Annals of Oncology 13 (Supplement 1): 67–74, 2002
DOI: 10.1093/annonc/mdf613
Symposium article
Prognostic factors in Hodgkin’s lymphoma
T. Zander, S. Wiedenmann & J. Wolf*
Department of Internal Medicine I, University of Cologne, Cologne, Germany
Risk-adapted treatment strategies have constituted a major issue since the beginning of clinical research
into Hodgkin’s disease (HD). Various prognostic factors have been identified and several of those
considered for staging procedures, resulting in strictly stage-dependent treatment recommendations for
patients suffering from HD. These factors may be subdivided in host-related (e.g. age, sex) and tumourrelated (e.g. number of tumour cells, growth characteristics, spread of tumour cells, resistance to
apoptosis) factors. Owing to the striking improvement of the overall prognosis in HD patients it may be
difficult to identify novel prognostic factors analysing the minority of patients with a fatal outcome.
However, especially in advanced-stage disease, improved treatment results were achieved by the introduction of more aggressive treatment regimens, resulting in an increased toxicity rate. Thus, partially in
contrast to earlier work in this field, future prognostic factors are needed for identification of those
patients that have a good prognosis and might be susceptible to overtreatment. During the Fifth International Symposium on Hodgkin’s Lymphoma, promising results on several new prognostic markers
were presented. Furthermore, a joint effort to design new studies on large, well characterised patient
groups has been initiated.
Key words: Hodgkin’s lymphoma, prognostic factors, risk, treatment strategies
Introduction
Prognosis of patients with Hodgkin’s lymphoma (HL) has
been impressively improved during recent decades. While
until the 1960s only a minority of patients (i.e. patients with
localised disease treated with radiotherapy) could be cured at
all, the introduction of the mechlorethamine, vincristine, procarbazine, prednisone (MOPP) polychemotherapy regimen by
de Vita and coworkers at the National Cancer Institute (NCI)
and later the ABVD (doxurubicin, bleomycin, vinblastine and
dacarbazine) regimen by Bonadonna and the Milan group
resulted in a long-term survival of 66%, even including
patients with stage IV disease [1, 2]. Simultaneously, improvement of radiotherapy techniques (i.e. megavoltage irradiation,
linear accelerator) led to a consistent cure rate of 90% and
more in patients with early and intermediate stage (i.e. early
stage unfavourable) patients who received combined-modality
treatment. Recently, the introduction of novel dose-escalated
regimens like bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisone (BEACOPP)
resulted in improved survival of patients with advanced-stage
disease indicated by 3-year survival rates of up to 92% [3].
Since the early days of HL treatment, therapeutic decisions
have been made by subdividing this entity into different prog-
*Correspondence to: Dr J. Wolf, Department of Internal Medicine I,
University of Cologne, Joseph-Stelzmann-Str. 9, D-50924 Cologne,
Germany. Tel: +49-221-478-3410; Fax: +49-221-478-6733;
E-mail: [email protected]
© 2002 European Society for Medical Oncology
nostic subgroups. Certainly, the Ann Arbor classification [4],
based on the anatomical extent and the tumour activity
(B-symptoms), had an enormous clinical impact, even though
many further prognostic factors have been identified. Prognostic factors are defined as variables measured in patients
that aid explanation of the heterogeneity of outcome and
might predict, with more or less accuracy, the clinical outcome of a single patient. Furthermore, they may help the
understanding of the biological features of the tumour. From a
theoretical point of view the prognosis of a patient is
influenced by the interaction between tumour (tumour-related
factors) and ‘host’ (patient-related characteristics) [5]. Therefore, critical parameters are the amount of tumour cells as well
as their specific characteristics (e.g. growth characteristics,
chemoresistance, immune escape, resistance to apoptosis) and
the ability of the ‘host’ to eliminate remaining tumour cells
(e.g. immunocompetence) and tolerate therapeutic regimens
(e.g. performance status, susceptibility to acute toxicity and
late toxicity such as secondary malignancies). Prognostic
factors reflect these interactions in a better or worse way.
In this review we want to summarise the data on prognostic
factors in HL, emphasising their great impact on the improvement of prognosis but also showing their limits due to the outstanding overall survival (OS) rates of this entity today. In
light of the price of high cure rates characterised by overtreatment of many patients, especially in advanced-stage HD, the
importance of defining good prognosis in contrast to earlier
approaches defining poor prognosis might gain more importance.
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Amount of tumour cells
Different measurable parameters describe the dissemination
and number of tumour cells. Each therapy intended to kill
tumour cells reduces these cells in a given proportion [6].
Therefore, the total number of tumour cells is one parameter to
predict the effect of an anti-neoplastic therapy. Furthermore,
the growing fraction, which is vulnerable to chemo- or radiotherapy, is smaller in large tumours [7]. Bulky mediastinal disease describes the number of tumour cells in the mediastinum.
Consensus exists on its prognostic value in early stage HD as
demonstrated for disease-free survival (DFS) in different
studies for patients treated with radiotherapy alone [8–12]. By
comparison, in advanced-stage HD treated with more aggressive therapies there are less consistent data on the prognostic
significance of mediastinal bulk [13–17]. Splenic involvement was shown to be of prognostic significance in an univariate analysis of patients treated with radiotherapy alone.
But the statistical significance disappeared when performing
multivariate analysis and after the introduction of multimodal
therapy [18–21]. In non-Hodgkin’s lymphoma (NHL), lactate
dehydrogenase (LDH) is a surrogate parameter of tumour mass
and is an accepted prognostic factor [22]. An elevated serum
LDH, which might reflect the total amount of tumour cells,
has also been shown to be of prognostic value in HD [23].
To define the number of tumour cells more precisely, different methods were developed for measuring the size of macroscopically involved areas. In several studies analysing patients
with different disease stages and treated with different therapies, the overwhelming prognostic relevance of the tumour
burden was confirmed, as pointed out by Specht during the
Fifth International Symposium on Hodgkin’s Lymphoma
[24–33]. The combination of macroscopic measurement of the
tumour with a microscopic estimation of the percentage of
tumour cells might even increase the predictive value of tumour
burden [34].
In the last decade, new parameters have been investigated to
predict prognosis. CD30, a member of the tumour necrosis
factor (TNF) family, although not specific for HD, is consistently expressed on Hodgkin’s and Reed–Sternberg (HRS)
cells and the CD30/CD30 ligand interaction is believed to be
crucial for the growth of HRS cells. In different studies, soluble CD30 had independent prognostic significance [35–37].
Data on 307 ABVD treated patients presented at the Fifth
International Symposium on Hodgkin’s Lymphoma further
underlined the independent prognostic value of this marker
[38]. As soluble CD30 correlates with stage and tumour
burden and is elevated in lymphocyte depleted HD [37, 39] it
might correlate with the number of HRS cells and therefore
predict clinical outcome.
Spread of tumour cells
In nearly all carcinomas spread of tumour cells equal to metastatic disease is the worst prognostic factor predicting the
incurability of the patient. The biological mechanisms underlying metastasis are the independency of tumour cells from
growth promoting stimuli in the microenvironment, the ability
to circulate through the blood and lymph system and the
invasive potential of these tumour cells [40]. Although different biological mechanisms might underlie the dissemination
of carcinoma and malignant lymphoma cells, disseminated,
i.e. stage III/IV, disease is also a negative prognostic factor in
malignant lymphomas [41].
HRS cells seem to be strongly dependent on their microenvironment, since they are extremely difficult to grow in
vitro. The majority of HD-derived cell lines were established
from cells in peripheral blood, pleural effusion, pericardial
effusion or bone marrow [42, 43] suggesting an in vivo adaption to liquid phase cultivation conditions in the course of
tumour progression. The Ann Arbor classification [4] describing the anatomic distribution and thus the dissemination of
tumour cells has been demonstrated to be of prognostic
relevance for DFS as well as for OS in several studies testing
different therapeutic regimens [23, 41, 44–49]. Consequently
the (modified) Ann Arbor classification is used in most therapeutic studies in HL to subdivide patients into different prognostic groups.
Different primary localisations of HD were shown to be of
prognostic significance. Bone marrow involvement, for example, had adverse prognostic value in patients with advancedstage HD treated with combination chemotherapy [50–52].
Other studies could not confirm these findings in previously
untreated patients [47, 53]. The rare pleural involvement has
also been shown to be of prognostic relevance in a mixed
population of patients with HD (primary and relapsed HD)
[1, 54]. Presentation of HD in the bone marrow as well as
pleural involvement may reflect the independency of HRS
cells from their physiological lymphoid microenvironment.
Further localisations of HD were only analysed in a few
studies and thus their prognostic value is questionable. Splenic
involvement and extranodal disease is taken into account by
the Ann Arbor classification, but overall impact on prognosis
seems to be small [1, 47–49, 55, 56]. In summary, whereas the
data on the prognostic value of the localisation of HD (bone
marrow, inguinal involvement, pleural involvement) are controversially discussed and seem to have only little impact on
prognosis, there is consensus about the pronounced prognostic
impact of dissemination of HD according to the Ann Arbor
classification.
Growth characteristics
The growth fraction of tumour cells can be assessed by
staining the Ki-67 antigen. In several neoplasias Ki-67 has
been shown to have a negative prognostic value [57, 58]. In
addition, in HD the growth fraction of the malignant cells is of
prognostic relevance [59–61]. Similiar to Ki-67, proliferating
cell nuclear antigen (PCNA) is a protein present only in prolif-
69
erating cells, which has been shown to be of prognostic value
in some studies [62]. The retinoblastoma tumour suppressor
gene is a protein interacting with the cell cycle influencing the
prognosis of several neoplasias [63, 64]. Only a few studies
have analysed retinoblastoma gene expression in HD [59, 65,
66]. In the study by Morente and colleagues a prognostic
impact of Rb expression is pointed out [59]. P53 is a further
protein that interacts with the cell cycle and often is mutated in
malignant cells. Data on the prognostic role of p53 expression
are controversial. A high index of p53 expressing cells has
been reported to have negative impact on the outcome of
patients suffering from HD [62]. Differing results were
obtained by Xerri et al. [67], as summarised by Nieder and colleagues [68]. Analysis of soluble p53 did not show prognostic
significance in HD [69] and mutations within the p53 gene are
rare events, which do not play a major pathogenetic role and
are not associated with EBV [70].
Resistance to apoptosis is a frequent characteristic of
malignant cells. One of the proteins preventing cells from
undergoing apoptosis is Bcl-2. Bcl-2 is expressed in a proportion of HRS cells. An elevated index of Bcl-2-positive cells
was shown to have a negative prognostic impact [62, 71–73],
which was confirmed on a large data set by Sarris and coworkers [38]. Van Spronsen further specified, that high amounts of
Bcl-2-expressing HRS cells surrounded by a low percentage
of Bcl-2-expressing T cells is associated with clinical prognosis [74]. Smolewski and colleagues further measured apoptotic cells by TUNEL staining, revealing a positive prognostic
value of a high frequency of apoptotic HRS cells [71]. The
proapoptotic Bax protein is expressed in HRS cells [75], but
no consistent data about its prognostic relevance exist [38].
Caspase-3 is a downstream element of the apoptotic cascade.
As Dukers and coworkers showed at the Fifth International
Symposium on Hodgkin’s Lymphoma, a high amount of
caspase-3-positive HRS cells predict a favourable clinical
outcome of these patients [76]. About 50% of HD cases are
Epstein–Barr virus (EBV) positive. LMP-1, an EBV-encoded
protein, is another protein that interacts in the apoptotic
cascade. In several studies LMP-1 expression was shown to
influence the prognosis of HD [59, 61, 77–79], but differing
results were obtained in other study groups [80].
Summarising these data one may conclude that differences
between the growth characteristics of HRS cells exist. A high
proportion of proliferating HRS cells and a small number of
apoptotic HRS cells or HRS cells susceptible to apoptosis
seem to have a negative prognostic impact. However, data
were collected in relatively small retrospective analyses and
the comparisons between different studies are difficult due to
differences in the populations analysed, the technical procedures and the clinical data presented.
Interaction of tumour and host
Interaction between host and tumour cells is reflected by the
unique pathomorphological appearance of HD. The HRS cells
are surrounded by a large number of non-malignant cells.
Since the early days of HD research, pathologists have
searched for morphological characteristics to describe HD and
to categorise patients into prognostic groups. The classification established in the 1960s by Lukes and Butler [81] was
confirmed in many studies [16, 21, 46, 82–84]. In a large data
set of the international database on HD, Gobbi and colleagues
demonstrated the prognostic value of histology stressing the
unfavourable prognosis of patients with lymphocyte depleted
HD [85]. Similarly a negative prognostic value was demonstrated for the lymphocyte depleted subtype in different studies [40, 86], but the number of patients suffering from this
subtype of HD is very small and even decreasing in recent
years. When comparing the nodular sclerosis (NS) and the
mixed cellularity (MC) subtype, respectively, with lymphocyte predominant HD (LPHD), histiotype added significant
prognostic value to tumour burden, the main prognostic factor
in the cited study [51]. The different biological behaviour of
LPHD has been considered in the new Revised European–
American Lymphoma (REAL) Classification opposing LPHD
to classical HD (CHD) [87]. As up to 70% of the study populations suffer from NS subtype, different efforts were made to
subdivide this subgroup. The British National Lymphoma
Investigation (BNLI) group categorised the NS type in two
subgroups, of which the NSII subtype with areas depleted
from lymphocytes and a large number of pleomorphic HRS
cells was associated with a decreased survival independently
of stage [88, 89]. However, other groups could not confirm
this prognostic difference [90]. At the Fifth International
Symposium on Hodgkin’s Lymphoma a further subclassification of NS histology was suggested using CD15, tissue
eosinophilia, lymphocytic depletion, extended necrosis and
atypical morphology of HRS cells as parameters [91].
Some groups focused on the non-malignant cells in HD
for the establishment of prognostic factors. The HRS cells are
surrounded by a high number of CD4+ T cells. Oudejans and
coworkers analysed CD8 granzyme B-positive T cells, demonstrating the negative prognostic impact of these cells [92].
Tissue eosinophilia was also shown to influence prognosis of
HL in a stage stratified model [93]. During the Fifth International Symposium on Hodgkin’s Lymphoma, Molin and
coworkers presented data on the prognostic value of mast cells
present in the affected lymph nodes [94]. Despite these
retrospective analyses the predictive value of the histopathological subtype is not pronounced enough to include it into
therapeutic decisions. Thus, in the current clinical trials of
nearly all major study groups, stage-dependent therapeutic
strategies are being clinically tested regardless of the histological subtype. A pathological grading with major prognostic
impact like in solid tumours has not been established.
B-symptoms have been known to be of clinical importance
for many years, and thus have been included in the Ann Arbor
classification and were confirmed in several studies [1, 8, 52,
56, 84, 85, 95–99]. B-symptoms correlate with other parameters used to predict prognosis, e.g. stage, erythrocyte
70
sedimentation rate (ESR) [27, 41, 56, 99], serum albumin [38,
41, 85] and haemoglobin [41]. All these parameters may have
their biological correlate in the spectrum and amount of
cytokines secreted by the tumour cells and the surrounding
lymphoid infiltrate. Specht pointed out that there is an inverse
relationship between accuracy of tumour mass assessment and
predictive value of B-symptoms [44]. This observation stresses
once more the great impact of the amount of tumours cells
compared with a rather weak impact of the characteristics of
the tumour cells in this special neoplasia. Several further
attempts were made to assess the interaction between tumour
cells and the host. ESR for example, which is thought to be the
result of a complex cytokine profile expressed by the host and
the tumour cells, was shown to have independent prognostic
significance for DFS and OS for different stages and several
therapeutic regimens [83, 100]. Albumin [41, 101, 102],
haemoglobin [23, 41, 103, 104], leukocytosis [41] and
lymphocytopenia [26, 86, 103] are further parameters describing the effect of cytokines secreted by malignant and nonmalignant reactive cells. Many further markers were correlated with prognosis. Factors like ferritin [105–107], coeruloplasmin, serum copper [107, 108], β2-microglobulin [32,
109–111] and thymidin kinase [112] may also reflect the
inflammatory re-action of the host.
VCAM-1 and ICAM-1 are adhesion molecules from the
immunoglobulin gene superfamily. Soluble forms of these
factors were analysed in HL by Christiansen and colleagues
and prognostic significance was shown [36, 113]. Soluble
VCAM-1 and ICAM-1 may help HRS cells to escape the
immune system by competitively inhibiting the function of
ligand receptors [114, 115]. HRS cells are surrounded by multiple lymphoid cells. An intensive interaction between these
predominantly T-helper (Th) 2 cells and HRS cells is reflected
by multiple cytokines and chemokines secreted by both cell
types. Several studies were performed measuring these
cytokines [interleukin (IL)-2r, TNFr, TNFα, IL2Rα, IL-6,
IL-7, IL-8, IL-10, IL-12, IL-13] and correlating them with
clinical outcome of patients [69, 116–121]. IL-10 is one of
these cytokines produced by HRS cells and able to suppress a
Th1 proliferation, which turned out to be of prognostic significance in advanced-stage HD [35, 120, 122, 123], which
was confirmed by data on 307 ABVD-treated patients
presented by Sarris and coworkers at the Fifth International
Symposium on Hodgkin’s Lymphoma [38]. IL-10 was further
shown to be much more prominent in the EBV-associated
cases [124]. A further marker, which was analysed in several
studies, is sCD25, the soluble IL-2 receptor and its correlation
to clinical stage and prognosis was shown [36, 125–129].
Inconsistent data exist about further cytokines and their prognostic value. Primary results on cytokines in HD are promising but further studies need to be conducted in a randomised,
multicentre setting with more patients to prove the additive
prognostic value of these parameters.
Patient characteristics
Age is not only a risk factor in HD. Several aspects have to be
taken into account when analysing age as a biological risk
factor. First, increased morbidity and mortality in older patients
due to other causes has to be considered and results have to
be matched to the general population. Secondly, increased
co-morbidity results in augmented therapy-related morbidity
(acute toxicity as well as late adverse effects as cardiac disease
and secondary neoplasia) [130, 131]. Therefore, taking comorbidity into account when analysing age as a prognostic
factor is of major interest [132]. Nevertheless, in studies
matching patients to the general population, considering additional prognostic factors and performing multivariate analysis
age has been shown to have adverse prognostic impact for different stages and therapies [46, 84, 88, 133–136]. Reduced
capacity of the immune system in older age has been hypothesised to play a role for the worse outcome of these patients.
Sex is a further well known but pathophysiologically not
well understood prognostic factor [10, 27, 41, 46, 83, 88].
Difference in HD between males and females is not only a
reflection of the predominance of NS histology, which may
explain part of the better prognosis in female patients, as convincingly demonstrated by Specht [44].
Perspectives
Several factors have been identified as prognostic factors in
HL. However, in view of the excellent prognosis of the majority of HD patients, prognosis for patients with stage adapted
modern therapy is nearly equal for each clinical stage as
demonstrated by Hasenclever [137]. This observation retrospectively underlines the great importance of the ‘classical’
prognostic factors that have already been included into staging
procedures. Concerning future attempts to identify new prognostic factors some difficulties may arise. As measurable
events such as treatment failure and death of HD become rare,
an enormous number of patients has to be analysed in prospective studies for the establishment of new prognostic factors. To
circumvent this problem, retrospective material from patients
treated with less aggressive therapies might be examined.
New information, however, will only be obtained if the markers studied will stratify patients better than the existing prognostic scores. Similar conclusions were drawn by Iannitto,
Henry-Amar and colleagues after a comparison of different
prognostic scores [138, 139]. They confirmed the need for the
improvement of existing prognostic scores while assuming
that single new prognostic factors will have little clinical
impact.
To overcome the problem of the low numbers of patients in
prognostic factor studies the combined effort of all interested
researchers is crucial. Therefore, at the Fifth International
Symposium on Hodgkin’s Lymphoma great interest was
expressed in planning joint studies to create large data sets that
would allow further refinement of existing prognostic factors.
71
The importance of prospectively collecting biological material in ongoing and planned clinical studies was underlined.
Furthermore, a large consensus existed about the importance
of defining risk factors for late therapy-related adverse events,
especially therapy-induced leukemia.
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