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.
References 1. Longo DL, Young RC, Wesley M et al. Twenty years of MOPP therapy for Hodgkin’s disease. J Clin Oncol 1986; 4: 1295–1306. 2. Bonadonna G, Santoro A, Bonfante V, Valagussa P. Cyclic delivery of MOPP and ABVD combinations in Stage IV Hodgkin’s disease: rationale, background studies, and recent results. Cancer Treat Rep 1982; 66: 881–887. 3. Diehl V, Franklin J, Paulus U et al. BEACOPP chemotherapy improves survival, and dose escalation further improves tumour control in advanced-stage Hodgkin’s disease: GHSG HD9 results. Leuk Lymphoma 2001; 42 (Suppl 2): 16. 4. Carbone PP, Kaplan HS, Musshoff K et al. Report of the Committee on Hodgkin’s Disease Staging Classification. Cancer Res 1971; 31: 1860–1861. 5. Specht L. Prognostic factors in Hodgkin’s Disease. Semin Radiat Oncol 1996; 6: 146–161. 6. Skipper HE, Schabel FM Jr, Wilcox WS et al. Experimental evaluation of potential anticancer agents. 28. Effects of therapy on viability and rate of proliferation of leukemic cells in various anatomic sites. Cancer Chemother Rep 1965; 47: 41–64. 7. Watson JV. The cell proliferation kinetics of the EMT6/M/AC mouse tumour at four volumes during unperturbed growth in vivo. Cell Tissue Kinet 1976; 9: 147–156. 8. Anderson H, Deakin DP, Wagstaff J et al. A randomised study of adjuvant chemotherapy after mantle radiotherapy in supradiaphragmatic Hodgkin’s disease PS IA-IIB: a report from the Manchester Lymphoma Group. Br J Cancer 1984; 49: 695–702. 9. Cimino G, Biti GP, Anselmo AP et al. MOPP chemotherapy versus extended-field radiotherapy in the management of pathological stages I-IIA Hodgkin’s disease. J Clin Oncol 1989; 7: 732–737. 10. Crnkovich MJ, Leopold K, Hoppe RT, Mauch PM. Stage I to IIB Hodgkin’s disease: the combined experience at Stanford University and the Joint Center for Radiation Therapy. J Clin Oncol 1987; 5: 1041–1049. 11. Leslie NT, Mauch PM, Hellman S. Stage IA to IIB supradiaphragmatic Hodgkin’s disease. Long-term survival and relapse frequency. Cancer 1985; 55: 2072–2078. 12. Tarbell NJ, Thompson L, Mauch P. Thoracic irradiation in Hodgkin’s disease: disease control and long-term complications. Int J Radiat Oncol Biol Phys 1990; 18: 275–281. 13. Mauch P, Gorshein D, Cunningham J, Hellman S. Influence of mediastinal adenopathy on site and frequency of relapse in patients with Hodgkin’s disease. Cancer Treat Rep 1982; 66: 809–817. 14. Lee CK, Bloomfield CD, Goldman AI, Levitt SH. Prognostic significance of mediastinal involvement in Hodgkin’s disease treated with curative radiotherapy. Cancer 1980; 46: 2403–2409. 15. Farah R, Golomb HM, Hallahan DE et al. Radiation therapy for pathologic stage III Hodgkin’s disease with and without chemotherapy. Int J Radiat Oncol Biol Phys 1989; 17: 761–766. 16. Rodgers RW, Fuller LM, Hagemeister FB et al. Reassessment of prognostic factors in stage IIIA and IIIB Hodgkin’s disease treated with MOPP and radiotherapy. Cancer 1981; 47: 2196–2203.
17. Bonadonna G, Valagussa P, Santoro A. Prognosis of bulky Hodgkin’s disease treated with chemotherapy alone or combined with radiotherapy. Cancer Surv 1985; 4: 439–458. 18. Hoppe RT, Cox RS, Rosenberg SA, Kaplan HS. Prognostic factors in pathologic stage III Hodgkin’s disease. Cancer Treat Rep 1982; 66: 743–749. 19. Hoppe RT, Rosenberg SA, Kaplan HS, Cox RS. Prognostic factors in pathological stage IIIA Hodgkin’s disease. Cancer 1980; 46: 1240– 1246. 20. Mauch P, Goffman T, Rosenthal DS et al. Stage III Hodgkin’s disease: improved survival with combined modality therapy as compared with radiation therapy alone. J Clin Oncol 1985; 3: 1166–1173. 21. Powlis WD, Mauch P, Goffman T, Goodman RL. Treatment of patients with ‘minimal’ stage IIIA Hodgkin’s disease. Int J Radiat Oncol Biol Phys 1987; 13: 1437–1442. 22. Osterman B, Jonsson H, Tavelin B, Lenner P. Non-Hodgkin’s lymphoma in northern Sweden. Prognostic factors and response to treatment. Acta Oncol 1993; 32: 507–515. 23. Straus DJ, Gaynor JJ, Myers J et al. Prognostic factors among 185 adults with newly diagnosed advanced Hodgkin’s disease treated with alternating potentially noncross-resistant chemotherapy and intermediate-dose radiation therapy. J Clin Oncol 1990; 8: 1173– 1186. 24. Specht L, Nissen NI. Prognostic significance of tumour burden in Hodgkin’s disease PS I and II. Scand J Haematol 1986; 36: 367–375. 25. Specht L, Nissen NI. Prognostic factors in Hodgkin’s disease stage III with special reference to tumour burden. Eur J Haematol 1988; 41: 80–87. 26. Specht L, Nissen NI. Prognostic factors in Hodgkin’s disease stage IV. Eur J Haematol 1988; 41: 359–367. 27. Specht L, Lauritzen AF, Nordentoft AM et al. Tumor cell concentration and tumor burden in relation to histopathologic subtype and other prognostic factors in early stage Hodgkin’s disease. The Danish National Hodgkin Study Group. Cancer 1990; 65: 2594–2601. 28. Gobbi PG, Ghirardelli ML, Solcia M et al. Image-aided estimate of tumor burden in Hodgkin’s disease: evidence of its primary prognostic importance. J Clin Oncol 2001; 19: 1388–1394. 29. Gisselbrecht C, Brice P, Lepage E et al. Autologous bone marrow transplantation in Hodgkin’s disease. Nouv Rev Fr Hematol 1990; 32: 5–7. 30. Enblad G. Hodgkin’s disease in young and elderly patients. Clinical and pathological studies. Minireview based on a doctoral thesis. Ups J Med Sci 1994; 99: 1–38. 31. Specht L. Prognostic factors in early stage Hodgkin’s disease. Leuk Lymphoma 2001; 42 (Suppl 2): 9. 32. Maltas J, Angus B, Jack F et al. Improved estimation of tumour burden leads to better prognostic discrimination in classical Hodgkin’s disease in adults. Leuk Lymphoma 2001; 42 (Suppl 2): 79. 33. Specht L, Nordentoft AM, Cold S et al. Tumor burden as the most important prognostic factor in early stage Hodgkin’s disease. Relations to other prognostic factors and implications for choice of treatment. Cancer 1988; 61: 1719–1727. 34. Specht L. Tumour burden as the main indicator of prognosis in Hodgkin’s disease. Eur J Cancer 1992; 28A: 1982–1985. 35. Axdorph U, Sjoberg J, Grimfors G et al. Biological markers may add to prediction of outcome achieved by the International Prognostic Score in Hodgkin’s disease. Ann Oncol 2000; 11: 1405–1411. 36. Christiansen I, Enblad G, Kalkner KM et al. Soluble ICAM-1 in Hodgkin’s disease: a promising independent predictive marker for survival. Leuk Lymphoma 1995; 19: 243–251.
72 37. Nadali G, Tavecchia L, Zanolin E et al. Serum level of the soluble form of the CD30 molecule identifies patients with Hodgkin’s disease at high risk of unfavorable outcome. Blood 1998; 91: 3011– 3016. 38. Sarris AH, Kliche KO, Nadali G. Biologic factors in Hodgkin’s disease: a window into prognosis and a guide for investigational therapy. Leuk Lymphoma 2001; 42 (Suppl 2): 10. 39. Nadali G, Vinante F, Ambrosetti A et al. Serum levels of soluble CD30 are elevated in the majority of untreated patients with Hodgkin’s disease and correlate with clinical features and prognosis. J Clin Oncol 1994; 12: 793–797. 40. Engers R, Gabbert HE. Mechanisms of tumor metastasis: cell biological aspects and clinical implications. J Cancer Res Clin Oncol 2000; 126: 682–692. 41. Hasenclever D, Diehl V. A prognostic score for advanced Hodgkin’s disease. International Prognostic Factors Project on Advanced Hodgkin’s Disease. N Engl J Med 1998; 339: 1506–1514. 42. Diehl V, Kirchner HH, Schaadt M et al. Hodgkin’s disease: establishment and characterization of four in vitro cell lies. J Cancer Res Clin Oncol 1981; 101: 111–124. 43. Wolf J, Kapp U, Bohlen H et al. Peripheral blood mononuclear cells of a patient with advanced Hodgkin’s lymphoma give rise to permanently growing Hodgkin/Reed–Sternberg cells. Blood 1996; 87: 3418–3428. 44. Specht L. Prognostic factors in Hodgkin’s disease. Cancer Treat Rev 1991; 18: 21–53. 45. Specht L. Prognostic factors in Hodgkin’s disease. Semin Radiat Oncol 1996; 6: 146–161. 46. Tubiana M, Henry-Amar M, Carde P et al. Toward comprehensive management tailored to prognostic factors of patients with clinical stages I and II in Hodgkin’s disease. The EORTC Lymphoma Group controlled clinical trials: 1964–1987. Blood 1989; 73: 47–56. 47. Pillai GN, Hagemeister FB, Velasquez WS et al. Prognostic factors for Stage IV Hodgkin’s disease treated with MOPP, with or without bleomycin. Cancer 1985; 55: 691–697. 48. Prosnitz LR, Farber LR, Kapp DS et al. Combined modality therapy for advanced Hodgkin’s disease: long-term follow-up data. Cancer Treat Rep 1982; 66: 871–879. 49. Jaffe HS, Cadman EC, Farber LR, Bertino JR. Pretreatment hematocrit as an independent prognostic variable in Hodgkin’s disease. Blood 1986; 68: 562–564. 50. Bartl R, Frisch B, Burkhardt R et al. Assessment of bone marrow histology in Hodgkin’s disease: correlation with clinical factors. Br J Haematol 1982; 51: 345–360. 51. Specht L, Nissen NI. Prognostic factors in Hodgkin’s disease stage IV. Eur J Haematol 1988; 41: 359–367. 52. Selby P, Patel P, Milan S et al. ChlVPP combination chemotherapy for Hodgkin’s disease: long-term results. Br J Cancer 1990; 62: 279– 285. 53. Wagstaff J, Steward W, Jones M et al. Factors affecting remission and survival in patients with advanced Hodgkin’s disease treated with MVPP. Hematol Oncol 1986; 4: 135–147. 54. Bonadonna G, Valagussa P, Santoro A. Alternating non-crossresistant combination chemotherapy or MOPP in stage IV Hodgkin’s disease. A report of 8-year results. Ann Intern Med 1986; 104: 739– 746. 55. Tubiana M, Henry-Amar M, Burgers MV et al. Prognostic significance of erythrocyte sedimentation rate in clinical stages I-II of Hodgkin’s disease. J Clin Oncol 1984; 2: 194–200.
56. Tubiana M, Henry-Amar M, Werf-Messing B et al. A multivariate analysis of prognostic factors in early stage Hodgkin’s disease. Int J Radiat Oncol Biol Phys 1985; 11: 23–30. 57. Miller TP, Grogan TM, Dahlberg S et al. Prognostic significance of the Ki-67-associated proliferative antigen in aggressive nonHodgkin’s lymphomas: a prospective Southwest Oncology Group trial. Blood 1994; 83: 1460–1466. 58. Gerdes J. Ki-67 and other proliferation markers useful for immunohistological diagnostic and prognostic evaluations in human malignancies. Semin Cancer Biol 1990; 1: 199–206. 59. Morente MM, Piris MA, Abraira V et al. Adverse clinical outcome in Hodgkin’s disease is associated with loss of retinoblastoma protein expression, high Ki67 proliferation index, and absence of Epstein– Barr virus-latent membrane protein 1 expression. Blood 1997; 90: 2429–2436. 60. Abele MC, Valente G, Kerim S et al. Significance of cell proliferation index in assessing histological prognostic categories in Hodgkin’s disease. An immunohistochemical study with Ki67 and MIB-1 monoclonal antibodies. Haematologica 1997; 82: 281–285. 61. Cheveresan L, Ionita H, Cheveresan M et al. Impact of bcl-2 expression, Ki67 proliferation index and Epstein–Barr virus-latent membrane protein 1 expression on the clinical outcome in Hodgkin’s disease patients. Leuk Lymphoma 2001; 42 (Suppl 2): 78. 62. Smolewski P, Niewiadomska H, Blonski JZ et al. Expression of proliferating cell nuclear antigen (PCNA) and p53, bcl-2 or C-erb B-2 proteins on Reed–Sternberg cells: prognostic significance in Hodgkin’s disease. Neoplasma 1998; 45: 140–147. 63. Sellers WR, Kaelin WG Jr. Role of the retinoblastoma protein in the pathogenesis of human cancer. J Clin Oncol 1997; 15: 3301–3312. 64. Cordon-Cardo C, Wartinger D, Petrylak D et al. Altered expression of the retinoblastoma gene product: prognostic indicator in bladder cancer. J Natl Cancer Inst 1992; 84: 1251–1256. 65. Kanavaros P, Stefanaki K, Vlachonikolis J et al. Expression of p53, p21/waf1, bcl-2, bax, Rb and Ki67 proteins in Hodgkin’s lymphomas. Histol Histopathol 2000; 15: 445–453. 66. Sanchez-Beato M, Martinez-Montero JC, Doussis-Anagnostopoulou TA et al. Anomalous retinoblastoma protein expression in Reed– Sternberg cells in Hodgkin’s disease: a comparative study with p53 and Ki67 expression. Br J Cancer 1996; 74: 1056–1062. 67. Xerri L, Bouabdallah R, Camerlo J, Hassoun J. Expression of the p53 gene in Hodgkin’s disease: dissociation between immunohistochemistry and clinicopathological data. Hum Pathol 1994; 25: 449– 454. 68. Nieder C, Petersen S, Petersen C, Thames HD. The challenge of p53 as prognostic and predictive factor in Hodgkin’s or non-Hodgkin’s lymphoma. Ann Hematol 2001; 80: 2–8 69. Trumper L, Jung W, Dahl G et al. Interleukin-7, interleukin-8, soluble TNF receptor, and p53 protein levels are elevated in the serum of patients with Hodgkin’s disease. Ann Oncol 1994; 5 (Suppl 1): 93– 96. 70. Maggio EM, Stekelenburg E, Van den BA, Poppema S. TP53 gene mutations in Hodgkin lymphoma are infrequent and not associated with absence of Epstein–Barr virus. Int J Cancer 2001; 94: 60–66. 71. Smolewski P, Niewiadomska H, Los E, Robak T. Spontaneous apoptosis of Reed–Sternberg and Hodgkin cells; clinical and pathological implications in patients with Hodgkin’s disease. Int J Oncol 2000; 17: 603–609. 72. Brink AA, Oudejans JJ, van den Brule AJ et al. Low p53 and high bcl-2 expression in Reed–Sternberg cells predicts poor clinical out-
73
73.
74.
75.
76.
77.
78.
79. 80.
81. 82.
83. 84.
85.
86.
87.
88.
89.
come for Hodgkin’s disease: involvement of apoptosis resistance? Mod Pathol 1998; 11: 376–383. Rassidakis GZ, Medeiros LJ, Nadali G et al. BCL-2 expression in Hodgkin/Reed–Sternberg cells UHRS: prognostic significance in Hodgkin’s disease (HD) patients. Leuk Lymphoma 2001; 42 (Suppl 2): 83. Van Spronsen DJ, Peh SC, Vrints LW et al. Clinical drug resistant nodular sclerosing Hodgkin’s lymphoma is associated with decreased Bcl-2 expression in the surrounding lymphocytes and with increased Bcl-2 expression in the Reed–Sternberg cells. Leuk Lymphoma 2001; 42 (Suppl 2): 79. Brousset P, Benharroch D, Krajewski S et al. Frequent expression of the cell death-inducing gene Bax in Reed–Sternberg cells of Hodgkin’s disease. Blood 1996; 87: 2470–2475. Dukers DF, Meijer CJLM, Vos W et al. High numbers of active caspase-3-positive Reed–Sternberg cells in pre-treatment biopsies of patients with Hodgkin’s diseases predict favourable clinical outcome. Leuk Lymphoma 2001; 42 (Suppl 2): 11. Montalban C, Abraira V, Morente M et al. Epstein–Barr virus-latent membrane protein 1 expression has a favorable influence in the outcome of patients with Hodgkin’s disease treated with chemotherapy. Leuk Lymphoma 2000; 39: 563–572. Murray PG, Billingham LJ, Hassan HT et al. Effect of Epstein–Barr virus infection on response to chemotherapy and survival in Hodgkin’s disease. Blood 1999; 94: 442–447. Morente MM, Montalbán C. EBV-LMP1 expression as prognostic factor. Leuk Lymphoma 2001; 42 (Suppl 2): 10. Von Wasielewski R, Wiebusch A, Mengel M et al. Clinical relevance of EBV-detection in Hodgkin’s disease. Leuk Lymphoma 2001; 42 (Suppl 2): 82. Lukes RJ, Butler JJ. The pathology and nomenclature of Hodgkin’s disease. Cancer Res 1966; 26: 1063–1083. Davis S, Dahlberg S, Myers MH et al. Hodgkin’s disease in the United States: a comparison of patient characteristics and survival in the Centralized Cancer Patient Data System and the Surveillance, Epidemiology, and End Results Program. J Natl Cancer Inst 1987; 78: 471–478. Gobbi PG, Cavalli C, Federico M et al. Hodgkin’s disease prognosis: a directly predictive equation. Lancet 1988; 1: 675–679. Sutcliffe SB, Gospodarowicz MK, Bergsagel DE et al. Prognostic groups for management of localized Hodgkin’s disease. J Clin Oncol 1985; 3: 393–401. Gobbi PG, Comelli M, Grignani GE et al. Estimate of expected survival at diagnosis in Hodgkin’s disease: a means of weighting prognostic factors and a tool for treatment choice and clinical research. A report from the International Database on Hodgkin’s Disease (IDHD). Haematologica 1994; 79: 241–255. Ranson MR, Radford JA, Swindell R et al. An analysis of prognostic factors in stage III and IV Hodgkin’s disease treated at a single centre with MVPP. Ann Oncol 1991; 2: 423–429. Harris NL, Jaffe ES, Stein H et al. A revised European-American classification of lymphoid neoplasms: a proposal from the International Lymphoma Study Group. Blood 1994; 84: 1361–1392. Haybittle JL, Hayhoe FG, Easterling MJ et al. Review of British National Lymphoma Investigation studies of Hodgkin’s disease and development of prognostic index. Lancet 1985; 1: 967–972. MacLennan KA, Bennett MH, Tu A et al. Relationship of histopathologic features to survival and relapse in nodular sclerosing Hodgkin’s disease. A study of 1659 patients. Cancer 1989; 64: 1686–1693.
90. Hess JL, Bodis S, Pinkus G et al. Histopathologic grading of nodular sclerosis Hodgkin’s disease. Lack of prognostic significance in 254 surgically staged patients. Cancer 1994; 74: 708–714. 91. Von Wasielewski R, von Wasielewski S, Franklin P et al. Nodular sclerosing HD: a new proposal to distinguish high-risk patients. Leuk Lymphoma 2001; 42 (Suppl 2): 82. 92. Oudejans JJ, Jiwa NM, Kummer JA et al. Activated cytotoxic T cells as prognostic marker in Hodgkin’s disease. Blood 1997; 89: 1376– 1382. 93. von Wasielewski R, Seth S, Franklin J et al. Tissue eosinophilia correlates strongly with poor prognosis in nodular sclerosing Hodgkin’s disease, allowing for known prognostic factors. Blood 2000; 95: 1207–1213. 94. Molin D, Edström A, Glimelius I et al. Mast cell infiltration in Hodgkin’s disease correlates with prognosis. Leuk Lymphoma 2001; 42 (Suppl 2): 66. 95. Dady PJ, McElwain TJ, Austin DE et al. Five years’ experience with ChlVPP: effective low-toxicity combination chemotherapy for Hodgkin’s disease. Br J Cancer 1982; 45: 851–859. 96. Fischer P, Franken T. A multivariate prognosis model for Hodgkin’s disease. Strahlentherapie 1984; 160: 535–542. 97. Hagemeister FB, Fuller LM, Velasquez WS et al. Stage I and II Hodgkin’s disease: involved-field radiotherapy versus extendedfield radiotherapy versus involved-field radiotherapy followed by six cycles of MOPP. Cancer Treat Rep 1982; 66: 789–798. 98. Jones SE, Haut A, Weick JK et al. Comparison of adriamycincontaining chemotherapy (MOP-BAP) with MOPP-Bleomycin in the management of advanced Hodgkin’s disease. A Southwest Oncology Group Study. Cancer 1983; 51: 1339–1347. 99. Tubiana M, Henry-Amar M, Hayat M et al. Prognostic significance of the number of involved areas in the early stages of Hodgkin’s disease. Cancer 1984; 54: 885–894. 100. Loeffler M, Pfreundschuh M, Hasenclever D et al. Prognostic risk factors in advanced Hodgkin’s lymphoma. Report of the German Hodgkin Study Group. Blut 1988; 56: 273–281. 101. Gobbi PG, Cavalli C, Gendarini A et al. Prognostic significance of serum albumin in Hodgkin’s disease. Haematologica 1986; 71: 95– 102. 102. Gobbi PG, Cavalli C, Federico M et al. Increasing interdependency of prognosis- and therapy-related factors in Hodgkin’s disease. Acta Haematol 1989; 81: 34–40. 103. Proctor SJ, Taylor P, Mackie MJ et al. A numerical prognostic index for clinical use in identification of poor- risk patients with Hodgkin’s disease at diagnosis. The Scotland and Newcastle Lymphoma Group (SNLG) Therapy Working Party. Leuk Lymphoma 1992; (7 Suppl): 17–20. 104. Hasenclever D, Schmitz N, Diehl V. Is there a rationale for highdose chemotherapy as first line treatment of advanced Hodgkin’s disease? German Hodgkin’s Lymphoma Study Group (GHSG). Leuk Lymphoma 1995; 15 (Suppl 1): 47–49. 105. Aulbert E, Steffens O. Serum ferritin–a tumor marker in malignant lymphomas? Onkologie 1990; 13: 102–108. 106. Bezwoda WR, Derman DP, Bothwell TH et al. Serum ferritin and Hodgkin’s disease. Scand J Haematol 1985; 35: 505–510. 107. Margerison AC, Mann JR. Serum copper, serum ceruloplasmin, and erythrocyte sedimentation rate measurements in children with Hodgkin’s disease, non-Hodgkin’s lymphoma, and nonmalignant lymphadenopathy. Cancer 1985; 55: 1501–1506.
74 108. Schulof RS, Bockman RS, Garofalo JA et al. Multivariate analysis of T-cell functional defects and circulating serum factors in Hodgkin’s disease. Cancer 1981; 48: 964–973. 109. Raida L, Hlusí A, Papajik T et al. Clinical significance of β2-microglobulin serum level in patients with Hodgkin’s lymphoma (single centre study). Leuk Lymphoma 2001; 42 (Suppl 2): 78. 110. Chronowski GM, Wilder RB, Tucker SL et al. Beta-2 microglobulin (B2M) is an adverse prognostic factor for overall survival in patients with early-stage Hodgkin’s disease. Leuk Lymphoma 2001; 42 (Suppl 2): 82. 111. Vassilakopoulos TP, Nadali G, Angelopoulou MK et al. The prognostic significance of β2-microglobulin in Hodgkin’s lymphoma. Leuk Lymphoma 2001; 42 (Suppl 2): 83. 112. Eriksson B, Hagberg H, Glimelius B et al. Serum thymidine kinase as a prognostic marker in Hodgkin’s disease. Acta Radiol Oncol 1985; 24: 167–171. 113. Christiansen I, Sundstrom C, Enblad G, Totterman TH. Soluble vascular cell adhesion molecule-1 (sVCAM-1) is an independent prognostic marker in Hodgkin’s disease. Br J Haematol 1998; 102: 701–709. 114. Becker JC, Termeer C, Schmidt RE, Brocker EB. Soluble intercellular adhesion molecule-1 inhibits MHC-restricted specific T cell/ tumor interaction. J Immunol 1993; 151: 7224–7232. 115. Meyer DM, Dustin ML, Carron CP. Characterization of intercellular adhesion molecule-1 ectodomain (sICAM-1) as an inhibitor of lymphocyte function-associated molecule-1 interaction with ICAM-1. J Immunol 1995; 155: 3578–3584. 116. Warzocha K, Bienvenu J, Ribeiro P et al. Plasma levels of tumour necrosis factor and its soluble receptors correlate with clinical features and outcome of Hodgkin’s disease patients. Br J Cancer 1998; 77: 2357–2362. 117. Gorschluter M, Bohlen H, Hasenclever D et al. Serum cytokine levels correlate with clinical parameters in Hodgkin’s disease. Ann Oncol 1995; 6: 477–482. 118. Gruss HJ, Dolken G, Brach MA et al. The significance of serum levels of soluble 60 kDa receptors for tumor necrosis factor in patients with Hodgkin’s disease. Leukemia 1993; 7: 1339–1343. 119. Kurzrock R, Redman J, Cabanillas F et al. Serum interleukin 6 levels are elevated in lymphoma patients and correlate with survival in advanced Hodgkin’s disease and with B symptoms. Cancer Res 1993; 53: 2118–2122. 120. Bohlen H, Kessler M, Sextro M et al. Poor clinical outcome of patients with Hodgkin’s disease and elevated interleukin-10 serum levels. Clinical significance of interleukin-10 serum levels for Hodgkin’s disease. Ann Hematol 2000; 79: 110–113. 121. Enblad G, Sundstrom C, Gronowitz S, Glimelius B. Serum levels of interleukin-2 receptor (CD 25) in patients with Hodgkin’s disease, with special reference to age and prognosis. Ann Oncol 1995; 6: 65– 70. 122. Vassilakopoulos TP, Nadali G, Angelopoulou MK et al. Serum interleukin-10 levels are an independent prognostic factor for patients with Hodgkin’s lymphoma. Haematologica 2001; 86: 274– 281.
123. Sarris AH, Kliche KO, Pethambaram P et al. Interleukin-10 levels are often elevated in serum of adults with Hodgkin’s disease and are associated with inferior failure-free survival. Ann Oncol 1999; 10: 433–440. 124. Dukers DF, Jaspars LH, Vos W et al. Quantitative immunohistochemical analysis of cytokine profiles in Epstein–Barr virus-positive and -negative cases of Hodgkin’s disease. J Pathol 2000; 190: 143– 149. 125. Ambrosetti A, Nadali G, Vinante F et al. Serum levels of soluble interleukin-2 receptor in Hodgkin disease. Relationship with clinical stage, tumor burden, and treatment outcome. Cancer 1993; 72: 201– 206. 126. Gause A, Jung W, Schmits R et al. Soluble CD8, CD25 and CD30 antigens as prognostic markers in patients with untreated Hodgkin’s lymphoma. Ann Oncol 1992; 3 (Suppl 4): 49–52. 127. Gause A, Roschansky V, Tschiersch A et al. Low serum interleukin-2 receptor levels correlate with a good prognosis in patients with Hodgkin’s lymphoma. Ann Oncol 1991; 2 (Suppl 2): 43–47. 128. Pizzolo G, Chilosi M, Vinante F et al. Soluble interleukin-2 receptors in the serum of patients with Hodgkin’s disease. Br J Cancer 1987; 55: 427–428. 129. Pui CH, Hudson M, Luo X et al. Serum interleukin-2 receptor levels in Hodgkin disease and other solid tumors of childhood. Leukemia 1993; 7: 1242–1244. 130. Balducci L, Phillips DM, Davis KM et al. Systemic treatment of cancer in the elderly. Arch Gerontol Geriatr 1988; 7: 119–150. 131. Peterson BA, Pajak TF, Cooper MR et al. Effect of age on therapeutic response and survival in advanced Hodgkin’s disease. Cancer Treat Rep 1982; 66: 889–898. 132. Pietrasanta D, D’Andrea E, Bertini M et al. Prognostic value of comorbidity in elderly patients affected by Hodgkin’s disease. Leuk Lymphoma 2001; 42 (Suppl 2): 85. 133. Vaughan HB, MacLennan KA, Easterling MJ et al. The prognostic significance of age in Hodgkin’s disease: examination of 1500 patients (BNLI report no. 23). Clin Radiol 1983; 34: 503–506. 134. Henry-Amar M, Somers R. Survival outcome after Hodgkin’s disease: a report from the international data base on Hodgkin’s disease. Semin Oncol 1990; 17: 758–768. 135. Specht L, Nissen NI. Hodgkin’s disease and age. Eur J Haematol 1989; 43: 127–135. 136. Straus DJ, Gaynor J, Myers J et al. Results and prognostic factors following optimal treatment of advanced Hodgkin’s disease. Recent Results Cancer Res 1989; 117: 191–196. 137. Hasenclever D. The disappearance of prognostic factors in Hodgkin’s disease. Ann Oncol 2002; 13 (Suppl 1): 75–78. 138. Iannitto E, De Cantis S, Cirrincione S et al. Comparison of seven models for prognostic evaluation of Hodgkin’s disease. Leuk Lymphoma 2001; 42 (Suppl 2): 81. 139. Henry-Amar M, Fremé C, Thomas J et al. Searching for new prognostic factors in Hodgkin’s lymphoma (HL): the EORTC-GELA experience. Leuk Lymphoma 2001; 42 (Suppl 2): 84.