 2 years. Our recurrence is just half of the largest series (reported so far) suggesting the superiority of transpalatal techniques. The similarity of curves suggests less likelihood for recent technical advances to influence the recurrence that as per our hypothesis is more likely to reflect tumor biology per se.


Juvenile nasopharyngeal angiofibroma (JNA) constitutes about 0.05 % of all head and neck tumors and happens to be the most common benign nasopharyngeal tumor seen exclusively in adolescent males. It is a highly vascular tumor, well known for recurrence and shows minimal probability for incomplete excision due to severe intraoperative hemorrhage. Being uncommon, the majority of publications pertaining to JNA are limited by their sample size and hence recurrence is rarely reported. The existing literature although reveals the incidence of recurrence in 12 small series but its occurrence with time is not yet reported. Even the largest series reporting a 30%–50% recurrence rate (out of 33 cases in 1990) and 48% recurrence (out of 49 cases in 1958) have not addressed this aspect. It is important to establish the predictability of recurrence and thereby formulate a definite follow up protocol for early detection. Many authors have suggested the onset of clinical symptoms to be an indicator of significant recurrence but the occurrence of the insignificant–asymptomatic–progressive recurrence may be better dealt safely otherwise. Probably a large follow up series from a single center or a multicentric pooled data may provide a definite answer to define this time trend. Not many centers are trained and equipped enough to manage this entity and hence JNA is essentially a referral disease. Our institution has contributed the highest incidence of JNA across the globe (Scott Brown’s Otolaryngology Fifth Edition: Rhinology) and with the information of 60 recurrence events amidst 341 JNA patients in the last 4 decades an attempt is made here to analyze the pattern of recurrence with time.


1


Material and methods


This retrospective study is based on the available archival index at our department since 1972 to 2014. The information that was obtained through these records was the identification of the patients and the time and number of recurrences across the last 4 decades. The cases that recurred in subsequent years were tagged with the first admission date. Unfortunately many of the annual databases were not in a proper condition to reveal sufficient information and hence were discarded. In addition the cases undergoing radiotherapy/estrogen therapy were also excluded from this study owing to their small numbers. The entered data were further counterchecked by another otolaryngologist (BN).


A total of 60 events of recurrence were recorded in 52 recurrent cases of which 8 patients recurred twice. The analysis of 60 events was undertaken as per the classical methods of actuarial survival. The incidences of recurrences were estimated for every year and the recurrence pattern was analyzed as per the Kaplan–Meier method. It is noteworthy that none of the patient was censored since every patient even after the recurrence had equal chances of a second recurrence. Microsoft Excel software was used to enter the data and calculate percentage & cumulative-percentage of recurrence every year along with probability of recurrence and cumulative probability of non-recurrence as per the time scale. SPSS software was used to plot the Kaplan–Meier curves for recurrent episodes overall as well as separately for 4 different time periods corresponding to 4 decades. These time periods were labeled as A (including admission data of the year 1972, 1981, 1984-86), B (1987, 1989–92), C (1993–95, 2001–2) & D (2010–14). The recurrence–time distributions were compared by 3 tests using SPSS software. These tests were Log-rank (Mantel Cox) test, Breslow (generalized Wilcoxon) test and Tarone–Ware test.


A thorough search of literature for the recurrence of JNA was undertaken to appreciate the rate of recurrence and the total sample size on which the studies were based. Despite our best efforts we could not find any publication that could reflect the time trends. In addition all of the reports revealed recurrence sample to be less than 14 except that by Harma in 1958 who reported a recurrence sample of 23. We purposely omitted this study for comparison since the understanding of disease and the infrastructure facilities existing in 1950s were ‘too primitive’ as compared to 1980s onwards. Our series of 60 recurrences out of 341 cases happens to be the largest till date.




2


Observation


The occurrence of 24 recurrences out of 60 in the last 4 years as evidenced in Table 1 probably reflects a high incidence of JNA cases during these years. The proportion of the recurrence to the total number of JNA has not changed much across the years. However the number of recurrences for the year 2014 is still awaited. Although the total number of recurrent cases admitted in 2013 & 2014 were 8 & 6 respectively, only 4 & 1 upfront cases in the year 2013 & 14 respectively actually recurred during that duration. Accordingly the difference of 4 & 5 cases respectively in both the years was assigned in that particular year in which the respective cases presented as the upfront cases. This adjustment in the data was particularly made across all the 60 cases so as to appreciate the management related variable in every year that was likely to contribute to the recurrence rate. However the comparison of the proportion of recurrence for each year as such may not be appropriate considering the wide variation in the annual incidence of JNA. In this regard it is worth noting that there is about a 4 fold increase in the incidence of this disease in the current decade.



Table 1

Incidence of recurrences.























































































































Year of admission as upfront case Number of recurrences for upfront cases admitted in that respective year Total no. of admissions in that year Percentage of recurrence in that year
1972 3 6 50
1981 1 6 16.66
1982 0 3 0
1984 1 10 10
1985 2 8 25
1986 2 9 22.22
1987 1 14 7.14
1989 3 12 25
1990 2 13 15.38
1991 3 12 25
1992 3 9 33.33
1993 2 15 13.33
1994 3 7 42.85
1995 4 18 22.22
2001 4 17 23.52
2002 1 17 5.88
2010 1 9 11.11
2011 13 44 29.54
2012 6 37 16.21
2013 4* 31 12.90
2014 1** 44 2.27
Total 60 341 17.59

*8; **6 (*/** see text for details). The details of patients admitted in the years 1983 (4 cases), 1995 (12 cases) and 2013 (11 cases) could not be concluded in terms of recurrence and were hence omitted from analysis.


Fig. 1 depicts the plot between overall cumulative probability of non-recurrence as a function of time. Note the gradual decrease in the slope of the curve reflecting decreasing chances of recurrence with time. The curve corresponds to the fact that 83% of population would remain free of recurrence during their entire lifespan postoperatively. Table 2 depicts the recurrence analysis of 60 events as per the time trends starting from a common point. The probability of non-recurrence as per different time intervals and its cumulative probability overall are specifically indicated.




Fig. 1


Cumulative-Probability of Non-recurrence with time.

X axis denotes the number of months after surgery when recurrence occurred. The bullet points indicate the recurrent episodes. Note that 25 to 28 correspond to 31, 32, 43, & 54 months respectively. Y axis denotes the Cumulative-Probability of Non-recurrence.


Table 2

Distribution of recurrences with time.









































































































































































































































































Recurrence period in months Total number of JNA patients Number of recurrences in that period Probability of recurrence P(R) Probability of Non-recurrence P(NR) Cumulative Probability of NR CP(NR) % (R) Cum% (R)
1 341 6 0.0175 0.9824 0.9824 10 10
2 341 4 0.0117 0.9882 0.9708 6.66 16.66
3 341 3 0.0087 0.9912 0.9623 5 21.66
4 341 6 0.0175 0.9824 0.9454 10 31.66
5 341 2 0.0058 0.9941 0.9398 3.33 35
6 341 6 0.0175 0.9824 0.9233 10 45
7 341 3 0.0087 0.9912 0.9152 5 50
8 341 4 0.0117 0.9882 0.9044 6.66 56.66
9 341 5 0.0146 0.9853 0.8912 8.33 65
10 341 1 0.0029 0.9970 0.888591 1.66 66.66
11 341 1 0.0029 0.9970 0.8859 1.66 68.33
12 341 3 0.0087 0.9912 0.8781 5 73.33
13 341 3 0.0087 0.9912 0.8704 5 78.33
14 341 0 0 1 0.8704 0 78.33
15 341 0 0 1 0.8704 0 78.33
16 341 2 0.0058 0.9941 0.8653 3.33 81.66
17 341 0 0 1 0.8653 0 81.66
18 341 1 0.0029 0.9970 0.8628 1.66 83.33
19 341 1 0.0029 0.9970 0.8602 1.66 85
20 341 1 0.0029 0.9970 0.8577 1.66 86.66
21 341 1 0.0029 0.9970 0.855253 1.66 88.33
22 341 2 0.0058 0.9941 0.8502 3.33 91.66
23 341 0 0 1 0.8502 0 91.66
24 341 1 0.0029 0.9970 0.8477 1.66 93.33
31 341 1 0.0029 0.9970 0.8452 1.66 95
32 341 1 0.0029 0.9970 0.8427 1.66 96.66
43 341 1 0.0029 0.9970 0.8403 1.66 98.33
54 341 1 0.0029 0.9970 0.8378 1.66 100

%(R): Percentage of recurrence is calculated as number of recurrence in that period with total number of recurrences (56) as denominator. Cum% (R): Cumulative % of recurrence with increasing time period.


With only a single recurrence appreciated at 31, 32, 43 & 54 months postoperatively, it seems reasonable that the recurrence after 24 months is exceedingly rare but certainly suggests its theoretical possibility. Whether this is really a recurrence or a neo-occurrence of a fresh JNA at a different site cannot be established with the current data. In accordance we have seen such a neo-occurrence lately (submitted).


Fig. 2 depicts the Kaplan–Meier curve for all the 60 events across the 4 time intervals. It is worth noting that the chances of recurrence fall drastically after 24 months suggesting a minimum of 2 years of follow up as being adequate after surgery. The overall recurrence rate was 17.59% and this corresponded to 83% chances for the rest of population to remain recurrence-free as per Fig. 1 .




Fig. 2


Overall recurrence pattern of four decades.


Fig. 3 shows the comparison of Kaplan–Meier curves of 4 different time periods (A, B, C, D) corresponding to 4 decades. The p-value is > 0.05 ( Table 3 ) and hence the differences are not significant. The results of comparison of recurrence–time distributions by 3 tests i.e. Log-rank (Mantel Cox) test, Breslow (generalized Wilcoxon) test and Tarone–Ware test are shown in Table 3 and the summary is depicted in Appendix A . All the three tests gave the same results.




Fig. 3


Comparison of curves of 4 decades.

Curves 1, 2, 3, and 4 correspond with the time periods A, B, C, and D.

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Aug 23, 2017 | Posted by in OTOLARYNGOLOGY | Comments Off on Time trends in recurrence of juvenile nasopharyngeal angiofibroma: Experience of the past 4 decades

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