Relationship Between Quality of Life and Survival in Patients With Pancreatic and Periampullary Cancer: A Multicenter Cohort Analysis

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  • 1 Department of Surgery, and
  • 2 Department of Medical Psychology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam;
  • 3 Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht;
  • 4 Department of Medical Oncology, Catharina Hospital, Eindhoven;
  • 5 Department of Medical Oncology, Isala Hospital, Zwolle;
  • 6 Department of Surgery, Erasmus Medical Center, Rotterdam;
  • 7 Department of Surgery, Catharina Hospital, Eindhoven;
  • 8 Department of Medical Oncology, Erasmus Medical Center, Rotterdam;
  • 9 Department of Internal Medicine, Division of Medical Oncology, GROW-School for Oncology and Developmental Biology, Maastricht UMC+, Maastricht;
  • 10 Department of Surgery, Regional Academic Cancer Center Utrecht, UMC Utrecht Cancer Center and St. Antonius Hospital, Utrecht;
  • 11 Department of Surgery, Isala Hospital, Zwolle;
  • 12 Division of Psychosocial Research & Epidemiology, Netherlands Cancer Institute, Amsterdam;
  • 13 Department of Medical and Clinical Psychology, Tilburg University, Tilburg; and
  • 14 Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

Background: A relationship between quality of life (QoL) and survival has been shown for several types of cancer, mostly in clinical trials with highly selected patient groups. The relationship between QoL and survival for patients with pancreatic or periampullary cancer is unclear. Methods: This study analyzed QoL data from a prospective multicenter patient-reported outcome registry in patients with pancreatic or periampullary carcinoma registered in the nationwide Netherlands Cancer Registry (2015–2018). Baseline and delta QoL, between baseline and 3-month follow-up, were assessed with the Happiness, EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30), and QLQ-PAN26 questionnaires. The relationship between QoL and survival was assessed using Cox regression models, and additional prognostic value of separate items was assessed using Nagelkerke R2 (explained variance). Results: For the baseline and delta analyses, 233 and 148 patients were available, respectively. Most were diagnosed with pancreatic adenocarcinoma (n=194; 83.3%) and had stage III disease (n=77; 33.0%), with a median overall survival of 13.6 months. Multivariate analysis using baseline scores indicated several scales to be of prognostic value for the total cohort (ie, happiness today, role functioning, diarrhea, pancreatic pain, and body image; hazard ratios all P<.05) and for patients without resection (ie, overall satisfaction with life, physical and cognitive functioning, QLQ-C30 summary score, fatigue, pain, constipation, diarrhea, and body image; hazard ratios all P<.05). Except for diarrhea, all QoL items accounted for >5% of the additional explained variance and were of added prognostic value. Multivariate analysis using delta QoL revealed that only constipation was of prognostic value for the total cohort, whereas no association with survival was found for subgroups with or without resection. Conclusions: In a multicenter cohort of patients with pancreatic or periampullary carcinoma, QoL scores predicted survival regardless of patient, tumor, and treatment characteristics. QoL scores may thus be used for shared decision-making regarding disease management and treatment choice.

Background

Patient-reported outcome measures (PROMs) are used increasingly in clinical practice to assess patients’ quality of life (QoL). Addressing QoL is important for patients with a short life expectancy, such as those with pancreatic and periampullary carcinoma, which has a median overall survival of 4 to 6 months.1 Different types of treatment that may improve survival in patients with pancreatic cancer may also impact QoL. Pancreatic resection has been found to be associated with a temporary deterioration in QoL, which usually returns to baseline values after 3 to 6 months.2,3 Moreover, chemotherapy has been found to improve QoL in randomized studies in the adjuvant and palliative setting.4,5

QoL may also be used to predict survival. Previous studies with other types of cancer (eg, breast, lung, esophageal, liver) consistently found a correlation between QoL and survival.611 Previous studies combined patients with different types of cancer, including a limited number (∼6%) of those with pancreatic cancer.9,10 Most of the data were acquired from randomized trials that included patients who were relatively fit. Only 1 case series of 55 patients with advanced pancreatic cancer suggested a prognostic relationship between the physical functioning scale scores of the EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) and survival.12

In the Netherlands, the Dutch Pancreatic Cancer Project (PACAP) was established in 2013. This is a multicenter cohort of patients with pancreatic and periampullary carcinoma for whom clinical data and PROMs are collected.13 We used this cohort to investigate the relationship between QoL and survival in daily clinical practice. The aim of this study was to examine which domains of QoL are predictive of survival in patients with pancreatic and periampullary cancer.

Methods

Study Design

This is a post hoc analysis of a prospective multicenter cohort of PROMs in patients with pancreatic and periampullary cancer. Currently, 48 centers in the Netherlands participate in the PACAP PROMs. Clinical data were included from the nationwide population-based Netherlands Cancer Registry (NCR). Both registries are incorporated within PACAP.13 Patients provided written informed consent for participation and linkage of their data between the registries. This study was designed in accordance with the STROBE guidelines.14

Study Population

Adult patients (aged ≥18 years) diagnosed with pancreatic and periampullary cancer in January 2015 through February 2018 who were registered in the NCR and participated in PACAP PROMs were included. Patients were excluded if they completed the baseline questionnaire after start of cancer treatment (n=143 of the total cohort).

Data Collection

The NCR data include patient, tumor, and treatment characteristics, such as date of diagnosis, age at diagnosis, sex, body mass index, comorbidities, ECOG performance status, pathologic diagnosis, tumor location, tumor stage (according to AJCC, 7th edition), tumor size, tumor differentiation grade, date of initial treatment, type of pancreatic resection, margin status (microscopically radical [R0] and irradical resection [R1]), (neo)adjuvant/palliative chemo(radio)therapy, biliary drainage, and survival data.15 PROMs at baseline and 3-month follow-up were used. Baseline measurement was defined as a measurement between the date of diagnosis and the start of first cancer treatment (eg, chemo[radio]therapy, resection, or local ablative therapy). Overall survival was defined as time between date of diagnosis and date of death.

QoL Assessment

The QoL data include data derived from the Happiness,16 EORTC QoL Questionnaire-Core 30 (QLQ-C30),17 and EORTC QLQ-PAN2618 questionnaires.19,20 The Happiness questionnaire consists of 4 items, including satisfaction with one’s life as a whole, happiness today, happiness during the last month, and the level at which one feels they currently stand on a scale from worst to best possible life. All items use a scale of 0 (worst) to 10 (best).16

The cancer-specific EORTC QLQ-C30 questionnaire encompasses global health status, 5 functioning scales (ie, physical, role, emotional, cognitive, and social functioning) and 8 symptom scales/items (ie, fatigue, nausea and vomiting, pain, dyspnea, insomnia, appetite loss, constipation, diarrhea), and financial difficulties. The pancreatic-specific EORTC QLQ-PAN26 questionnaire includes 9 disease- and treatment-related symptoms (pain, eating-related items, cachexia, hepatic symptoms, side effects, altered bowel habit, ascites, indigestion, and flatulence) and 5 emotional domains specific to pancreatic cancer (body image, healthcare satisfaction, sexuality, fear of future health, and ability to plan future). The items of the EORTC questionnaires use 4 response categories, which after linear transformation, form a scale ranging from 0 to 100. A higher score on the functional and global scales indicate better QoL, whereas for problems and symptoms, higher scores indicate poorer QoL. In addition, a summary score was obtained from the EORTC QLQ-C30 questionnaire21 based on the mean of all scale and item scores with the exclusion of global QoL and financial impact, and after reversing the scores of the symptom scales.

The relationship between baseline and delta QoL (between baseline and 3-month follow-up) and survival was assessed using the scales/items from the 3 questionnaires. Secondary analyses addressed the relationship between QoL and survival for patients undergoing pancreatic resection and those not undergoing pancreatic resection (with or without metastases).

Statistical Analysis

Descriptive statistics were used to analyze baseline, tumor, and treatment characteristics and QoL scores. These data were reported as proportions for binary or categorical variables, and as mean (SD) or as median with interquartile range (IQR) for continuous variables as appropriate. Missing data from clinical variables (0.9%–13.7%) were imputed by multiple imputation using predictive mean matching in which 20 dummy sets were created. Primary and secondary analyses were performed with baseline and delta QoL (3-month follow-up minus baseline) scores. Survival analyses were performed using Cox regression models. QoL variables with P<.20 in univariable analysis were selected for inclusion in multivariable analysis with backward stepwise selection and reported as hazard ratios (HRs) with corresponding 95% confidence intervals. Analyses were adjusted for patient, tumor, and treatment characteristics and other known predictors for survival. Delta analyses were additionally adjusted for baseline scores. The covariates are presented in the footnotes of the tables. The prognostic value of baseline QoL predictors was assessed using Nagelkerke R2 (ie, explained variance) in univariable analysis, multivariable analysis with adjustment for clinical variables (ie, sex, age, body mass index, ECOG performance status, tumor topography, tumor stage, and type of chemotherapy), and multivariable analysis with adjustment clinical variables and other predictive QoL items from the same questionnaire. An increase in explained variance in analyses with adjustment for clinical variables of 5% was considered clinically relevant. These analyses were performed according to the previously described method for estimation of R2 after multiple imputation.22 The survival analyses were repeated for the resected and nonresected subgroups. Two-sided P<.05 were considered statistically significant after adjustment for multiple testing using the Benjamini-Hochberg procedure.

Results

Population

For baseline analyses, 376 patients were included. After exclusion of 143 patient who completed the baseline questionnaire after treatment initiation, 233 patients remained. Similarly, for delta analyses, 256 patients were included, and after exclusion of 108 patients, 148 patients remained. Overall response rate to the questionnaires during the study period was 60%. Most patients were diagnosed with pancreatic adenocarcinoma (n=194; 83.3%) and had stage III (n=77; 33.0%) or IV (n=61; 26.2%) disease. Overall, 141 patients (60.5%) received chemotherapy. Of all patients, 103 (44.2%) underwent a pancreatic resection and 130 (55.8%) did not. During the study period, 159 patients (68.2%) of the cohort died. Median follow-up of patients was 13.1 months (IQR 7.4–17.5). Median overall survival was 13.6 months (95% CI, 11.6–15.6) for the total cohort, 20.7 months (95% CI, 14.9–26.5) for patients after resection, and 9.3 months (95% CI, 7.7–11.2) for patients without resection. Table 1 provides an overview of patient, tumor, and treatment characteristics. Most QoL scores changed over time; Table 2 provides QoL scores for all items and Figure 1 presents a radar chart of the EORTC QLQ-C30 and QLQ-PAN26 scores.

Table 1.

Patient Characteristics

Table 1.
Table 2.

Median Quality of Life Scores

Table 2.
Figure 1.
Figure 1.

Baseline and 3-month QoL scores for the total cohort based on the (A, B) EORTC QLQ-C30 ([A] summary and functioning scoresa; [B] symptom scoresb) and (C) EORTC-PAN26 (symptom scoresb) questionnaire items.

Abbreviations: QLQ-C30, Quality of Life Questionnaire-Core 30; QLQ-PAN26, Quality of Life Questionnaire, pancreatic cancer module 26; QoL, quality of life.

aHigher scores represent better QoL.

bHigher scores represent worse QoL.

Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 10; 10.6004/jnccn.2020.7579

Baseline QoL and Survival

For the total cohort, independent baseline QoL predictors based on multivariable analyses for reduced survival were overall happiness today (HR per step on 0–10 scale, 0.92; 95% CI, 0.84–0.92; P=.035), role functioning (HR per step on 0–100 scale, 0.99; 95% CI, 0.99–1.00; P=.007), diarrhea (HR per step on 0–100 scale, 1.01; 95% CI, 1.00–1.01; P=.018), pancreatic pain (HR per step on 0–100 scale, 1.01; 95% CI, 1.00–1.02; P=.009), and body image (HR per step on 0–100 scale, 1.01; 95% CI, 1.00–1.01; P=.035) (Table 3).

Table 3.

Univariable and Multivariable Analysis of Relationship Between Baseline QoL Scores and Overall Mortality

Table 3.

For patients who had undergone resection, no independent baseline QoL score predicted survival (supplemental eTable 1; available with this article at JNCCN.org).

For patients without resection, lower overall satisfaction with life, lower physical and cognitive functioning, and higher QLQ-C30 summary, fatigue, (pancreatic) pain, constipation, diarrhea, and body image scores were independent predictors for reduced survival in multivariable analysis (Table 4).

Table 4.

Univariable and Multivariable Analysis of Relationship Between Baseline QoL Scores and Overall Mortality of Patients Without Resection

Table 4.

Delta QoL and Survival

For the total cohort in multivariable analysis, the only independent predictor for reduced survival was more constipation at 3 months compared with baseline (HR per step on 0–100 scale, 1.02; 95% CI, 1.01–1.03; P=.006; supplemental eTable 2). For patients with or without resection, no independent delta QoL score predicted survival (supplemental eTables 3 and 4).

The small HRs from baseline and delta multivariable analyses from the EORTC QLQ-C30 and QLQ-PAN26 scales (eg, HR, 1.02) represent the risk of mortality per 1 point change in score on a 0–100 scale (eg, from 66–67). This HR of 1.02 corresponds to a HR of 1.22 per 10 points change in score (eg, from 66–76; HR, 1.02^10=1.22).

Explained Variance Baseline Without Resection

Together, the clinical variables (ie, sex, age, body mass index, ECOG, tumor topography, tumor stage, and type of chemotherapy) in this subgroup model explained 20% of the outcome variance (blue bars, Figure 2). Figure 2 shows what percentage of the outcome is explained additionally by the various independent QoL predictors individually (orange bars). When for example the item physical functioning was added, 32% of variance of the outcome was explained (12% increase by adding this to the model; blue plus orange bar for physical functioning). All baseline QoL items except diarrhea accounted for >5% of the additional explained variance and were therefore considered to be of additional prognostic value. A similar effect was seen after adding the other QoL items from the same questionnaire to the model (gray bars, Figure 2).

Figure 2.
Figure 2.

Additional prognostic value of independent baseline QoL predictors for overall mortality of patients without resection for pancreatic and periampullary adenocarcinoma expressed as Nagelkerke R2. Blue bars: clinical variables include sex, age, body mass index, ECOG performance status, tumor topography, tumor stage, and type of chemotherapy. Orange bars: additional explained variance of the QoL item. Gray bars: additional explained variance of the other QoL items from the same questionnaire.

Abbreviations: QLQ-C30, Quality of Life Questionnaire-Core 30; QLQ-PAN26, Quality of Life Questionnaire, pancreatic cancer module 26; QoL, quality of life.

aItem one (ie, satisfaction with one’s life as a whole) from the Happiness questionnaire. In gray, not adjusted for other QoL items from the Happiness questionnaire.

bFrom the EORTC QLQ-C30 questionnaire. In gray, adjusted for the other predictive QoL items from the EORTC QLQ-C30 questionnaire (ie, summary score, physical functioning, cognitive functioning, fatigue, pain, constipation, diarrhea).

cFrom the EORTC QLQ-PAN26 questionnaire. In gray, adjusted for the other predictive QoL items from the EORTC QLQ-PAN26 questionnaire (ie, pancreatic pain, body image).

Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 10; 10.6004/jnccn.2020.7579

Discussion

This multicenter study including patients with pancreatic and periampullary cancer in daily clinical practice showed that several QoL domains measured at baseline and follow-up predict survival, even when adjusting for well-known clinical prognostic parameters such as ECOG performance status.15 Because QoL questionnaires measure patients’ perspective on their functioning and symptoms, they may provide a more sensitive and comprehensive picture of patients’ health status that may be missed by traditional clinical measures (eg, tumor stage or performance status).6,23

We found lower happiness, a worse body image, and a lower summary score to predict reduced survival of patients with pancreatic and periampullary cancer. With the Happiness questionnaire, happiness is measured as life satisfaction, hedonic level of affect, and contentment.16 Taking this into account, the happiness items could cover more QoL aspects than for example the global health status item only, and therefore come forth as predictor, whereas global health status does not. Previous studies found that satisfaction with life among patients with cancer is correlated with clinical (eg, times of admission, surgical treatment, postoperative complications, length of hospital stay), psychosocial (eg, depressive symptoms, stress, social support, self-esteem), and sociodemographic (eg, marital status, occupation) factors.2426 Several of these factors have been associated with survival, such as postoperative complications, depressive symptoms, and marital status.2729 This could also be a reason why life satisfaction or happiness is associated with survival in our population. In addition, it was suggested that socioeconomic status (eg, marital status, occupation) of patients with cancer is a survival predictor.23 Unfortunately, because socioeconomic status is not registered accurately in the NCR, we could not investigate this in more detail.

Body image is often negatively influenced in patients with cancer by physical changes caused by the disease or treatment, such as after surgery for breast or colorectal cancer (eg, mastectomy, colostomy).30,31 Specifically for patients with pancreatic and periampullary cancer, body image may be affected by the occurrence of cachexia.32 The incidence of cachexia in patients with pancreatic cancer is high, cachexia-related complications occur often, and cachexia has been associated with reduced survival.3335 Apart from obstructive jaundice, which often is the presenting symptom among patients with pancreatic and periampullary cancer, other mechanisms leading to cachexia are still not completely clear and evaluation of this multifactorial syndrome is not straightforward.35 For this reason, this easy-to-measure QoL item—body image— could be representative of cachexia, which is an important prognostic factor for patients with cancer, especially in combination with other factors of cachexia (eg, weight loss, anorexia).

The summary score combines 13 of the 15 EORTC QLQ-C30 scales and was among other things developed to reduce the risk of type I errors caused by multiple testing. The score was found to have equal or superior known-groups validity and responsiveness to change over time compared with the separate scales.21 Although many of these individual scales were shown to have predictive value in other cancers,7,23,36,37 this was not yet the case for patients with pancreatic and periampullary cancer, nor for the relatively new summary score. This score uses the information of the individual scales, while maintaining a broad QoL scope. In addition, it is measured with a widely implemented and validated questionnaire. Therefore, through comparison of data from other pancreatic or periampullary cancer populations, it can be investigated whether this item is not only efficient (ie, single vs multiple testing) but also effective for measuring a predictive relation to survival (ie, robust single higher order factor model).21

We found that baseline QoL scores were specifically predictive of survival for the subgroup of patients who did not undergo pancreatic resection. In contrast, baseline scores were not predictors of mortality in the resected subgroup. This might be because of the longer survival times after resection and thus other factors that may come into play in the course time that could also influence survival. In other patient groups, for example patients with colorectal cancer, baseline QoL has been associated with survival after resection.38 However, the disease course in patients with pancreatic cancer is fairly different from that of other cancer types, for instance regarding morbidities, treatment, disease recurrence, and survival. Of the baseline symptoms that we found to be predictive of survival among patients who did not undergo a resection, diarrhea as a symptom deserves special attention. Diarrhea can be treatment-related or a symptom of exocrine pancreatic insufficiency, which occurs in up to 92% in patients with unresectable pancreatic or periampullary tumors within 6 months from diagnosis.39 Unfortunately, often only a small proportion of patients in the palliative setting receive pancreatic enzyme replacement therapy.40 Recent studies have suggested that this therapy may independently improve survival.41 Therefore, this is an important and potentially modifiable risk factor that can be identified through PROMs.

For delta QoL, we found that constipation was predictive of mortality for the total cohort. Some studies, for example those in patients with lung and esophageal cancer, have shown that deterioration of QoL scores was predictive of shorter survival times,37,42 whereas delta scores for patients with head and neck cancer were not related to survival.43 It may be hypothesized that the patients with more constipation were those with progressive disease and more pain, and therefore received more opioids, leading to obstipation. Unfortunately, due to a limited number of events in the subgroups of our dataset, we could not test this hypothesis and could only adjust for a limited number of confounding factors.

Our results have important implications for daily practice and research. In the explained variance analysis (Nagelkerke R2), we found that the QoL items were of additional prognostic value on top of the clinical variables. Given the prognostic value of QoL parameters, these parameters may be used during shared decision-making regarding disease management and treatment in the (outpatient) clinic. Ideally, patients should complete questionnaires before meeting their clinician so that QoL can be discussed during the subsequent appointment. The summary score could easily be used for evaluation of overall QoL, because it is one seemingly valid score compared with the 15 individual scale scores. When specific symptoms are present, such as diarrhea, these could be addressed immediately. Predictive QoL parameters may be added to prediction models for survival,44,45 in addition to patient, tumor, and treatment characteristics, to improve their predictive outcome. Finally, QoL parameters may be considered as a stratification factor in clinical trials and should be included in the core set of mandatory baseline measurements.15,20

Some limitations of our study should be considered. First, median overall survival of our cohort is relatively high compared with other population-based studies.4648 Although the NCR covers all patients with cancer in the Netherlands, selection bias has probably occurred in the PROMs registry. Almost half of this study population underwent resection, whereas usually this is approximately 20% in the Netherlands.47 Second, almost 60% of patients without surgery received chemotherapy, whereas this is approximately 30% in an unselected subgroup.47 Presumably, fit patients are more willing to participate in QoL questionnaire studies, or clinicians are more likely to include fit patients. Third, approximately 40% of patients were excluded because baseline questionnaires were not completed before treatment initiation. Fourth, although the association model remained stable, due to limitations in the sample size, multiple testing and some statistical uncertainty were introduced. To reduce this, the Benjamini-Hochberg procedure was used. Fifth, adjustment for chemotherapy duration or change of treatment was not feasible in delta subgroup analyses, because the number of patients and nonevents (ie, nondeath) decreased in the subgroups compared with the total cohort. Future studies with a larger sample size are needed to investigate this newly found relationship between QoL and survival more clearly.

Conclusions

In daily clinical practice for patients with pancreatic and periampullary carcinoma, QoL is related to survival regardless of patient, tumor, and treatment characteristics. Overall happiness (Happiness), summary score (EORTC QLQ-C30), and several functioning and symptom scale item scores (EORTC QLQ-C30 and QLQ-PAN26) were predictive of survival. Baseline QoL scores were of prognostic value for patients without resection, whereas delta QoL scores were predictive for the total cohort. Given their additional prognostic value, PROMs may be used for different reasons in the clinical setting (ie, shared decision-making, disease management/treatment, clinical prediction models, or stratification in trials).

Acknowledgments

The authors thank the registration team of the Netherlands Cancer Registry for their dedicated data collection, and Mariska Prins and Joyce Pijpers for the coordination of the Patient Reported Outcome Measure registry.

References

  • 1.

    Carrato A, Falcone A, Ducreux M, . A systematic review of the burden of pancreatic cancer in Europe: real-world impact on survival, quality of life and costs. J Gastrointest Cancer 2015;46:201211.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    van Dijk SM, Heerkens HD, Tseng DSJ, . Systematic review on the impact of pancreatoduodenectomy on quality of life in patients with pancreatic cancer. HPB (Oxford) 2018;20:204215.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Heerkens HD, Tseng DS, Lips IM, . Health-related quality of life after pancreatic resection for malignancy. Br J Surg 2016;103:257266.

  • 4.

    Carter R, Stocken DD, Ghaneh P, . Longitudinal quality of life data can provide insights on the impact of adjuvant treatment for pancreatic cancer—subset analysis of the ESPAC-1 data. Int J Cancer 2009;124:29602965.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Conroy T, Desseigne F, Ychou M, . FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med 2011;364:18171825.

  • 6.

    Gotay CC, Kawamoto CT, Bottomley A, . The prognostic significance of patient-reported outcomes in cancer clinical trials. J Clin Oncol 2008;26:13551363.

  • 7.

    Ediebah DE, Quinten C, Coens C, . Quality of life as a prognostic indicator of survival: a pooled analysis of individual patient data from Canadian cancer trials group clinical trials. Cancer 2018;124:34093416.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Pinheiro LC, Reeve BB. Investigating the prognostic ability of health-related quality of life on survival: a prospective cohort study of adults with lung cancer. Support Care Cancer 2018;26:39253932.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Quinten C, Coens C, Mauer M, . Baseline quality of life as a prognostic indicator of survival: a meta-analysis of individual patient data from EORTC clinical trials. Lancet Oncol 2009;10:865871.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Quinten C, Maringwa J, Gotay CC, . Patient self-reports of symptoms and clinician ratings as predictors of overall cancer survival. J Natl Cancer Inst 2011;103:18511858.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Sternby Eilard M, Hagstrom H, Mortensen KE, . Quality of life as a prognostic factor for survival in hepatocellular carcinoma. Liver Int 2018;38:885894.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Gupta D, Lis CG, Grutsch JF. The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire: implications for prognosis in pancreatic cancer. Int J Gastrointest Cancer 2006;37:6573.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Coebergh van den Braak RRJ, van Rijssen LB, van Kleef JJ, . Nationwide comprehensive gastro-intestinal cancer cohorts: the 3P initiative. Acta Oncol 2018;57:195202.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    von Elm E, Altman DG, Egger M, . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg 2014;12:14951499.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    ter Veer E, van Rijssen LB, Besselink MG, . Consensus Statement on Mandatory Measurements in Pancreatic Cancer Trials (COMM-PACT) for systemic treatment of unresectable disease. Lancet Oncol 2018;19:e151e160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Veenhoven R. How do we assess how happy we are? Tenets, implications and tenability of three theories. In: Dutt AK, Radcliff B, eds.Happiness, Economics and Politics: Toward a Multi-Disciplinary Approach. Cheltenham, UK: Edward Elger Publishers; 2009:45– 69.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Aaronson NK, Ahmedzai S, Bergman B, . The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993;85:365376.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Fitzsimmons D, Johnson CD, George S, . Development of a disease specific quality of life (QoL) questionnaire module to supplement the EORTC core cancer QoL questionnaire, the QLQ-C30 in patients with pancreatic cancer. EORTC Study Group on Quality of Life. Eur J Cancer 1999;35:939– 941.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Gerritsen A, Jacobs M, Henselmans I, . Developing a core set of patient-reported outcomes in pancreatic cancer: a Delphi survey. Eur J Cancer 2016;57:6877.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    van Rijssen LB, Gerritsen A, Henselmans I, . Core set of patient-reported outcomes in pancreatic cancer (COPRAC): an international Delphi study among patients and health care providers. Ann Surg 2019;270:158164.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Giesinger JM, Kieffer JM, Fayers PM, . Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. J Clin Epidemiol 2016;69:7988.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Harel O. The estimation of R2 and adjusted R2 in incomplete data sets using multiple imputation. J Appl Stat 2009;36:11091118.

  • 23.

    Montazeri A. Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008. Health Qual Life Outcomes 2009;7:102.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Cobo-Cuenca AI, Martín-Espinosa NM, Rodríguez-Borrego MA, . Determinants of satisfaction with life and self-esteem in women with breast cancer. Qual Life Res 2019;28:379387.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Hamdan-Mansour AM, Al Abeiat DD, Alzoghaibi IN, . Psychosocial and sociodemographic correlates of life satisfaction among patients diagnosed with cancer in Jordan. J Cancer Educ 2015;30:3136.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Romain B, Rohmer O, Schimchowitsch S, . Influence of preoperative life satisfaction on recovery and outcomes after colorectal cancer surgery—a prospective pilot study. Health Qual Life Outcomes 2018;16:16.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Nathan H, Yin H, Wong SL. Postoperative complications and long-term survival after complex cancer resection. Ann Surg Oncol 2017;24:638644.

  • 28.

    Massie MJ. Prevalence of depression in patients with cancer. J Natl Cancer Inst Monogr 2004;32:5771.

  • 29.

    Wang XD, Qian JJ, Bai DS, . Marital status independently predicts pancreatic cancer survival in patients treated with surgical resection: an analysis of the SEER database. Oncotarget 2016;7:2488024887.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Ayaz-Alkaya S. Overview of psychosocial problems in individuals with stoma: review of literature. Int Wound J 2019;16:243249.

  • 31.

    Miaja M, Platas A, Martinez-Cannon BA. Psychological impact of alterations in sexuality, fertility, and body image in young breast cancer patients and their partners. Rev Invest Clin 2017;69:204209.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Dengsø KE, Tjørnhøj-Thomsen T, Dalton SO, . Gut disruption impairs rehabilitation in patients curatively operated for pancreaticoduodenal cancer—a qualitative study. BMC Cancer 2018;18:1017.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Hou YC, Wang CJ, Chao YJ, . Elevated serum interleukin-8 level correlates with cancer-related cachexia and sarcopenia: an indicator for pancreatic cancer outcomes. J Clin Med 2018;7:502.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Mueller TC, Burmeister MA, Bachmann J, . Cachexia and pancreatic cancer: are there treatment options? World J Gastroenterol 2014;20:93619373.

  • 35.

    Tan CR, Yaffee PM, Jamil LH, . Pancreatic cancer cachexia: a review of mechanisms and therapeutics. Front Physiol 2014;5:88.

  • 36.

    Robinson DW Jr, Eisenberg DF, Cella D, . The prognostic significance of patient-reported outcomes in pancreatic cancer cachexia. J Support Oncol 2008;6:283290.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Blazeby JM, Brookes ST, Alderson D. The prognostic value of quality of life scores during treatment for oesophageal cancer. Gut 2001;49:227230.

  • 38.

    Sharma A, Walker LG, Monson JR. Baseline quality of life factors predict long term survival after elective resection for colorectal cancer. Int J Surg Oncol 2013;2013:269510.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Sikkens EC, Cahen DL, de Wit J, . A prospective assessment of the natural course of the exocrine pancreatic function in patients with a pancreatic head tumor. J Clin Gastroenterol 2014;48:e43e46.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Landers A, Muircroft W, Brown H. Pancreatic enzyme replacement therapy (PERT) for malabsorption in patients with metastatic pancreatic cancer. BMJ Support Palliat Care 2016;6:7579.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Domínguez-Muñoz JE, Nieto-Garcia L, López-Díaz J, . Impact of the treatment of pancreatic exocrine insufficiency on survival of patients with unresectable pancreatic cancer: a retrospective analysis. BMC Cancer 2018;18:534.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Eton DT, Fairclough DL, Cella D, . Early change in patient-reported health during lung cancer chemotherapy predicts clinical outcomes beyond those predicted by baseline report: results from Eastern Cooperative Oncology Group Study 5592. J Clin Oncol 2003;21:15361543.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43.

    Fang FM, Liu YT, Tang Y, . Quality of life as a survival predictor for patients with advanced head and neck carcinoma treated with radiotherapy. Cancer 2004;100:425432.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    van den Boorn HG, Engelhardt EG, van Kleef J, . Prediction models for patients with esophageal or gastric cancer: a systematic review and meta-analysis. PLoS One 2018;13:e0192310.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 45.

    DuMontier C, Clough-Gorr KM, Silliman RA, . Health-related quality of life in a predictive model for mortality in older breast cancer survivors. J Am Geriatr Soc 2018;66:11151122.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 46.

    van der Geest LGM, Lemmens VEPP, de Hingh IHJT, . Nationwide outcomes in patients undergoing surgical exploration without resection for pancreatic cancer. Br J Surg 2017;104:15681577.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 47.

    van Erning FN, Mackay TM, van der Geest LGM, . Association of the location of pancreatic ductal adenocarcinoma (head, body, tail) with tumor stage, treatment, and survival: a population-based analysis. Acta Oncol 2018;57:16551662.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 48.

    Zijlstra M, van der Geest LGM, van Laarhoven HWM, . Patient characteristics and treatment considerations in pancreatic cancer: a population based study in the Netherlands. Acta Oncol 2018;57:11851191.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

Submitted January 29, 2020; accepted for publication April 21, 2020.

Author contributions: Study concept or design: Mackay, Latenstein, van der Geest, Besselink, van Laarhoven. Data acquisition or analysis: Mackay, Latenstein, van der Geest, Besselink, van Laarhoven. Data interpretation: All authors. Manuscript preparation or critical revision: All authors.

Disclosures: The authors have disclosed that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: This work was supported by funding from KWF Kankerbestrijding (UVA2013-5842).

Correspondence: Hanneke W.M. van Laarhoven, MD, PhD, Department of Medical Oncology, D3-312, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands. Email: h.vanlaarhoven@amsterdamumc.nl

Supplementary Materials

  • View in gallery

    Baseline and 3-month QoL scores for the total cohort based on the (A, B) EORTC QLQ-C30 ([A] summary and functioning scoresa; [B] symptom scoresb) and (C) EORTC-PAN26 (symptom scoresb) questionnaire items.

    Abbreviations: QLQ-C30, Quality of Life Questionnaire-Core 30; QLQ-PAN26, Quality of Life Questionnaire, pancreatic cancer module 26; QoL, quality of life.

    aHigher scores represent better QoL.

    bHigher scores represent worse QoL.

  • View in gallery

    Additional prognostic value of independent baseline QoL predictors for overall mortality of patients without resection for pancreatic and periampullary adenocarcinoma expressed as Nagelkerke R2. Blue bars: clinical variables include sex, age, body mass index, ECOG performance status, tumor topography, tumor stage, and type of chemotherapy. Orange bars: additional explained variance of the QoL item. Gray bars: additional explained variance of the other QoL items from the same questionnaire.

    Abbreviations: QLQ-C30, Quality of Life Questionnaire-Core 30; QLQ-PAN26, Quality of Life Questionnaire, pancreatic cancer module 26; QoL, quality of life.

    aItem one (ie, satisfaction with one’s life as a whole) from the Happiness questionnaire. In gray, not adjusted for other QoL items from the Happiness questionnaire.

    bFrom the EORTC QLQ-C30 questionnaire. In gray, adjusted for the other predictive QoL items from the EORTC QLQ-C30 questionnaire (ie, summary score, physical functioning, cognitive functioning, fatigue, pain, constipation, diarrhea).

    cFrom the EORTC QLQ-PAN26 questionnaire. In gray, adjusted for the other predictive QoL items from the EORTC QLQ-PAN26 questionnaire (ie, pancreatic pain, body image).

  • 1.

    Carrato A, Falcone A, Ducreux M, . A systematic review of the burden of pancreatic cancer in Europe: real-world impact on survival, quality of life and costs. J Gastrointest Cancer 2015;46:201211.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    van Dijk SM, Heerkens HD, Tseng DSJ, . Systematic review on the impact of pancreatoduodenectomy on quality of life in patients with pancreatic cancer. HPB (Oxford) 2018;20:204215.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Heerkens HD, Tseng DS, Lips IM, . Health-related quality of life after pancreatic resection for malignancy. Br J Surg 2016;103:257266.

  • 4.

    Carter R, Stocken DD, Ghaneh P, . Longitudinal quality of life data can provide insights on the impact of adjuvant treatment for pancreatic cancer—subset analysis of the ESPAC-1 data. Int J Cancer 2009;124:29602965.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Conroy T, Desseigne F, Ychou M, . FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med 2011;364:18171825.

  • 6.

    Gotay CC, Kawamoto CT, Bottomley A, . The prognostic significance of patient-reported outcomes in cancer clinical trials. J Clin Oncol 2008;26:13551363.

  • 7.

    Ediebah DE, Quinten C, Coens C, . Quality of life as a prognostic indicator of survival: a pooled analysis of individual patient data from Canadian cancer trials group clinical trials. Cancer 2018;124:34093416.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Pinheiro LC, Reeve BB. Investigating the prognostic ability of health-related quality of life on survival: a prospective cohort study of adults with lung cancer. Support Care Cancer 2018;26:39253932.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Quinten C, Coens C, Mauer M, . Baseline quality of life as a prognostic indicator of survival: a meta-analysis of individual patient data from EORTC clinical trials. Lancet Oncol 2009;10:865871.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Quinten C, Maringwa J, Gotay CC, . Patient self-reports of symptoms and clinician ratings as predictors of overall cancer survival. J Natl Cancer Inst 2011;103:18511858.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Sternby Eilard M, Hagstrom H, Mortensen KE, . Quality of life as a prognostic factor for survival in hepatocellular carcinoma. Liver Int 2018;38:885894.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Gupta D, Lis CG, Grutsch JF. The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire: implications for prognosis in pancreatic cancer. Int J Gastrointest Cancer 2006;37:6573.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Coebergh van den Braak RRJ, van Rijssen LB, van Kleef JJ, . Nationwide comprehensive gastro-intestinal cancer cohorts: the 3P initiative. Acta Oncol 2018;57:195202.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    von Elm E, Altman DG, Egger M, . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg 2014;12:14951499.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    ter Veer E, van Rijssen LB, Besselink MG, . Consensus Statement on Mandatory Measurements in Pancreatic Cancer Trials (COMM-PACT) for systemic treatment of unresectable disease. Lancet Oncol 2018;19:e151e160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Veenhoven R. How do we assess how happy we are? Tenets, implications and tenability of three theories. In: Dutt AK, Radcliff B, eds.Happiness, Economics and Politics: Toward a Multi-Disciplinary Approach. Cheltenham, UK: Edward Elger Publishers; 2009:45– 69.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Aaronson NK, Ahmedzai S, Bergman B, . The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993;85:365376.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Fitzsimmons D, Johnson CD, George S, . Development of a disease specific quality of life (QoL) questionnaire module to supplement the EORTC core cancer QoL questionnaire, the QLQ-C30 in patients with pancreatic cancer. EORTC Study Group on Quality of Life. Eur J Cancer 1999;35:939– 941.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Gerritsen A, Jacobs M, Henselmans I, . Developing a core set of patient-reported outcomes in pancreatic cancer: a Delphi survey. Eur J Cancer 2016;57:6877.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    van Rijssen LB, Gerritsen A, Henselmans I, . Core set of patient-reported outcomes in pancreatic cancer (COPRAC): an international Delphi study among patients and health care providers. Ann Surg 2019;270:158164.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Giesinger JM, Kieffer JM, Fayers PM, . Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. J Clin Epidemiol 2016;69:7988.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Harel O. The estimation of R2 and adjusted R2 in incomplete data sets using multiple imputation. J Appl Stat 2009;36:11091118.

  • 23.

    Montazeri A. Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008. Health Qual Life Outcomes 2009;7:102.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Cobo-Cuenca AI, Martín-Espinosa NM, Rodríguez-Borrego MA, . Determinants of satisfaction with life and self-esteem in women with breast cancer. Qual Life Res 2019;28:379387.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Hamdan-Mansour AM, Al Abeiat DD, Alzoghaibi IN, . Psychosocial and sociodemographic correlates of life satisfaction among patients diagnosed with cancer in Jordan. J Cancer Educ 2015;30:3136.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Romain B, Rohmer O, Schimchowitsch S, . Influence of preoperative life satisfaction on recovery and outcomes after colorectal cancer surgery—a prospective pilot study. Health Qual Life Outcomes 2018;16:16.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Nathan H, Yin H, Wong SL. Postoperative complications and long-term survival after complex cancer resection. Ann Surg Oncol 2017;24:638644.

  • 28.

    Massie MJ. Prevalence of depression in patients with cancer. J Natl Cancer Inst Monogr 2004;32:5771.

  • 29.

    Wang XD, Qian JJ, Bai DS, . Marital status independently predicts pancreatic cancer survival in patients treated with surgical resection: an analysis of the SEER database. Oncotarget 2016;7:2488024887.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Ayaz-Alkaya S. Overview of psychosocial problems in individuals with stoma: review of literature. Int Wound J 2019;16:243249.

  • 31.

    Miaja M, Platas A, Martinez-Cannon BA. Psychological impact of alterations in sexuality, fertility, and body image in young breast cancer patients and their partners. Rev Invest Clin 2017;69:204209.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Dengsø KE, Tjørnhøj-Thomsen T, Dalton SO, . Gut disruption impairs rehabilitation in patients curatively operated for pancreaticoduodenal cancer—a qualitative study. BMC Cancer 2018;18:1017.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Hou YC, Wang CJ, Chao YJ, . Elevated serum interleukin-8 level correlates with cancer-related cachexia and sarcopenia: an indicator for pancreatic cancer outcomes. J Clin Med 2018;7:502.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Mueller TC, Burmeister MA, Bachmann J, . Cachexia and pancreatic cancer: are there treatment options? World J Gastroenterol 2014;20:93619373.

  • 35.

    Tan CR, Yaffee PM, Jamil LH, . Pancreatic cancer cachexia: a review of mechanisms and therapeutics. Front Physiol 2014;5:88.

  • 36.

    Robinson DW Jr, Eisenberg DF, Cella D, . The prognostic significance of patient-reported outcomes in pancreatic cancer cachexia. J Support Oncol 2008;6:283290.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Blazeby JM, Brookes ST, Alderson D. The prognostic value of quality of life scores during treatment for oesophageal cancer. Gut 2001;49:227230.

  • 38.

    Sharma A, Walker LG, Monson JR. Baseline quality of life factors predict long term survival after elective resection for colorectal cancer. Int J Surg Oncol 2013;2013:269510.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Sikkens EC, Cahen DL, de Wit J, . A prospective assessment of the natural course of the exocrine pancreatic function in patients with a pancreatic head tumor. J Clin Gastroenterol 2014;48:e43e46.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Landers A, Muircroft W, Brown H. Pancreatic enzyme replacement therapy (PERT) for malabsorption in patients with metastatic pancreatic cancer. BMJ Support Palliat Care 2016;6:7579.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Domínguez-Muñoz JE, Nieto-Garcia L, López-Díaz J, . Impact of the treatment of pancreatic exocrine insufficiency on survival of patients with unresectable pancreatic cancer: a retrospective analysis. BMC Cancer 2018;18:534.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Eton DT, Fairclough DL, Cella D, . Early change in patient-reported health during lung cancer chemotherapy predicts clinical outcomes beyond those predicted by baseline report: results from Eastern Cooperative Oncology Group Study 5592. J Clin Oncol 2003;21:15361543.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43.

    Fang FM, Liu YT, Tang Y, . Quality of life as a survival predictor for patients with advanced head and neck carcinoma treated with radiotherapy. Cancer 2004;100:425432.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    van den Boorn HG, Engelhardt EG, van Kleef J, . Prediction models for patients with esophageal or gastric cancer: a systematic review and meta-analysis. PLoS One 2018;13:e0192310.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 45.

    DuMontier C, Clough-Gorr KM, Silliman RA, . Health-related quality of life in a predictive model for mortality in older breast cancer survivors. J Am Geriatr Soc 2018;66:11151122.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 46.

    van der Geest LGM, Lemmens VEPP, de Hingh IHJT, . Nationwide outcomes in patients undergoing surgical exploration without resection for pancreatic cancer. Br J Surg 2017;104:15681577.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 47.

    van Erning FN, Mackay TM, van der Geest LGM, . Association of the location of pancreatic ductal adenocarcinoma (head, body, tail) with tumor stage, treatment, and survival: a population-based analysis. Acta Oncol 2018;57:16551662.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 48.

    Zijlstra M, van der Geest LGM, van Laarhoven HWM, . Patient characteristics and treatment considerations in pancreatic cancer: a population based study in the Netherlands. Acta Oncol 2018;57:11851191.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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