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Keywords:

  • mantle cell lymphoma;
  • beta-2 microglobulin;
  • absolute monocyte count;
  • microenvironment;
  • international prognostic index

Summary

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

An increased number of circulating monocytes at presentation has recently been associated with shorter survival in Hodgkin lymphoma, follicular lymphoma and diffuse large B cell lymphoma. This study aimed to assess the prognostic impact of the absolute monocyte count (AMC) at diagnosis in mantle cell lymphoma (MCL). AMC at diagnosis was available in 97 MCL cases recorded in the databases of the Oncology Institute of Southern Switzerland in Bellinzona (Switzerland) and the Division of Haematology of the Amedeo Avogadro University of Eastern Piedmont in Novara (Italy). With a median follow up of 7 years, the 5-year overall survival was 29% for patients with AMC >0·50 × 109/l and 62% for patients with AMC ≤0·50 × 109/l (= 0·008). Elevated AMC and beta-2 microglobulin at diagnosis remained independent outcome predictors at multivariate analysis, controlling for the MCL International Prognostic Index (MIPI), and have been used to build a simple prognostic scoring system. In this relatively small and heterogeneous series an increased AMC identified poor-risk patients. Our results suggest that AMC together with the beta-2 microglobulin level might provide an inexpensive way to stratify MCL patient risk as a complement to the MIPI, which was confirmed to be a very powerful prognostic tool.

Mantle cell lymphoma (MCL) is a specific entity characterized by the chromosomal translocation t(11;14)(q13;q32), resulting in constitutional overexpression of cyclin D1 and subsequent cell cycle deregulation. This lymphoma accounts for 3–10% of non-Hodgkin lymphoma cases and occurs most frequently in middle-aged to older males with a median age at presentation in the seventh decade of life (Bertoni et al, 2006; Swerdlow et al, 2008; Perez-Galan et al, 2011). MCL represents the B cell lymphoma subtype with the poorest long-term outcome; most patients show an aggressive clinical course with a continuous relapse pattern and a median survival of only 3–4 years in historical series (Zucca et al, 1995; Ghielmini & Zucca, 2009). The introduction of intensive programmes of immune-chemotherapy and autologous stem cell transplantation has apparently led to a survival improvement (Ghielmini & Zucca, 2009). However, since these aggressive treatment strategies can be adopted only in young and fit patients, MCL prognosis remains dismal in most patients. A minority of cases, however, displays an initially indolent clinical course (Martin et al, 2009). Because of this clinical heterogeneity, many efforts have been made in order to tailor treatments according to the expected prognosis in different patient subsets (Hoster et al, 2008; Geisler et al, 2010; Nygren et al, 2012).

Most of the available prognostic indicators comprise clinical features of the patients and biological characteristics of the tumour cells, whereas scant data are available on the microenvironment contribution to the patients' biological and clinical diversity. In regard to the relevance of the tumour microenvironment in B-cell neoplasms, there is growing attention to the role of monocytes and macrophages, which may suppress anti-tumour immunity, promote tumour angiogenesis, and drive the growth and survival of malignant lymphocytes (Burger & Ford, 2011; Coupland, 2011). The absolute monocyte count (AMC) in peripheral blood has been proposed as a useful prognostic tool in several lymphoma subtypes (Wilcox et al, 2011, 2012; Koh et al, 2012; Li et al, 2012; Porrata et al, 2012a,b,c; Tadmor et al, 2012), but only a small amount of information is available in MCL patients (Hoster et al, 2008).

The aim of the present study was to assess the prognostic significance of the AMC in the peripheral blood at diagnosis in a population of consecutive patients with MCL.

Patients and methods

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

The electronic databases of all non-Hodgkin lymphoma (NHL) cases treated at two centres (the Oncology Institute of Southern Switzerland – IOSI, and the Division of Haematology of the Amedeo Avogadro University of Eastern Piedmont in Novara, Italy) from 1980 to 2011 contain 2426 records, including 142 histologically reviewed MCL patients (Conconi et al, 2013). These databases have a common structure and contain information on the main demographic and clinicopathological features of each patient at presentation, as well as data on treatment type and treatment outcome. The leucocyte counts including AMC were assessed in 97 MCL patients by routine blood cell counts obtained at the time of diagnosis; confirmation by visual examination of blood smear was required in the case of abnormal automated counts.

Performance status (PS) was defined according to the Eastern Cooperative Oncology Group (ECOG) scale. Proliferation index (Ki-67 index) was assessed by immunohistochemistry. The international prognostic index (IPI) and the MCL International Prognostic Index (MIPI) were determined as previously described (The International Non-Hodgkin's Lymphoma Prognostic Factors Project's, 1993; Hoster et al, 2008). Overall survival (OS) and cause-specific survival (CSS) were defined according to the revised National Cancer Institute criteria (Cheson et al, 2007) and estimated using the Kaplan-Meier or the life-table method as appropriate (Kaplan & Meier, 1958). Differences between survival curves were analysed using the log-rank test for equality of survival functions (Kalbfleisch & Prentice, 1980). Follow-up was calculated as the median time to censoring using a reverse Kaplan-Meier analysis (Altman et al, 1995). The potential prognostic factors were analysed as discrete variables with the cut-off values commonly reported in the literature. The Cox proportional hazards model (Cox, 1972) was used for the estimation of hazard ratio and its confidence interval (with Wald test P-values) in both univariate and multivariate analysis. The exact 95% confidence intervals (95% CI) were calculated for incidence percentages. Either the χ2 test or the Fisher's exact test was used for testing associations in two-way tables, as appropriate. P values of 0·05 or less (two-sided test) were considered to indicate statistical significance. Statistical analysis was conducted using the STATA 5.0 software package (Stata Corporation 1997. Stata Statistical Software: Release 5.0. College Station, TX, USA) and the R software environment (r-project.org).

Results

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

Patients' population

Among 142 consecutive MCL patients included in our databases, information on the AMC at the time of diagnosis was available in 97 cases, which represent the subject of the present study. Median AMC was 0·50 × 109/l (interquartile range 0·32–0·70). The main clinical features are reported in Table 1; these characteristics were not significantly different from those of the patients excluded from the study because of the missing AMC value, with the exception of the bone marrow involvement rate (73% in the study population and 55% in the excluded cases) and lactate dehydrogenase (LDH) value (elevated in 34% of the study population and in 59% of the excluded cases).

Table 1. Clinical features of the 97 MCL patients at diagnosis
CharacteristicPatients, n (%)a
  1. ECOG PS, Eastern Cooperative Oncology Group performance status; LDH, lactate dehydrogenase; IPI, international prognostic index; MIPI, MCL international prognostic index.

  2. a

    Percentages may not total 100 due to rounding.

Median age (interquartile range)69 years (61–78)
Median absolute leucocyte count (interquartile range)8·2 (6·0–16·6) × 109/l
Median absolute monocyte count (interquartile range)0·50 (0·32–0·70) × 109/l
Median absolute lymphocyte count (interquartile range)2·30 (1·5–9·4) × 109/l
Gender
Male67 (69)
ECOG PS
>114 (14)
B symptoms
Present25 (25)
Bulky disease (= 45)
(Max nodal lesion > 7 cm)11 (24)
Extranodal involvement
>1 site67 (69)
Bone marrow involvement71 (73)
Ann Arbor stage
I-II17 (18)
III-IV80 (82)
Serum LDH (= 96)
(>Normal upper value)35 (36)
Serum beta-2-microglobulin (= 65)
(>Normal upper value)45 (69)
Histologic subtype (= 97)
Classical93 (96)
Blastoid variant4 (4)
Ki-67 index (= 33)
<10%1 (3)
10–29%16 (48)
≥30%16 (48)
IPI (= 96)
Low/low-intermediate risk32 (33)
Intermediate-high/high risk64 (67)
MIPI (= 96)
Low risk24 (25)
Intermediate risk26 (27)
High risk46 (48)

Treatment at diagnosis

Eleven patients did not receive treatment at diagnosis; in six of them, systemic treatment followed an initial watchful waiting strategy, while the other five were never treated. Of the 92 treated patients, two patients received local therapeutic interventions only: splenectomy in one patient and radiotherapy in the other. Eighty-six patients were treated with chemotherapy [40 with single alkylating agents or the CVP regimen (cyclophosphamide, vincristine, prednisolone), 40 with CHOP (cyclophosphamide, doxorubicin, vincristine, prednisolone)-like regimens and six patients with the hyper-CVAD regimen (cyclophosphamide, vincristine, doxorubicin, dexamethasone) alternated with high-dose methotrexate (MTX) and cytarabine therapy]. Thirty-four patients received rituximab, 30 in combination with chemotherapy and four as single agent. Six patients had autologous stem cell transplantation as part of their front line treatment. All treatment strategies were similarly distributed between patients with higher and lower AMC values at diagnosis.

General outcome

At the time of analysis 56 patients have died. With a median follow up of 7 years (95% CI, 4–15·6 years), the Kaplan-Meier estimate of the median OS of the whole population was 4·5 years (95% CI, 2·8–7·8 years) and the median CSS was 6·4 years (95% CI, 3·4–10·4 years). The OS and CSS at 5 years were 48% (95% CI, 36–59%) and 56% (95% CI, 43–66%) respectively.

Monocyte counts and other prognostic factors

The correlation between clinical features at diagnosis and the survival endpoints (OS, CSS) has been explored by both univariate (Table 2) and multivariate (Table 3) analyses.

Table 2. Univariate analysis (Cox regression) of the main prognostic factors for overall survival and cause specific survival. (A) For each continuous variable the hazard ratio (HR) and its confidence interval (95% CI) are given together with the P-value derived from the Wald test. (B) For the dichotomized or discrete variables, HR and its 95% CI are reported together with the Kaplan Meier estimates of the median survival time in years for each subgroup and the corresponding P-value derived from the log-rank test
(A) Continuous variables (= 97)Overall survivalCause-specific survival
HR95% CIP-valueHR95% CIP-value
AMC (increases of 0·10 × 109/l)1·071·02–1·120·0021·071·02–1·120·008
WBC (increases of 1 × 109/l)1·0061·0002–1·0110·0421·0061·00 005–1·0120·048
ALC (increases of 1 × 109/l)1·0030·996–1·0090·4171·0030·996–1·0090·421
(B) Discrete variablesMedian OS (years)HR95% CIP-valueMedian CSS (years)HR95% CIP-value
  1. AMC, absolute monocyte count; WBC, absolute leucocyte count; ALC, absolute lymphocyte count; ECOG PS, Eastern Cooperative Oncology Group performance status; LDH, serum lactate dehydrogenase level; Beta-2 MG, serum beta-2 microglobulin level; IPI, international prognostic index; MIPI, MCL international prognostic index; NR, not reached; HR, hazard ratio; CI, confidence interval.

  2. a

    P-value from log-rank test for trend.

AMC
≤0·5 × 109/l (= 50)7·82·061·19–3·550·00819·42·251·21–4·170·0087
>0·5 × 109/l (= 47)2·42·8
WBC
≤10 × 109/l (= 59)6·01·821·06–3·110·0278·61·540·83–2·850·165
>10 × 109/l (= 38)2·53·1
ALC
≤0·6 × 109/l (= 4)10·02·670·64–11·030·15921·04·070·56–29·830·134
>0·6 × 109/l (= 93)4·56·0
ECOG PS
≤1 (= 83)5·42·541·27–5·080·00637·33·041·44–6·380·0021
>1 (= 14)0·71·0
Age
≤60 years (= 19)9·52·441·14–5·210·0179·51·790·82–3·900·138
>60 years (= 78)3·15·5
Ki67
≤30% (= 17)9·55·701·51–21·650·00439·54·080·98–16·890·037
>30% (= 16)1·66·4
LDH
Normal (= 61)6·42·121·23–3·650·00558·62·361·28–4·360·0045
Elevated (= 35)1·72·7
Beta-2 MG
Normal (= 20)NR4·311·51–12·340·003NR4·631·38–15·510·0064
Elevated (= 45)4·04·8
B symptoms
No (= 72)5·51·831·04–3·210·0347·32·021·08–3·790·025
Yes (= 25)2·22·7
IPI
Low (= 18)10·41·481·12–1·940·0046a10·41·551·13–2·120·0055a
Low-int (= 14)2·82·9
Int-high (= 34)6·4NR
High (= 30)1·41·5
MIPI
Low (= 24)10·02·591·73–3·89<0·0001a10·42·351·50–3·69<0·0001a
Intermediate (= 26)6·48·6
High (= 46)1·51·5
Table 3. Multivariate analysis of the main prognostic factors: Cox regression model generated by backward selection of the significant variables identified by univariate analysis of OS (monocyte count, leucocyte count, age>60 years, LDH and beta-2 microglobulin higher than normal, ECOG PS > 1 and the presence of B symptoms; Ki-67 index was not included due to the high rate of missing observations)
VariableOverall survival = 65 (32 events)Cause-specific survival = 65 (25 events)
HR (95% CI)P-valueHR (95% CI)P-value
  1. HR, hazard ratio; CI, confidence interval; AMC, absolute monocyte count; ECOG PS, Eastern Cooperative Oncology Group performance status; Beta-2 MG, serum beta-2 microglobulin level.

AMC (continuous, for increments of 0·10 × 109/l)1·06 (1·01–1·12)0·0271·06 (1·003–1·13)0·038
Beta-2 MG (>normal)3·90 (1·35–11·28)0·0124·21 (1·24–14·31)0·021
ECOG PS (>1)3·21 (1·06–9·70)0·0394·22 (1·33–13·35)0·014

Absolute monocyte count at diagnosis ranged from 0·05 to 3·50 × 109/l and 14 patients (14%; 95% CI, 8–23%) had a count above the upper normal level (0·95 × 109/l). Univariate analysis of AMC both as a continuous and a dichotomized variable was performed. As a continuous variable, the number of circulating monocytes was significantly associated with shorter survival endpoints (Table 2). After dichotomization by the median, AMC>0·50 × 109/l predicted for shorter OS (= 0·0081) and CSS (= 0·0087), as shown in Fig 1. The 5-year OS was 62% (95% CI, 46–75%) in patients with AMC below 0·50 × 109/l and 29% (95% CI, 14–46%) in those with higher counts, while 5-year CSS rates were 70% (95% CI, 52–82%), and 38% (95% CI, 21–55%) respectively. The independent statistically significant prognostic value of AMC, with respect to OS and CSS was retained in Cox models (data not shown) controlling for the IPI but not in those including the MIPI, which overpowered any other prognostic factor in our series. In the subset of 34 patients receiving rituximab as part of their first line therapy, the AMC retained its prognostic impact on OS (= 0·0362), but this was not statistically significant with respect to CSS.

image

Figure 1. Outcome of mantle cell lymphoma patients according to the number of circulating monocytes at presentation. (A) overall survival. (B) cause-specific survival.

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Along with AMC, absolute white blood cell counts, proliferation index, ECOG PS, age, B-symptoms, serum LDH and beta-2 microglobulin levels had a significant impact on OS (Table 2).

The IPI and MIPI confirmed their capacity to define risk groups with different outcomes (Table 2) and the MIPI was the strongest predictor of OS and CSS controlling for the IPI in Cox regression analysis (data not shown). In contrast, gender, bulky disease, Ann Arbor stage, blastoid morphology, bone marrow involvement and involvement of more than one extranodal site did not show a statistically significant impact on any survival endpoint.

A backward selection, using a significance level of 0·05 for dropping variables, was employed to build a Cox proportional hazards model (Table 3), starting from the model with all the prognostic variables identified by univariate analysis of OS (absolute monocyte and white blood cell counts, age>60 years, LDH and beta-2 microglobulin higher than normal, ECOG PS > 1 and B symptoms). The Ki-67 proliferation index was not included in the model due to the high rate of missing observations. The IPI and MIPI also were not included as specific variables because the significant factors contributing to these indices were already present as individual parameters. The resulting final model comprised the AMC, ECOG PS and beta-2 microglobulin. This model was also able to predict CSS (Table 3).

After removing the ECOG PS, which is already included in IPI and MIPI, from the model, the AMC controlled for the beta-2 microglobulin levels maintained a significant impact on OS.

A simple prognostic scoring system could then be built by combining AMC and beta-2 microglobulin levels, which do not contribute to either the IPI or the MIPI. In fact, a score based on beta-2 microglobulin above the normal (2·3 mg/l) and AMC above the upper normal level (0·95 × 109/l) identified 3 groups of patients with significant differences in the survival parameters. We used the upper normal level of AMC instead of the median (which was also significant) in order to obtain a more easily reproducible score, as it does not depend on the median of our cohort. Score 0 corresponds to normal beta-2 microglobulin and AMC below the upper normal level, score 1 corresponds to beta-2 microglobulin or AMC above the upper limit of normal, score 2 corresponds to beta-2 microglobulin and AMC above the upper limit of normal. This scoring system can apparently identify three well-defined prognostic groups, with clearly different OS (= 0·0002) and CSS (= 0·0025). Figure 2 displays the Kaplan-Meier estimates of OS and CSS according to this index, which we named M2 score (from Monocyte and beta-2 Microglobulin).

image

Figure 2. Outcome of mantle cell lymphoma patients according to the M2 scoring system based on the beta-2 microglobulin levels and the number of circulating monocytes at presentation. Risk factors0’ corresponds to normal beta-2 microglobulin and normal absolute monocyte count (AMC); risk factors ‘1’ indicates that only one of the two parameter (beta-2 microglobulin or AMC) is above the upper limit of normal; risk factors ‘2’ indicates the presence of both beta-2 microglobulin and AMC above the upper limit of normal.

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The M2 score retained statistical significance at multivariate analysis of OS, after controlling for either the main other individual prognostic factors (i.e., leucocyte count, age, ECOG PS, LDH and B symptoms, data not shown), the IPI or the MIPI (Table 4).

Table 4. Cox regression models estimating the effect of the M2 score on overall survival after adjustment for the MIPI (A) and the IPI (B)
(A) Cox proportional hazards model controlling for the MIPI
= 64 (31 events)
VariableHR (95% CI)P-value
M2 score2·04 (1·04–3·99)0·037
MIPI1·99 (1·10–3·60)0·023
(B) Cox proportional hazards model controlling for the IPI
= 64 (31 events)
VariableHR (95% CI)P-value
  1. HR, hazard ratio; CI, confidence interval; M2 score, prognostic scoring system combining monocyte count and beta-2 microglobulin level; MIPI, MCL international prognostic index; IPI, international prognostic index.

M2 score2·35 (1·20–4·63)0·013
IPI1·41 (0·89–2·23)0·143

Discussion

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

In the original publication of the MIPI score, AMC was one of the many clinical variables associated with shorter survival by univariate analysis, but it was excluded from multiple Cox regression due to missing data (Hoster et al, 2008). To our knowledge, no other studies assessing the role of AMC in MCL have been published to date. Here we studied the AMC at diagnosis in a retrospective cohort of unselected consecutive newly diagnosed MCL, presenting with an expected preponderance of cases with intermediate or high risk MIPI and IPI score and followed-up for a very prolonged period. An AMC above the median, in keeping with previous reports in other lymphoma subtypes (Wilcox et al, 2011), represented an independent and powerful predictor of poor outcome. The prognostic value of AMC was retained at multivariate analysis after controlling for the main other adverse prognostic indicators. The impact of AMC on survival may represent a proof of principle of the biological role of the tumour microenvironment in MCL course.

Interestingly, the multivariate analysis (Table 3) showed that the patient general fitness (ECOG PS), its immune system efficiency (monocyte count) and the tumour aggressiveness (beta-2 microglobulin) concur to determine the clinical outcome.

Tumour-associated macrophages (TAM) and monocytes can foster cancer progression by promoting proliferation and angiogenesis (Allavena & Mantovani, 2012). There is growing evidence that the survival of lymphoma patients can be influenced by the immune cells in the tumour microenvironment (Dave et al, 2004; Lenz et al, 2008; Steidl et al, 2010; Zaki et al, 2011) and the connivance of macrophages and monocytes with the proliferation of both neoplastic B and T lymphocytes has been documented in several experimental models (Mueller et al, 2007; de Totero et al, 2008; Wilcox et al, 2009; Valkovic et al, 2010; Perry et al, 2011; Epron et al, 2012; Guilloton et al, 2012; Ishii et al, 2012).

To date, gene expression profiling (GEP) studies have provided only limited information on the interaction of microenvironment and outcome in MCL (Burger & Ford, 2011) but signatures associated with monocytes, macrophages and dendritic cells may have a significant impact on survival in other lymphoma types, including follicular lymphoma (FL) (Dave et al, 2004), diffuse large B cell lymphoma (DLBCL) (Lenz et al, 2008) and classical Hodgkin lymphoma (HL) (Steidl et al, 2010).

The immunohistochemical expression of CD68 (an indicator of TAM infiltration) and the co-expression of CD68 with CD163 (an indicator of a specific subset of TAM), have been shown in some (but not all) studies to predict the outcome of HL, FL and DLBCL (Farinha et al, 2005; Kelley et al, 2007; Taskinen et al, 2007; Canioni et al, 2008; Hasselblom et al, 2008; de Jong et al, 2009; Steidl et al, 2010; Wahlin et al, 2010; Andjelic et al, 2012; Azambuja et al, 2012; Cai et al, 2012; Wada et al, 2012; Greaves et al, 2013).

The balance between T lymphocytes and monocytes in the microenvironment, which is representative of the anti-tumour immune surveillance, has been shown to have a detrimental impact on the outcome of FL patients when monocytes are preponderant on T lymphocytes (Dave et al, 2004; Byers et al, 2008). In line with this concept, the absolute counts of circulating monocytes (AMC) and lymphocytes (ALC) were studied in combination as surrogates of the microenvironment composition of different lymphoma subtypes. These studies showed that the increment of AMC associated with the reduction of ALC identifies patients with poor outcome in HL and DLBCL (Wilcox et al, 2011; Koh et al, 2012; Porrata et al, 2012b).

In our series, very few patients presented with lymphocytopenia, while 37% of patients had more than 4·0 × 109 lymphocytes/l and 25% more than 10 × 109 lymphocytes/l, indicating that a leukaemic presentation of the disease (which is not an uncommon event in MCL) could be a relevant concern in our study population. Alas, due to the incomplete flow cytometry and morphological data on the circulating lymphocytes, it was not possible to discriminate between normal lymphocytes and lymphoma cells in a significant proportion of cases. Therefore, we decided to exclude the AMC/ALC ratio from the analysis of prognostic factors, considering that this parameter could have been biassed by the presence of lymphoma cells.

During the last three decades the knowledge regarding clinical course and prognosis of MCL have thoroughly changed and therapeutic approaches have evolved accordingly (Ghielmini & Zucca, 2009; Perez-Galan et al, 2011). The aggressive clinical course observed in most cases led to the design of intensive therapeutic protocols including high dose chemotherapy followed by autologous stem cell transplantation, which, however, can be adopted only in a minority of young and fit patients (Ghielmini & Zucca, 2009). On the other hand, a subset of patients displays an initially indolent course and may not need immediate treatment (Martin & Leonard, 2011). In our series, 11% of patients underwent an initial expectant strategy and front-line aggressive strategies were adopted in only 9% of patients (including six who had autologous transplantation). The identification of clinicopathological features associated with different clinical courses may enable personalized treatments tailored along with the expected prognosis of the individual patient.

In our study, the MIPI remains the strongest tool to predict the patient outcome, however, also the absolute number of circulating monocytes at diagnosis – an inexpensive, easily ascertained and highly reproducible parameter in clinical practice – predicted the outcome independently of the main known prognostic features and indices (Table 3). A simple scoring system resulting from the combination of beta-2 microglobulin levels with AMC (Fig 2) appears in our cohort to possibly represent an additional prognostic tool (Table 4). If validated in larger independent series of homogeneously treated patients, it may be used as a complement to the MIPI to better stratify the patient risk.

Acknowledgements

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

We thank the precious contribution of Cristina Morinini and Elena Porro for the data management.

Author's Contributions

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

KAvH, AC, FB, GG and EZ designed the study. KAvH, AC, SF and GMC collected the data. EZ, AC, CPdC and KAvH performed the statistical analysis. KAvH, AC, and EZ wrote the manuscript and all authors critically reviewed it and contributed to its final version.

Funding

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References

This study has been partially supported by the grant KLS-01690-03-2005 from the Swiss Cancer League (Krebsliga Schweiz), by the Nelia and Amadeo Barletta Foundation (Lausanne, Switzerland), by the Ministry of Health, Ricerca Sanitaria Finalizzata (Rome, Italy), and by Novara-AIL Onlus (Novara, Italy).

References

  1. Top of page
  2. Summary
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Author's Contributions
  8. Funding
  9. Disclosures
  10. References
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