The conditional survival statistics for survivors with primary supratentorial astrocytic tumors

Nomogram of conditional survival probability of long-term Survival for Metastatic Colorectal Cancer: A Real-World Data Retrospective Cohort Study from SEER database

BACKGROUND

Many patients with metastatic colorectal cancer (mCRC) have better prognosis than the prediction at diagnosis. Compared with invariable traditional Kaplan Meier assessment, conditional survival (CS) assessment has become a more accurate and informative assessment method to predict survival time.

MATERIALS AND METHODS

Patients with mCRC between 2010 and 2015 were extracted from Surveillance, Epidemiology and End Results linked database. CS analysis was applied to depict exact survival for patients who have survived for specific year and standardized difference (d) was used to evaluate the differences between subgroups in CS analysis. Based on variables selected by Lasso analysis, nomograms for each year after diagnosis were fitted to estimate 3-year survival of stage IV CRC, respectively.

RESULTS

Of 9732 patients, overall actuarial survival (OS) decreased from 24% at 4-year to 16% at 6-year, while corresponding 3-year CS (CS3) increased from 33% at 1-year to 48% at 3-year. Overall, CS3 was higher than corresponding actuarial survival. All clinicopathological characteristics were associated with actuarial survival (p < 0.05). However, in CS3 analysis, survival difference caused by gender, race and tumor size gradually disappeared over time (|d|>0.1→ |d|<0.1). Furthermore, survival difference caused by histological type, brain metastasis and chemotherapy reversed over time (d > 0→d<0 or d<0→d>0). Based on lasso analysis, nomograms for 1st, 2nd and 3rd year after diagnosis were conducted respectively. The AUC of nomogram for 1st year was 0.705, for 2nd year was 0.675, and for 3rd year was 0.648.

CONCLUSION

Patients with mCRC demonstrated a substantial increase in CS over time. Risk factors collected at diagnosis may change gradually. Nomograms constructed by survival time can predict more accurate survival for patients with mCRC. Conditional survival assessments provide important quantitative information about the probability of survival and are therefore of great value to patients and health care professionals.

Identifying metrics of success for transitional care practices in childhood cancer survivorship: a qualitative interview study of survivors

BACKGROUND

Adolescent and young adult (AYA) childhood cancer survivors (CCS) should be empowered to continue their survivor-focused care as they transition into adult medicine. However, the majority of AYA-aged survivors become lost to follow up around the age of typical transition to adulthood. The purpose of this study was to identify, from the patient's perspective, key factors that facilitate successful transitions to adult-centered survivorship care.

METHODS

A qualitative study was conducted with AYA CCS (n = 29) from the survivorship clinic of a single institution as key informants. Data were collected through a series of structured phone interviews and subjected to thematic content analysis.

RESULTS

Four major themes with multiple subthemes were identified: (1) transition practices need to be flexible and individually tailored; (2) effective communication is critical to a successful transition; (3) continuity in providers is needed during the transition; and (4) comprehensive care means care that also addresses psycho-social well-being.

CONCLUSIONS

From the perspective of AYA CCS, the ideal model of transitional survivorship care could include a patient navigator who promotes provider flexibility, consistent communication, and pro-active comprehensive care that encompasses both medical and psycho-social well-being. Models of care for CCS should be built to provide, or seamlessly facilitate, continuous survivor-focused care across the age continuum. A longitudinal relationship with a survivor-focused provider can help promote the values that CCS' report as important in transitioning care from pediatric- to adult-centered care.

Conditional survival after a diagnosis of malignant brain tumour in Canada: 2000-2008

BACKGROUND

"Conditional survival probability" is defined as the probability that a patient will survive an additional time, given that the patient has already survived a defined period of time after diagnosis. Such estimates might be more relevant for clinicians and patients during post-diagnosis care, because survival probability projections are based on the patient's survival to date. Here, we provides the first population-based estimates of conditional survival probabilities by histology for brain cancer in Canada.

METHODS

Canadian Cancer Registry data were accessed for patients diagnosed with primary brain cancers during 2000-2008. Kaplan-Meier survival probabilities were estimated by histology. Conditional survival probabilities at 6 months (short-term, denoted scs) and 2 years (long-term, denoted lcs) were derived from the Kaplan-Meier survival estimates for a range of time periods.

RESULTS

Among the 20,875 patients who met the study criteria, scs increased by a margin of 16-18 percentage points from 6-month survivors to 2-year survivors for the three most aggressive brain cancers. The lcs for 2-year survivors was 66% or greater for all tumour groups except glioblastoma. The lcs for 4-year survivors was 62% or greater for all histologies. For glioblastoma and diffuse astrocytoma, the lcs increased each year after diagnosis. For all other histologies, the lcs first increased and then plateaued from 2 years after diagnosis. The lcs and scs both worsened with increasing older age at diagnosis.

SUMMARY

We report histologically specific conditional survival probabilities that can have value for clinicians practicing in Canada as they plan the course of follow-up for individual patients with brain cancer.

Long-term mortality among women with epithelial ovarian cancer

OBJECTIVES

Patients with solid tumors are at greatest risk for dying from their cancers in the five years following diagnosis. For most malignancies, deaths from other chronic diseases begin to exceed those from cancer at some point. As little is known about the causes of death among long-term survivors of ovarian cancer, we examined causes of death by years from diagnosis.

METHODS

The Surveillance, Epidemiology, and End Results (SEER) database was used to identify women diagnosed with ovarian cancer between 1988 and 2012. We compared causes of death by stage, age, and interval time after diagnosis.

RESULTS

A total of 67,385 women were identified. For stage I neoplasms, 13.6% (CI, 13.0-14.2%) died from ovarian cancer, 4.2% (CI, 3.8-4.5%) from cardiovascular disease, 3.6% (CI, 3.3-3.9%) from other causes and 2.6% (CI, 2.4-2.9%) from other tumors; ovarian cancer was the leading cause of death until 7 years after diagnosis after which time deaths are more frequently due to other causes. For those with stage III-IV tumors, 67.8% (CI, 67.3-68.2%) died from ovarian cancer, 2.8% (CI, 2.6-2.9%) from other causes, 2.3% (CI, 2.2-2.4%) from cardiovascular disease and 1.9% (CI, 1.7-2.0%) from other cancers; ovarian cancer was the most frequent cause of death in years 1-15 after which time deaths were more commonly due to other causes.

CONCLUSIONS

The probability of dying from ovarian cancer decreases with time. Ovarian cancer remains the most common cause of death for 15 years after diagnosis in women with stage III-IV tumors.

Conditional survival in pediatric malignancies: analysis of data from the Childhood Cancer Survivor Study and the Surveillance, Epidemiology, and End Results Program

BACKGROUND

Long-term survivors of pediatric cancer are at risk of life-threatening late effects of their cancer. Previous studies have shown excesses in long-term mortality within high-risk groups defined by demographic and treatment characteristics.

METHODS

To investigate conditional survival in a pediatric cancer population, the authors performed an analysis of conditional survival in the original Childhood Cancer Survivor Study (CCSS) cohort and the Surveillance, Epidemiology, and End Results (SEER) database registry. The overall probability of death for patients at 5 years and 10 years after they survived 5, 10, 15, and 20 years since cancer diagnosis and cause-specific death in 10 years for 5-year survivors were estimated using the cumulative incidence method.

RESULTS

Among patients in the CCSS and SEER cohorts who were alive 5 years after their cancer diagnosis, within each diagnosis group at least 92% were alive in the subsequent 5 years, except for patients with leukemia, of whom only 88% of 5-year survivors remained alive in the subsequent 5 years. The probability of all-cause mortality in the next 10 years among patients who survived at least 5 years after diagnosis was 8.8% in CCSS and 10.6% in SEER, approximately 75% of which was due to neoplasms as the cause of death.

CONCLUSIONS

The risk of death among survivors of pediatric cancer in 10 years can vary between diagnosis groups by at most 12%, even up to 20 years after diagnosis. This information is clinically significant when counseling patients regarding their conditional survival, particularly when survivors are seen in long-term follow-up.

Dynamic prognostication using conditional survival estimates

Measures of prognosis are typically estimated from the time of diagnosis. However, these estimates become less relevant as the time from diagnosis increases for a patient. Conditional survival measures the probability that a cancer patient will survive some additional number of years, given that the patient has already survived for a certain number of years. In the current study, the authors analyzed data regarding patients with stage III melanoma to demonstrate that survival estimates from the time of diagnosis underestimate long-term survival as the patient is followed over time. The probability of surviving to year 5 for patients at the time of presentation compared with patients who had already survived for 4 years increased from 72% to 95%, 48% to 90%, and 29% to 86%, respectively, for patients with substage IIIA, IIIB, and IIIC disease. Considering the major role played by survival estimates during follow-up in patient counseling and the development of survivorship programs, the authors strongly recommend the routine use of conditional survival estimates.

Conditional probability of survival in patients with newly diagnosed glioblastoma

PURPOSE

The disease outcome for patients with cancer is typically described in terms of estimated survival from diagnosis. Conditional probability offers more relevant information regarding survival for patients once they have survived for some time. We report conditional survival probabilities on the basis of 498 patients with glioblastoma multiforme receiving radiation and chemotherapy. For 1-year survivors, we evaluated variables that may inform subsequent survival. Motivated by the trend in data, we also evaluated the assumption of constant hazard.

PATIENTS AND METHODS

Patients enrolled onto seven phase II protocols between 1975 and 2007 were included. Conditional survival probabilities and 95% CIs were calculated. The Cox proportional hazards model was used to evaluate prognostic values of age, Karnofsky performance score (KPS), and prior progression 1-year post diagnosis. To assess the constant hazard assumption, we used a likelihood-ratio test to compare the Weibull and exponential distributions.

RESULTS

The probabilities of surviving an additional year given survival to 1, 2, 3, and 4 years were 35%, 49%, 69%, and 93%, respectively. For patients who survived for 1 year, lower KPS and progression were significantly predictive of shorter survival (both P < .001), but age was not (hazard ratio, 1.22 for a 10-year increase; P = .25). The Weibull distribution fits the data significantly better than exponential (P = .02), suggesting nonconstant hazard.

CONCLUSION

Conditional probabilities provide encouraging information regarding life expectancy to survivors of glioblastoma multiforme. Our data also showed that the constant hazard assumption may be violated in modern brain tumor trials. For single-arm trials, we advise using individual patient data from historical data sets for efficacy comparisons.

Conditional survival of all primary brain tumor patients by age, behavior, and histology

BACKGROUND

Survival statistics commonly reflect survival from the time of diagnosis but do not take into account survival already achieved after a diagnosis. The objective of this study was to provide conditional survival estimates for brain tumor patients as a more accurate measure of survival for those who have already survived for a specified amount of time after diagnosis.

METHODS

Data on primary malignant and nonmalignant brain tumor cases diagnosed from 1985-2005 from selected SEER state cancer registries were obtained. Relative survival up to 15 years postdiagnosis and varying relative conditional survival rates were computed using the life-table method.

RESULTS

The overall 1-year relative survival estimate derived from time of diagnosis was 67.8% compared to the 6-month relative conditional survival rate of 85.7% for 6-month survivors (the probability of surviving to 1 year given survival to 6 months). The 10-year overall relative survival rate was 49.5% from time of diagnosis compared to the 8-year relative conditional survival rate of 79.2% for 2-year survivors. Conditional survival estimates and standard survival estimates varied by histology, behavior, and age at diagnosis. The 5-year relative survival estimate derived from time of diagnosis for glioblastoma was 3.6% compared to the 3-year relative conditional survival rate of 36.4% for 2-year survivors. For most nonmalignant tumors, the difference between relative survival and the corresponding conditional survival estimates were minimal. Older age groups had greater numeric gains in survival but lower conditional survival estimates than other age groups. Similar findings were seen for other conditional survival intervals.

CONCLUSIONS

Conditional survival is a useful disease surveillance measure for clinicians and brain tumor survivors to provide them with better 'real-time' estimates and hope.

An interactive tool for individualized estimation of conditional survival in rectal cancer

BACKGROUND

For rectal cancer patients who have already survived a period of time after diagnosis, survival probability changes and is more accurately depicted by conditional survival. The specific aim of this study was to develop an interactive tool for individualized estimation of changing prognosis for rectal cancer patients.

METHODS

A multivariate Cox proportional hazards (CPH) survival model was constructed using data from rectal cancer patients diagnosed from 1994 to 2003 from the Surveillance, Epidemiology, and End Results (SEER) database. Age, race, sex, and stage were used as covariates in the survival prediction model. The primary outcome variable was overall survival conditional on having survived up to 5 years from diagnosis.

RESULTS

Data from 42,830 rectal cancer patients met the inclusion criteria. The multivariate CPH model showed age, race, sex, and stage as significant independent predictors of survival. The survival prediction model demonstrated good calibration and discrimination, with a bootstrap-corrected concordance index of 0.75. A web-based prediction tool was built from this regression model that can compute individualized estimates of changing prognosis over time.

CONCLUSIONS

An interactive prediction modeling tool can estimate prognosis for rectal cancer patients who have already survived a period of time after diagnosis and treatment. Having more accurate prognostic information can empower both patients and clinicians to be able to make more appropriate decisions regarding follow-up, surveillance testing, and future treatment.

Conditional survival estimates improve over 5 years for melanoma survivors with node-positive disease

BACKGROUND

Conditional survival estimates provide useful prognostic information for cancer survivors. The objective of this study was to determine conditional survival estimates for melanoma patients with substages of stage III disease.

MATERIALS AND METHODS

A retrospective analysis of 760 patients who underwent lymphadenectomy for node-positive melanoma was conducted, and patients were stratified into substages: IIIA, IIIB, and IIIC. The 5-year conditional disease-free survival (DFS) and disease-specific survival (DSS) were calculated following lymphadenectomy using the methods of Kaplan and Meier and were reassessed for survivors on an annual basis. Multivariate Cox regression models were used to calculate adjusted conditional DFS and DSS accounting for age, gender, tumor histology, and extracapsular extension.

RESULTS

For patients with IIIA, IIIB, and IIIC disease, 5-year conditional DSS from treatment to year 5 improved from 78% to 90%, 54% to 79%, and 39% to 78%, respectively. For 5-year conditional DFS over the same period, the estimates increased from 65% to 79%, 37% to 81%, and 26% to 92%, respectively. Male patients experienced decreased 5-year conditional DSS and DFS across all substages, with the most pronounced effect on DSS in stage IIIC. Multivariate analysis demonstrated that survival differences among stage IIIC patients based on histologic subtype and extracapsular extension decreased over time.

CONCLUSIONS

Conditional survival estimates are more optimistic and realistic for cancer survivors than traditional survival estimates over time. For node-positive melanoma survivors, 5-year conditional DFS and DSS improve significantly over time. These estimates are critical to treatment decisions and non-treatment-related planning for both clinicians and patients.

Conditional survival estimates improve over time for patients with advanced melanoma: results from a population-based analysis

BACKGROUND

Conditional survival (CS) has emerged as a clinically relevant measure of prognosis for cancer survivors. The objective of this analysis was to provide melanoma-specific CS estimates to help clinicians promote more informed patient decision making.

METHODS

Patients with melanoma and at least 5 years of follow-up were identified from the Surveillance Epidemiology and End Results registry (1988-2000). By using the methods of Kaplan and Meier, stage-specific, 5-year CS estimates were independently calculated for survivors for each year after diagnosis. Stage-specific multivariate Cox regression models including baseline survivor functions were used to calculate adjusted melanoma-specific CS for different subgroups of patients further stratified by age, gender, race, marital status, anatomic tumor location, and tumor histology.

RESULTS

Five-year CS estimates for patients with stage I disease remained constant at 97% annually, while for patients with stages II, III, and IV disease, 5-year CS estimates from time 0 (diagnosis) to 5 years improved from 72% to 86%, 51% to 87%, and 19% to 84%, respectively. Multivariate CS analysis revealed that differences in stages II through IV CS based on age, gender, and race decreased over time.

CONCLUSIONS

Five-year melanoma-specific CS estimates improve dramatically over time for survivors with advanced stages of disease. These prognostic data are critical to patients for both treatment and nontreatment related life decisions.

Conditional survival and the choice of conditioning set for patients with colon cancer: an analysis of NSABP trials C-03 through C-07

PURPOSE

Colon cancer overall survival (OS) is usually computed from the time of diagnosis. Survival gives the initial prognosis but does not reflect how prognosis changes with changing hazard rates over time. Conditional survival (probability of surviving y additional years given they have survived x years [CS or OS|OS]) is an alternative measure that accounts for elapsed time since diagnosis, providing more relevant prognostic information. We extend the concept of CS to condition on the set of patients alive, recurrence-free, and second primary cancer-free (disease-free survival [OS|DFS]).

PATIENTS AND METHODS

Using data from National Surgical Adjuvant Breast and Bowel Project trials C-03 through C-07, 5-year OS|DFS was calculated on patients who were disease free up to 5 years after diagnosis, stratified by age, stage, nodal status, and performance status (PS).

RESULTS

For stage II, OS|DFS improved from 87% to 92% at 5 years. For stage III, OS|DFS improved from 69% to 88%. Patients younger than 50 years showed OS|DFS improvement from 79% to 95%; those older than 70 years showed no sustained increase in OS|DFS. Node-negative patients with > or = 12 nodes resected showed little change (89% to 94%); those with more than four positive nodes showed an improvement (57% to 86%). Patients with a PS of 0 or 1 demonstrated a small improvement; those with a PS of 2 did not (64% to 58%).

CONCLUSION

Prognosis improves over time for almost all groups of patients with colon cancer, especially those with positive nodes. OS|DFS is a more relevant measure of prognosis for those who have already survived disease free a period of time after diagnosis.

Relative lack of conditional survival improvement in young adults with cancer

Cancer prognosis is usually reported in terms of survival from time of diagnosis. For patients surviving a period of time after diagnosis, conditional survival (CS) accounts for changing risk over time. This report provides information on how CS in cancer patients changes as a function of age at diagnosis. Using data from the US Surveillance, Epidemiology and End Results database, we examined survival for patients diagnosed between 1973 and 2002. The average annual percent change (AAPC) in CS during the first 5 years after diagnosis was evaluated for the 14 most common cancers occurring in young adults, defined as 15- to 39-year-olds, and how they compared with cancers that are more common in older and younger patients. For all cancers, young adult patients had less CS improvement over time than younger or older patients, and this difference was most pronounced in those aged 20 to 29 years (45% below the mean). Eleven of the 14 most common cancers in 15- to 39-year-olds either had a lower CS improvement after diagnosis than either younger or older patients, or than just the older patients. Young adults with leukemia had the greatest improvement in CS over time. In conclusion, young adults with cancer have not enjoyed the same improvement in CS over time compared with other age groups. Explanations for this deficit include the biologic nature of the type of cancers in young adults and less effective therapies for patients in the age group. Regardless of the reasons, the deficit is yet another challenge faced by young adult patients that merits further study.

Conditional survival rates of buccal and tongue cancer patients: how far does the benefit go?

The purpose of this study was to investigate the conditional survival probability in buccal and tongue cancer patients, and to identify the limit of increment in conditional survival probabilities after first diagnosis. This study retrospectively analyzed 339 consecutive patients with either buccal or tongue caner. The conditional survival probability was computed by Kaplan-Meier estimates, and the pair-wise Log-rank tests with Bonferroni correction were used to evaluate differences among conditional survival curves. It was found that the 3-year conditional survival rates for successive years of survival were 55.5%, 69.9%, 74.1% and 77.8%. The conditional survival curves started to become significantly better than the original survival curve at the twelfth month, and those curves after 24 months of survival were not significantly different from each other. Many previous studies have described the benefit of conditional survival probabilities for personalized information on better chance of survival, but only reported conditional survival probabilities and statistical tests for point-wise estimates. In this study, a new approach was adopted to conclude that the idea of conditional survival probability is best for the first 2 years in buccal and tongue cancer patients, and any longer survival time would not make significant difference in survival rates. The idea of pair-wise log-rank tests on conditional survival curves can provide statistical evidence for the critical time frame of survival in many different cancers.

Conditional survival in ovarian cancer: results from the SEER dataset 1988-2001

OBJECTIVES

Survival statistics for patients with ovarian cancer are typically reported in terms of survival from time of diagnosis. For patients who have survived a period of time since diagnosis, however, conditional survival (CS) is a more clinically relevant measure, as it accounts for the changes in risk over time. The purpose of this study was to estimate CS for ovarian cancer patients through analysis of large-scale cancer registry data.

METHODS

Ovarian cancer cases were extracted from the Surveillance, Epidemiology, and End Results (SEER 17) database from the National Cancer Institute (NCI) for patients diagnosed between 1988-2001. Five-year relative CS calculations were performed with stratification by age, race, stage, histology, and grade for patients who had already survived up to 5 years from diagnosis.

RESULTS

The 5-year overall relative CS improved over time for up to 5 years after diagnosis for ovarian cancer patients. The largest gains in CS over time were seen for patients with advanced stage disease, poor grade, and serous and undifferentiated epithelioid histologies. For patients with stage IV disease, 5-year CS more than tripled over the first 5 years of surveillance (17%-56%). Among histological types, patients with undifferentiated epithelioid histology saw 5-year CS rise from 29% at diagnosis to 84% after 5 years.

CONCLUSIONS

Prognosis improves over time for almost all groups of ovarian cancer patients. For ovarian cancer survivors, CS provides a more relevant measure of prognosis than conventional survival estimates that are made at the time of diagnosis.

Conditional survival in gastric cancer: a SEER database analysis

BACKGROUND

Gastric cancer survival is typically reported in terms of survival from the time of diagnosis. Conditional survival is a more relevant measure of prognosis for patients who have already survived 1 or more years since diagnosis.

METHODS

Using the Surveillance, Epidemiology, and End Results (SEER 17) database from the National Cancer Institute, we analyzed data from 20 018 gastric cancer patients diagnosed between 1988 and 1998. Using the life-table method, we computed 5-year relative conditional survival, grouped by summary stage, age, sex, and ethnicity, for patients who had already survived up to 5 years from diagnosis.

RESULTS

Relative conditional survival improves over time for all groups of gastric cancer patients who survive a period of time after diagnosis. The largest gains in conditional survival were seen in patients with advanced stage disease. In general, females showed better survival than males. When grouped by ethnicity, Asians continued to have improved survival compared to other ethnic categories, even at 5 years out from diagnosis.

CONCLUSION

For gastric cancer patients who survive a period of time after diagnosis, the largest increases in conditional survival are seen for patients with advanced stage disease and for those less than 65 years old. Conditional survival can provide more relevant prognostic information than survival from the time of diagnosis for gastric cancer patients who survive a period of time after diagnosis.

Conditional survival in head and neck squamous cell carcinoma: results from the SEER dataset 1973-1998

BACKGROUND

Survival statistics for patients with head and neck squamous cell carcinomas (HNSCC) are commonly calculated from the time of diagnosis. The less commonly employed conditional survival (CS) analyzes survival for patients who have survived a period of time after diagnosis. Useful prognostic information for cancer survivors is provided by CS analysis. Estimated baseline CS parameters for HNSCC were sought using large-scale cancer registry data.

METHODS

HNSCC cases identified from the Surveillance, Epidemiology, and End Results (SEER) Program were accessed to identify those diagnosed between 1973 and 1998. Five-year observed, relative, and cumulative CS calculations were performed, with secondary stratification by site, extent of disease, and age.

RESULTS

The overall 5-year observed survival for all sites increased from 47.8% for 76,181 included patients from the time of diagnosis to 64.4% for those 43,985 patients alive at 3 years, and thereafter plateaus. The greatest increase in CS was for oropharyngeal cancers, which more than doubled over the first decade of surveillance (26.5%-60%). Distant disease showed a 10-year increase in CS (17.4%-60.4%), whereas localized disease CS was essentially static, ranging from 66.1% to 68.5%; for those over 65 at diagnosis it ranged from 39.9-52.9%, whereas patients <65 years at diagnosis ranged from 53.8-73.5%.

CONCLUSIONS

Benchmark CS estimates for domestic HNSCC cohorts were developed from the SEER database. CS is a useful tool to assist clinicians in predicting the probability of demise from HNSCC for patients surviving 1 or more year after diagnosis.

Ethnic disparities in conditional survival of patients with non-small cell lung cancer

PURPOSE

Conditional survival (CS) is an accurate estimate of survival probability for patients who have already survived at least 1 year after diagnosis. The purpose of this study was to determine whether ethnicity plays a role in 5-year CS rates for patients with non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Using the Surveillance, Epidemiology, and End Results database, we analyzed 96,480 patients with NSCLC diagnosed between 1988 and 1995. Patients were divided into five ethnic groups: White (non-Hispanic), Hispanic, African American, Asian/Pacific Islander, and Native American/Alaskan. Using the life table method, we computed observed 5-year CS rates for patients who had already survived up to 5 years after diagnosis. Results were analyzed by stage, age, sex, and histology.

RESULTS

In general, 5-year CS rates increase for all ethnicities as time from diagnosis increases, but African Americans continued to have lower CS rates compared with other ethnic groups, even up to 5 years from diagnosis. When analyzed by stage, Hispanics with stage IV disease showed the greatest improvement in CS rate, increasing to 73% at 5 years from diagnosis. Among patients older than 70 years, African Americans had the lowest CS at 5 years--only 28%, compared with 40% to 47% for other groups. When analyzed by histology, Hispanics with large cell carcinoma had the worst CS rate (35% at 5 years).

CONCLUSION

For patients with NSCLC surviving a period of time after diagnosis, 5-year CS rates vary by ethnicity. CS can provide accurate prognostic information for patients with NSCLC who have already survived several years after diagnosis.

The conditional probabilities of survival in patients with anaplastic astrocytoma or glioblastoma multiforme

BACKGROUND

By the use of conditional probabilities of survival, we studied the yearly survival rates for individual tumor survivors.

METHODS

Conditional survival rate was estimated in 114 consecutive patients with anaplastic astrocytoma or glioblastoma multiforme. Conditional probabilities of surviving some years given survival to a specific period of time after craniotomy and 95% confidence intervals were calculated in the individual tumor survivors.

RESULTS

The estimated median survival was 30 months for 45 patients with anaplastic astrocytoma and 12 months for 69 patients with glioblastoma multiforme. The conditional probabilities of surviving next one year given survival to 1 year, 2 years, 3 years, 4 years, or 5 years after craniotomy for anaplastic astrocytoma were 86.2%, 75.0%, 85.9%, 77.8%, or 85.7%, respectively; for glioblastoma multiforme 64.8%, 58.7%, 85.7%, 80.0%, or 75.0%, respectively. The conditional probability of surviving to 5 years given survival to 2 years after craniotomy for anaplastic astrocytoma, i.e., surviving an additional 3 years, was 50.1%, which was better than observed 5-year survival rate (28.6%); for glioblastoma multiforme it was 40.2%, which also was better than observed 5-year survival rate (12.4%).

CONCLUSIONS

The conditional probability of survival was a good method to clinically predict yearly survival rate for individual tumor survivors. In addition, the method can estimate the probabilities of surviving next some years given survival to a specific period of time after craniotomy. It also showed a more encouraging result than observed survival rate in patients with supratentorial malignant astrocytomas.

[Outcome of surgical treatment of malignant astrocytoma of the brain]

BACKGROUND

The aim of this study was to analyze the outcome after the surgical treatment of patients with malignant brain astrocytomas, as well as the factors influencing the outcome. Retrospective study was performed on 145 operated patients (102 with glioblastoma multiforme, and 43 with anaplastic astrocytomas).

METHODS

Clinical state was graded according to the Yasargil scale (grades I-IV) and the Karnofski score, and the outcome was defined either as good (better or unchanged clinical state) or as poor (deteriorated state or death). The outcome was correlated with patients age and preoperative clinical condition, as well as with the localization, extensiveness and the extent of resection of the tumor.

RESULTS

Preoperative clinical state of patients most frequently corresponded to grades II-III (75.9%). Radical resection was done in 48.3%, subtotal in 15.2%, partial in 30.3%, and biopsy was performed in 6.2% of patients, with the total operative mortality of 16.5%, morbidity of 9.7%, and good postoperative outcome in 73.8% of the patients. The incidence of good postoperative outcome did not significantly depend on the tumor location (42.6-78.3%), cortical presentation, the extent of resection (68.2-75.7%), and preoperative clinical state (67.8-81.5%). Good outcome was seen in 82.7% of patients with one, and in 53.8% of patients with three or more infiltrated lobes (p < 0.01). Patients with poor outcome were significantly older in average than the patients with good outcome (58.9 +/- 12.1 and 50.9 +/- 13.4 years of age, respectively; p < 0.05). Operative mortality was 7.4%, and 27.3% for clinical grades II and IV (p < 0.05), namely 11% and 23.8% for the patients with the Karnofski score above and under 50 (p < 0.05), respectively.

CONCLUSION

The outcome after the operative treatment of malignant cerebral astrocytomas significantly depended on patients age and the extensity of the tumor. For such patients operative mortality was also significantly influenced by clinical preoperative state.