Multivariate Analyses to Assess Treatment Effectiveness in Advanced Head and
Neck Cancer


Author Information
<http://archotol.ama-assn.org/issues/v128n5/rfull/#aainfo>   Urjeet Patel,
MD; Edward Spitznagel, PhD; Jay Piccirillo, MD
Objective  To assess relative benefit of combined radiotherapy and surgery
over single-modality treatment for advanced-stage squamous cell carcinoma of
the aerodigestive tract by means of several multivariable analyses to
control for patient variables.
Design  Medical chart review.
Setting  University medical center.
Patients and Methods  The study included 532 patients receiving initial
therapy between January 1, 1980, and December 31, 1989. Three multivariate
techniques (multiple logistic regression, propensity score stratification,
and conjunctive consolidation) were used to compare outcomes for treatment
groups.
Main Outcome Measure  Five-year survival.
Results  Survival for radiation, surgery, and combined treatment groups were
24%, 40%, and 46%, respectively. With the use of multiple logistic
regression to control patient variables, the radiation group had a
significantly lower survival than the combined therapy group (risk ratio,
2.24; 95% confidence interval, 1.32-3.80), while there was no statistical
difference for the surgery group compared with the combined therapy group
(risk ratio, 1.26; 95% confidence interval, 0.78-2.03). When analyzed by
propensity score, 5-year survival was higher in each quintile for the
combined therapy group than for the group who received radiation alone (P =
.002). There was no significant difference in survival between the surgery
and combined treatment groups (P = .25). Conjunctive consolidation was used
to create a clinical staging system to compare outcomes across treatment
groups. In each clinical severity stage, radiation alone had a lower
survival than combined therapy (P = .001), while no statistical difference
was noted between surgery and combined therapy (P = .50).
Conclusions  All 3 statistical techniques showed a significantly lower
survival for patients treated with radiation alone vs combined therapy. No
significant difference was noted between surgery and combined therapy.
Propensity score analysis and conjunctive consolidation are useful
techniques to control prognostic variables in cancer database studies and
should be used in future outcome studies that address more current treatment
dilemmas in head and neck oncology.
Arch Otolaryngol Head Neck Surg. 2002;128:497-503
OOA10007
COMBINED SURGERY and postoperative radiotherapy are often used to treat
stages III and IV squamous cell carcinoma of the upper aerodigestive tract.
1 <http://archotol.ama-assn.org/issues/v128n5/rfull/#r1>  The choice of
combined treatment over single-modality treatment often hinges on clinical
factors such as primary site, tumor size, and extent of regional metastasis.
Some centers report improved locoregional control with combined therapy,
while others report improved survival; however, controversy exists over the
benefit of combined therapy in various clinical settings. 2-4
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r2>
The criterion standard for assessing the merits of a given treatment is the
prospective randomized trial. Accordingly, such trials have long been
advocated; however, these trials in head and neck cancer treatment are
inherently problematic and rare. The main problem is the heterogeneity of
the study population in terms of tumor stage, primary site, histologic
grade, age, and small sample size for any given research trial. In addition,
it is often difficult to randomize patients to treatments that are so
markedly different, as patients are hesitant to leave such grossly
dissimilar options to chance alone. Therefore, studies of treatment
effectiveness in head and neck cancer are often relegated to the realm of
observational studies, where patients are not randomized to particular
treatments.
The goal of the observational study is to measure treatment effectiveness.
One of the major difficulties in the analysis of results from observational
studies is that the same clinical variables that affect patient outcomes
(age, stage, comorbidity, etc) also impact on treatment choice. 5
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r5>  This may lead to
treatment selection bias. Thus, an observational study must also seek to
control selection bias to accurately measure treatment effect.
The goal of this study was to use observational data to assess the relative
benefit of combined surgery and radiotherapy over single-modality treatment
for advanced-stage squamous cell carcinoma of the upper aerodigestive tract.
To accomplish this goal, multiple statistical techniques were used to
control for selection bias.



PATIENTS AND METHODS



POPULATION UNDER STUDY

We studied 532 patients with newly diagnosed TNM stage III or IV
biopsy-proved squamous cell carcinoma who were first treated at Washington
University Medical Center, St Louis, Mo, between January 1, 1980, and
December 31, 1989. These patients were initially identified by means of
records from the pathology department of Barnes-Jewish Hospital, St Louis.
Patients with American Joint Committee on Cancer (AJCC) TNM stage III or IV
squamous cell carcinoma of the oral cavity, oropharynx, or larynx who were
initially treated with radiotherapy, surgery, or combined radiation and
surgery were included in the study population. 6
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r6>  Patients with
metastatic disease at the time of diagnosis were excluded from the study, as
were patients who received therapy other than the 3 above-mentioned
treatment options. Baseline and follow-up information was obtained from
inpatient medical records as well as records from the Departments of
Otolaryngology and Radiation Oncology. Full 5-year follow-up information was
obtained for all 532 patients. Supplemental date of death and death
certificate information was obtained from Equifax National Death Search
(Arlington, Va).
COLLECTION OF DATA

Specially designed data extraction forms were used to ensure uniform data
collection from the medical records. Data collected from the pretreatment
interval and at the time of presentation included basic demographic
information, risk factors, medical history, symptom type and duration,
complete anatomic description of the tumor including the TNM classification
with the 1992 AJCC criteria, 6
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r6>  pathological
description of the biopsy specimen, and details of subsequent therapy. The
zero-time for each patient was chosen as the date of first antineoplastic
intervention directed at the primary site. Follow-up data, including
development of recurrence, new primary, and subsequent treatment, were also
collected. Patient and tumor status at last follow-up or death was obtained.
CLASSIFICATION OF DATA

To maintain scientific accuracy and ensure high quality of data,
imperfections in data obtained from retrospective studies must be managed in
a systematic and consistent manner. The general methods for such management
have been previously described. 7-9
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r7>
SYMPTOM SEVERITY

To study the prognostic importance of symptoms for a specific cancer type,
the presence of symptoms and their relationship to the primary cancer must
be clearly established. To manage possible discrepancies in the medical
record, 2 conventions were consistently applied. If a symptom was recorded
by at least 1 examiner, the symptom was regarded as present. If different
periods of duration were reported, the longer duration was recorded.
The details of symptom severity staging as used in our study have been
previously described. 8
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r8>  Briefly, the
symptoms of dysphagia, otalgia, neck lump, and weight loss were found to be
independent predictors of survival. Accordingly, a symptom severity staging
system was developed on the basis of the presence of these symptoms. Stage
was defined as none if none of the 4 symptoms was recorded, mild if 1 of the
4 symptoms was recorded, moderate if 2 of the 4 symptoms were recorded, and
severe if 3 or 4 of the 4 symptoms were recorded.
COMORBIDITY

The presence of concomitant disease unrelated to the disease under study is
termed comorbidity. Comorbidity has been shown to clearly impact on survival
and treatment selection in several types of cancer. 10-12
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r10>  The
Kaplan-Feinstein index was used to classify comorbidity for this study. 13
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r13>  This scheme was
used to classify the patients' comorbidity as none, mild, moderate, or
severe (grades 0, 1, 2, or 3, respectively). When a patient's condition was
described in the medical record as too sick to tolerate standard
antineoplastic therapy, a grade of 3 was assigned regardless of other
illnesses. Prognostic comorbidity was defined as grade 3, signifying the
presence of concomitant illness that significantly reduces a patient's life
expectancy.
CANCER STAGING

The staging criteria for all tumors were reviewed according to the AJCC
cancer staging manual. 6
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r6>  All information
obtained before the zero-time was used to assess accuracy of the recorded
stage as dictated by the AJCC rules. In the case of staging discrepancies
between written notes by different physicians where the medical record
lacked sufficient anatomic information to accurately restage the tumor, the
stage assigned by the most senior otolaryngologist or radiation oncologist
was recorded. Information regarding the presence of cervical adenopathy was
lacking in 4 members of the final cohort. It was known that they had stage
III or IV disease based on T stage alone; subsequently, they were included
in the study. These members were omitted from aspects of data analysis
requiring exact node status information.
PATHOLOGICAL EXAMINATION

The histologic grade of the primary tumor was recorded from the biopsy or
primary specimen for all patients, and grades were grouped into categories
of well, moderately, and poorly differentiated. If both biopsy specimen and
primary tumor were available, the biopsy specimen was used to define the
histologic grade. Specimens graded as moderately to well differentiated were
recorded as moderate, and those graded as moderately to poorly
differentiated were recorded as poor. Histopathologic grade was absent for 4
patients; these members were omitted from data analyses requiring
pathological information.
PRIMARY TREATMENT

Information regarding each patient's initial treatment included type of
treatment (radiotherapy, surgery, or combined treatment), type of surgical
procedure, timing of radiotherapy (preoperative or postoperative), and
therapeutic complications. Subsequent treatment was defined as treatment
initiated secondary to failure of primary therapy and was also recorded.
FOLLOW-UP AND OUTCOME

Each patient was monitored for persistence, recurrence, and development of
new primary cancer. Follow-up was considered complete when either a
patient's death was documented or a minimum of 5 years' survival was
obtained. The primary outcome measure presented in this study was 5-year
survival.
DATA ANALYSIS

The primary objective of data analysis was to estimate any possible benefit
on 5-year survival of combined therapy over either radiation or surgery
alone. The possible benefit was estimated by 3 separate multivariable
statistical techniques: multivariate logistic regression, propensity score
stratification, 14 <http://archotol.ama-assn.org/issues/v128n5/rfull/#r14>
and conjunctive consolidation. 12
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r12>
The information from the data extraction forms was entered into a Paradox
database (Borland International, Scotts Valley, Calif). The specially
designed database screens were equipped with internal validity checks that
facilitated reliable and efficient data entry. Periodic review for internal
consistency and comparison with separate databases was performed to ensure
accuracy of data entry. Sorting, tabulation, and statistical analyses were
performed with the SAS system, release 6.12 (SAS Institute Inc, Cary, NC).
Logistic Regression
The impact of covariates and initial treatment options on 5-year survival
was evaluated by multiple logistic regression (PROC LOGIST function). The
logistic regression modeled the dependent variable of 5-year survival from
the independent patient, tumor, and treatment variables. A regression model
was fit with the use of the following covariates: age group, sex, race,
prognostic comorbidity, symptom severity, pathological findings, tumor size,
presence of adenopathy, primary site, and initial treatment choice. Of the
532 patients, 7 were eliminated from the regression model because of missing
information as described in the "Cancer Staging" and "Pathological
Examination" subsections. The multivariable regression had an area under the
receiver operating characteristic curve of 0.72. This means that the
regression model was fairly accurate in discriminating survivors from
nonsurvivors on the basis of covariate information. Adjusted risk ratios and
corresponding 95% confidence intervals and P values were obtained according
to reference groups for each variable.
Propensity Score
The goal of propensity analysis is to reduce the effect of selection bias
between 2 treatment options as described by Rosenbaum and Rubin. 15-17
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r15>  Selection bias is
clearly problematic in observational studies when clinical covariates (age,
comorbidity, tumor stage, etc) impact on both treatment (radiation, surgery,
or combined therapy) and outcome (5-year survival). Propensity score
stratification seeks to replace the wide host of confounding covariates that
may be present in an observational study with a single variable function of
these covariates. The covariates are summarized into a single probability
function called the propensity score that describes the likelihood of
receiving treatment A (surgery plus radiation, for example) vs treatment B
(radiation alone). The propensity score can be estimated through logistic
regression of the covariates on treatment choice. Accordingly, each
individual has a propensity score that represents the probability of being
treated with combined therapy rather than radiation alone. The propensity
score is then used in further analysis as the single confounding variable.
The study population is then stratified into a discrete number of groups,
usually 5, on the basis of the propensity score. Stratification into 5
quintiles has been shown by Rosenbaum 18
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r18>  to eliminate more
than 90% of selection bias by covariates. Within each propensity stratum,
there will generally be a number of patients who received combined therapy
or radiation alone. The rationale behind the propensity score scheme is as
follows: If 2 patients have the same propensity score, then it follows that
they have the same likelihood of receiving combined treatment as radiation
alone on the basis of their given covariates. If the 2 patients receive
different treatments, then the choice of treatment can be considered random.
The same principle holds for 2 groups with similar propensity scores. Within
a given propensity stratum, the group of patients receiving combined therapy
will have a distribution of propensity scores similar to that of patients
who received surgery alone. Subsequently, the patients composing one
treatment group can be considered to be randomly chosen from the entire
propensity stratum with regard to their confounding covariate data. Within a
propensity stratum, the multivariate distribution of covariates should
differ only randomly between the 2 treatment groups as if they had been
randomly assigned a treatment option. Thus, use of this technique with
stratification into quintiles eliminates selection bias between 2 treatment
groups. 15 <http://archotol.ama-assn.org/issues/v128n5/rfull/#r15>
In our study, propensity score analysis was first used to assess treatment
effect between patients receiving combined therapy vs radiation alone. To
identify variables that were unbalanced between the 2 treatment groups,
bivariate screening was performed for all potential confounding covariates
that potentially impact on treatment decision. A multiple logistic
regression was performed in a stepwise fashion to determine important
predictors of treatment selection. A logistic regression model was then fit
with variables found to be significant (P<.15) in the logistic analysis. The
area under the receiver operating characteristic curve for this regression
model was 0.76, indicating good discrimination between patients receiving
combined vs single therapy. With this model, a propensity score was
calculated for each patient that predicts the likelihood of being initially
treated with combined surgery and radiation therapy vs radiation alone. 19
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r19>  Patients were then
sorted by propensity score and clustered into quintiles accordingly.
Bivariate screening and logistic regression were then performed within each
quintile to identify any remaining bias among covariates after
stratification by propensity score. The effect of treatment assignment on
5-year survival was then analyzed within each quintile. The Mantel-Haenszel
odds ratio was calculated in addition to the Cochran-Mantel-Haenszel (CMH)
chi2. The Mantel-Haenszel odds ratio represents a composite of the 5 odds
ratios derived from each quintile, and the CMH chi2 reflects the statistical
significance of the odds ratio. The Breslow-Day test, which indicates
whether there is homogeneity of the odds ratios among the 5 quintiles, was
also performed. 20 <http://archotol.ama-assn.org/issues/v128n5/rfull/#r20>
The same process described above was then repeated for the comparison of
combined therapy vs surgery alone. A similar regression model was fit with
significant covariates. The area under the receiver operating characteristic
curve for this model was 0.67, indicating good discrimination of treatment
options. Similar analysis to estimate the effect of treatment assignment was
then performed after estimation of the propensity scores and stratification
into propensity quintiles.
Conjunctive Consolidation
An alternative multivariable technique produces clusters of patients through
conjunctive consolidation and is exemplified by the TNM staging systems. 12
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r12>  Use of conjunctive
consolidation to evaluate treatment effect has been previously described. 12
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r12>  Under this system,
patients are stratified according to values of the prognostic covariates
(such as TNM, age, comorbidity, etc). With the addition of each new
variable, the number of strata grows and the number of patients within each
stratum decreases. The problem with addition of numerous variables is the
exponential growth in the number of stratified groups of patients, making
further analysis of patients within each group difficult. Through
conjunctive consolidation, groups of categories are clustered by means of
unions and intersections of Boolean algebra. 12
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r12>  This process is the
cross-table analysis of the conjoined effect of 2 variables on the outcome
of interest. Each conjoined cell contains patients with similar values for
the 2 variables being conjoined. Adjacent cells can then be combined
according to clinical and statistical similarity. This allows for the
inclusion of numerous clinical factors while avoiding the subsequent
increase in number of categories.
To assemble data for evaluating the prognostic covariates, patients were
combined according to a therapeutic "nil hypothesis," as previously
described. 12 <http://archotol.ama-assn.org/issues/v128n5/rfull/#r12>  This
makes a tentative clinical assumption that treatment had no effect on a
patient's clinical course. With this assumption made, the data were combined
for all patients regardless of treatment. Patients were then categorized
according to their nontherapeutic prognostic covariates, and survival
outcomes were then analyzed for each category. After prognostic factors were
consolidated according to the nil hypothesis, the impact of different
treatment options was explored for patients within given stages.
In the present study, the technique of conjunctive consolidation was first
applied to combine 2 clinical variables, age group and prognostic
comorbidity, into a 3-category composite functional staging system. Patients
younger than 55 years with no comorbidity were categorized as stage alpha,
those aged 55 to 69 years with no comorbidity as stage beta, and those older
than 69 years or with prognostic comorbidity as stage gamma. The cancer
variables of tumor size and presence of adenopathy were then combined to
form a composite tumor staging system (1, 2, and 3). Patients with T3,4 N0
disease were combined with patients with T1 N1 disease into cancer stage 1;
T2 N1 was classified as stage 2; and T3,4 N1 was categorized as stage 3. The
functional stage and the tumor stage were next combined to create a
composite clinical severity staging system (A, B, C, and D). Stage alpha1
was classified as composite stage A. Stages alpha2 and beta1 were combined
into composite stage B. Stages alpha3, beta2, beta3, gamma1, and gamma2 were
combined into stage C. Finally, stage gamma3 was classified as stage D. With
the use of conjunctive consolidation in this manner, the 4 covariates of
age, comorbidity, tumor size, and cervical adenopathy were conjoined into a
4-category composite clinical severity staging system.
The association between clinical severity stage and 5-year survival was
examined. There was a strong relationship that was both clinically
impressive and statistically significant. The chi2 for linear trend was P =
.001. Next, treatment effect was examined within composite clinical severity
stage groups. Patients were grouped according to initial treatment within
composite stages. Survival rates were calculated for each treatment group by
composite stage. A chi2 test of significance was performed by comparing
survival rates across the different therapies within composite clinical
severity staging groups. The Mantel-Haenszel odds ratio was then calculated
for each single modality treatment vs combined therapy in addition to the
CMH chi2. The Breslow-Day test was also performed to verify that the odds
ratios derived from each stage were homogeneous.



RESULTS



The characteristics of the 532 study patients are presented in Table 1
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t1.html> . The
study population was 70% male, and more than 75% were white. Most patients
had either absent or mild comorbidity as well as symptom severity. More than
65% had evidence of cervical adenopathy and were equally divided between TNM
stage III and stage IV disease. Disease was most prevalent in the oropharynx
(40%), followed by the larynx (35%) and then the oral cavity (25%). The most
common initial treatment plan was combined surgery plus radiation (52%),
followed by radiation alone (25%) and then surgery alone (23%).
The relationship between covariates, including treatment and survival, is
also shown in Table 1
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t1.html> .
Patient characteristics that were associated with decreased survival
included increasing age (P = .01), increasing comorbidity (P = .03), and
increasing symptom severity (P = .002). Presence of cervical adenopathy was
associated with a significant decrease in survival from 47% to 35% (P =
.01). Laryngeal cancer was associated with the highest 5-year survival at
47%, compared with oral cavity and oropharyngeal disease at 37% and 33%,
respectively. Looking at treatment, radiation alone was associated with
significantly lower survival of 24% while survival rates for combined
therapy and surgery alone were 46% and 40%, respectively.
Multivariate logistic regression was used to assess the impact of covariates
and treatment on survival. Table 2
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t2.html>  shows
the adjusted risk ratios for covariates and treatment for the study
population. Increasing age and male sex were both related to a decreased
5-year survival rate. Similarly, the presence of cervical adenopathy and
tumor size greater than stage 1 impact negatively on survival. With regard
to primary site, patients with cancer of the oral cavity and oropharynx had
significantly higher risk of death than the patients with laryngeal cancer.
With regard to treatment, the group of patients treated with radiation alone
had a significantly higher risk of death than those receiving combined
therapy (risk ratio, 2.24; 95% confidence interval, 1.32-3.80). While
treatment with surgery alone did reflect an increased risk of death compared
with patients receiving combined treatment, this risk was not found to be
statistically significant (risk ratio, 1.26; 95% confidence interval,
0.78-2.03).
Stratification by propensity score and assessment of the treatment effect of
each single-modality treatment and combined therapy on survival were
performed. The population receiving either radiation alone or combined
therapy was examined first (n = 410). The population was stratified into
propensity quintiles as previously described. Table 3
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t3.html>  shows
survival rates for both treatment groups after stratification. The
percentage of patients receiving combined therapy decreased from the first
propensity quintile to the fifth as predicted by the propensity model. In
each of the 5 strata, patients receiving combined therapy had a higher
5-year survival rate than the group receiving radiation alone. In quintiles
1 and 3, the difference in survival was statistically significant. The P
value for the CMH chi2 comparing survival between the treatment groups while
controlling for propensity quintile was .002, suggesting a strong difference
in survival between those receiving radiation alone vs combined treatment.
Propensity score analysis was similarly performed for patients initially
receiving either surgery alone or combined therapy (n = 397). Table 4
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t4.html>  shows
survival rates for these treatment groups after propensity score
stratification. As expected, the percentage of patients receiving combined
therapy decreased from the first to the fifth quintile. Within quintile 2,
patients receiving surgery alone had a higher survival than those receiving
combined treatment, while in the remaining quintiles, patients with combined
treatment had more favorable survival. In none of the quintiles was the
difference in survival statistically significant. The P value for the CMH
chi2 was .25, suggesting no significant difference between treatment groups
across quintiles.
Conjunctive consolidation was performed as previously described. Table 5
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t5.html>  shows
survival rates for all patients according to composite stage (A, B, C, or
D). A prognostic gradient was noted in survival from stage A through stage
D, with a significant chi2 for linear trend (P = .001). Patients were
separated into treatment group, and survival rates were then compared within
composite staging groups ( Table 6
<http://archotol.ama-assn.org/issues/v128n5/fig_tab/ooa10007_t6.html> ). In
all 4 composite staging groups, survival rates were higher for patients
receiving combined therapy compared with radiation alone, with a
statistically significant difference noted in 3 of the 4 stages. The CMH
chi2 was highly significant (P = .001). Comparing groups receiving combined
therapy vs surgery alone, survival was higher for combined therapy in stages
A, B, and D, while surgery alone was favored for stage C patients. In only
stage D was there a statistically significant difference in survival between
patients receiving surgery vs combined treatment. No statistical difference
was noted between the 2 groups by the CMH chi2 (P = .50).



COMMENT



Our research demonstrates the usefulness of multivariate analysis with
regard to head and neck oncology observational studies. The relative benefit
of combined therapy over single-modality therapy was assessed by means of
multiple logistic regression, propensity score analysis, and conjunctive
consolidation. The 3 forms of analysis concurred in their findings that
combined therapy offered significantly higher survival at 5 years than
radiotherapy alone. In contrast, no significant difference was seen when
combined therapy was compared with surgical treatment alone. By using
multivariate analysis to eliminate selection bias, the difference in
survival can be attributed to treatment effect without the influence of
confounding variables.
Previous studies have compared combined therapy with single-modality
treatment for various tumors in the head and neck region. 21-24
<http://archotol.ama-assn.org/issues/v128n5/rfull/#r21>  While many of these
studies seek to measure treatment effect, few of them compare different
treatment options while controlling for selection bias. Patient variables
such as comorbidity, pathological grade, symptom severity, and age are often
omitted from analysis despite the fact that these variables may influence
treatment choice as well as outcome. Subsequently, conclusions are drawn
regarding treatment effectiveness without adequately controlling for
potential selection bias. Without such control, the conclusions may not
accurately assess true treatment effectiveness.
While multivariate analysis does permit a more controlled estimate of
treatment effectiveness, there do exist potential inaccuracies in its
formulation. Each multivariate model is able to control only the study
variables included in the analysis. In our study, there was no variable to
quantify the amount of radiotherapy given to each patient, nor was there any
measure in the quality of the surgery performed. Subsequently, it is
possible that variables exist that would alter the measured treatment
effects had they been included in the multivariate analysis. In addition, a
given multivariate analysis makes use of statistical models to approximate
the data being analyzed. The degree to which a given model fits the data
appropriately can vary and needs to be considered when the results of
statisitical analysis are interpreted. This is especially true when
different statistical tools yield varying results when the same data are
analyzed.
Multivariate analysis is a highly useful tool to measure treatment effect in
observational studies. Multiple logistic regression is a statistical
technique that is frequently used in analysis of observational study
results. Propensity score analysis and conjunctive consolidation are also
highly effective at controlling selection bias to measure treatment
effectiveness. The use of these techniques will improve the ability to
accurately measure treatment effectiveness in observational studies. These
tools may be applied to more current clinical dilemmas, such as
chemoradiation protocols compared with surgical resection for treatment of
head and neck cancer.



Author/Article Information


From the Departments of Otolaryngology (Drs Patel and Piccirillo) and
Mathematics (Dr Spitznagel), Washington University, St Louis, Mo.

Corresponding author and reprints: Jay Piccirillo, MD, Department of
Otolaryngology, 660 S Euclid St, Box 8115, St Louis, MO 63110 (e-mail:
[log in to unmask] <mailto:[log in to unmask]> ).
Accepted for publication October 11, 2001.
This study was supported in part by grant R01CA2072 from the National Cancer
Institute, Bethesda, Md (Dr Piccirillo).
This study was presented at the Fifth International Conference on Head and
Neck Cancer, San Francisco, Calif, July 31, 2000.




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Edward E. Rylander, M.D.
Diplomat American Board of Family Practice.
Diplomat American Board of Palliative Medicine.